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A comparison of weekend and weekday travel behavior characteristics in urban areas

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Title:
A comparison of weekend and weekday travel behavior characteristics in urban areas
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Book
Language:
English
Creator:
Agarwal, Ashish, 1980-
Publisher:
University of South Florida
Place of Publication:
Tampa, Fla.
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Subjects

Subjects / Keywords:
NHTS
NPTS
Household Travel Survey
Demographic
Socioeconomic
Personal
Vehicle Occupancy
SEM
Structural Equation Modeling
Activity Behavior
Dissertations, Academic -- Civil Engineering -- Masters -- USF   ( lcsh )
Genre:
government publication (state, provincial, terriorial, dependent)   ( marcgt )
bibliography   ( marcgt )
theses   ( marcgt )
non-fiction   ( marcgt )

Notes

Summary:
ABSTRACT: Travel demand analysis has traditionally focused on exploring and modeling travel behavior on weekdays. This emphasis on weekday travel behavior analysis was largely motivated by the presence of well-defined peak periods, primarily associated with the journey to and from work. Most travel demand models are based on weekday travel characteristics and purport to estimate traffic volumes for daily or peak weekday conditions. Much of the planning and policy making that occurs in transportation arena in response to weekday travel behavior and forecasts. More recently, there had been a growing interest in exploring, understanding, and quantifying weekend travel characteristics. The ability to do this has been limited due to the non-availability of travel survey data that includes weekend trip information. Most travel surveys collect information about weekday travel behavior and ignore weekend days. However, the 2001 National Household Travel Survey includes a substantial sample that provided detailed trip information for weekend days and therefore this dataset offers a key opportunity to explore in-depth weekend travel characteristics. Weekend travel behavior is expected to be substantially different from the weekday travel behavior for difference in several spatial and temporal constraints. The difference in constraints can also lead to a change in trip chaining patterns on weekdays and weekends. Differences in constraints coupled with socio-economic changes characterized by greater disposable income, time-constrained lives, and greater discretionary activity opportunities point towards the growing role that weekend travel behavior is going to play in transportation planning and policy-making. This thesis provides a comprehensive analysis of weekend travel behavior using the 2001 NHTS. Differences and similarities between weekday and weekend travel behavior are identified and presented for different urban areas sizes varying according to Metropolitan Statistical Area (MSA) size. Models of weekend and weekday travel behavior are developed to capture the structural relationship of socio-demographics, activity durations, and travel duration are developed using structural equations modeling approaches to better understand the relationships among these aspects of travel behavior on weekdays and weekends. This report is supposed to act as an updated data guide to the National Cooperative Highway Research Program's (NCHRP) Report 365 titled "Travel Estimation Techniques for Urban Planning" aims at studying the changes in behavioral characteristics between two categories of the day of week - a weekday and a weekend based on personal, household and trip characteristics.
Thesis:
Thesis (M.S.C.E.)--University of South Florida, 2004.
Bibliography:
Includes bibliographical references.
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System requirements: World Wide Web browser and PDF reader.
System Details:
Mode of access: World Wide Web.
Statement of Responsibility:
by Ashish Agarwal.
General Note:
Title from PDF of title page.
General Note:
Document formatted into pages; contains 193 pages.

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aleph - 001478758
oclc - 56389829
notis - AJS2448
usfldc doi - E14-SFE0000400
usfldc handle - e14.400
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SFS0025092:00001


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ABSTRACT: Travel demand analysis has traditionally focused on exploring and modeling travel behavior on weekdays. This emphasis on weekday travel behavior analysis was largely motivated by the presence of well-defined peak periods, primarily associated with the journey to and from work. Most travel demand models are based on weekday travel characteristics and purport to estimate traffic volumes for daily or peak weekday conditions. Much of the planning and policy making that occurs in transportation arena in response to weekday travel behavior and forecasts. More recently, there had been a growing interest in exploring, understanding, and quantifying weekend travel characteristics. The ability to do this has been limited due to the non-availability of travel survey data that includes weekend trip information. Most travel surveys collect information about weekday travel behavior and ignore weekend days. However, the 2001 National Household Travel Survey includes a substantial sample that provided detailed trip information for weekend days and therefore this dataset offers a key opportunity to explore in-depth weekend travel characteristics. Weekend travel behavior is expected to be substantially different from the weekday travel behavior for difference in several spatial and temporal constraints. The difference in constraints can also lead to a change in trip chaining patterns on weekdays and weekends. Differences in constraints coupled with socio-economic changes characterized by greater disposable income, time-constrained lives, and greater discretionary activity opportunities point towards the growing role that weekend travel behavior is going to play in transportation planning and policy-making. This thesis provides a comprehensive analysis of weekend travel behavior using the 2001 NHTS. Differences and similarities between weekday and weekend travel behavior are identified and presented for different urban areas sizes varying according to Metropolitan Statistical Area (MSA) size. Models of weekend and weekday travel behavior are developed to capture the structural relationship of socio-demographics, activity durations, and travel duration are developed using structural equations modeling approaches to better understand the relationships among these aspects of travel behavior on weekdays and weekends. This report is supposed to act as an updated data guide to the National Cooperative Highway Research Program's (NCHRP) Report 365 titled "Travel Estimation Techniques for Urban Planning" aims at studying the changes in behavioral characteristics between two categories of the day of week a weekday and a weekend based on personal, household and trip characteristics.
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PAGE 1

A Comparison of Weekend and Weekday Travel Behavior Characteristics in Urban Areas by Ashish Agarwal A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Civil Engineering Department of Civil and Environmental Engineering College of Engineering University of South Florida Major Professor: Ram M. Pendyala, Ph.D. Jian J. Lu, Ph.D., P.E. Steven E. Polzin, Ph.D., P.E. Date of Approval: May 27, 2004 Key Words: NHTS, NPTS, Household Travel Survey, Demographic, Socioeconomic, Personal, Vehicle Occupancy, SEM, Struct ural Equation Modeling, Activity Behavior Copyright 2004, Ashish Agarwal

PAGE 2

DEDICATION This thesis is dedicated to my father, Late Sh ri Roshan Lal, and my mother Smt. Raj Rani for their love and affection. I am indebted to them for their support and encouragement. I would also like to dedicate this thesis to my brother and sister for their encouragement.

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ACKNOWLEDGEMENTS I wish to express my sincere gratitude to Dr. Ram M. Pendyala, my major professor, for his consistent support and encouragement th roughout the two years of my study at the University of South Florida. I am greatly i ndebted to him for his help and support in the pursuit of my goals and research interests. I would like to th ank Dr. Steven E. Polzin, Dr. Jian John Lu, and Dr. Juan Pernia for se rving on my committee and providing their valuable suggestions apart from their gui dance in coursework I also thank the Department of Civil and Environmental Engi neering for providing w ith such excellent facilities and research envir onment. I would also like to thank the faculty members Dr. Xuehao Chu and Dr. Edward A. Mierzejew ski of Center for Urban Transportation Research (CUTR) for the excellent course work they provided during the Masters program. Finally, I would like to thank my friends and collea gues: Siva S. Jonnavithula, Srikanth Vadepalli, Abdul R. Pinjari, Constantinos A. Tringides, Manohar B. Reddy, Rajan Malik, Vijay Rudrabhatla, Vivek Bansal, Aleem Khan and Rajarshi Sengupta for their support and encouragement throughout the research work.

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i TABLE OF CONTENTS LIST OF TABLES iii LIST OF FIGURES vii ABSTRACT x CHAPTER 1: INTRODUCTION 1 1.1 Background 1 1.2 Weekdays and Weekends 5 1.3 Objectives and Scope of this Study 6 1.4 Organization 6 CHAPTER 2: LITERATURE REVIEW 8 2.1 Introduction 8 2.2 Multi-Day Versus One-Day Travel Survey Diaries 9 2.3 Effect of Socio-Demographics 10 2.4 Changes in Travel Behavior 15 2.4.1 Trip Rates 15 2.4.2 Activities/Trip Purposes 16 2.4.3 Travel Time Length or Duration 19 2.4.4 Vehicle Occupancy 20 2.4.5 Time of Day 20 2.5 Seasonal/Monthly Variation 23 2.6 Transit Ridership 24 2.7 Suggestions to Policy Makers 25 CHAPTER 3: DATA DESCRIPTION 26 3.1 Introduction 26 3.2 National Travel Surveys 27 3.3 2001 National Household Travel Survey (NHTS) 28 CHAPTER 4: COMPARISON OF PERSON AND VEHICLE TRIP RATES 36 4.1 Introduction 36 4.2 Trip Rates by Household Characteristics 37 4.3 Trip Rates by Person Characteristics 55 4.4 Trips by Purpose 61

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ii CHAPTER 5: DIFFERENCES IN TRIP LENGTH AND DURATION 66 5.1 Introduction 66 5.2 Distribution of Trip Lengths 67 5.3 Total Travel per Hous ehold and per Person 78 5.4 Gender Differences 80 5.5 Modal Differences 81 5.6 Effect of Income 86 CHAPTER 6: MODAL COMPARISON 89 6.1 Introduction 89 6.2 Distribution of Person Trips 90 6.3 Distribution of Trips by Mode and Trip Length 96 6.4 Gender Differences 100 CHAPTER 7: VARIATION IN VEHICLE OCCUPANCIES 102 7.1 Introduction 102 7.2 Occupancy by Trip Purpose 103 7.2.1 Urban Area Size and Purpose 103 7.2.2 Trip Purpose and Income 104 7.2.3 Trip Purpose and Trip Length 105 7.3 Occupancy by Gender and Trip Length 106 CHAPTER 8: DIURNAL DI STRIBUTION OF TRIPS 109 8.1 Introduction 109 8.2 Distribution of Person Trips by Mode 109 8.3 Distribution of Vehi cle Trips by Purpose 124 8.4 Gender Differences 125 8.5 Occupancies by Purpose and Trip Start Time 153 CHAPTER 9: MODELING OF ACTIVI TY AND TRAVEL BEHAVIOR 157 9.1 Introduction 157 9.2 Model Specification 157 9.3 Data Preparation 159 9.4 Theory of Structural Equations Modeling 162 9.5 Model Estimation Results 165 9.5.1 Weekdays 166 9.5.2 Weekends 169 CHAPTER 10: CONCLUSIONS AND FURTHER RESEARCH 172 10.1 Conclusions 172 10.2 Further Research 173 REFERENCES 175

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iii LIST OF TABLES Table 3.1 Categorization of Home Based Trips 32 Table 3.2 Household Characteris tics of the Urban Areas from 2001 NHTS 33 Table 3.3 Person Characteristics of the Urban Areas from 2001 NHTS 34 Table 3.4 Percent of Households by Autos Owned and Income 35 Table 4.1 Average Daily Person Trips (on Weekdays) per Household by Persons per Household and Income 38 Table 4.2 Average Daily Person Trips (on Weekends) per Household by Persons per Household and Income 39 Table 4.3 Average Daily Person Trips (on Weekdays) per Household by Persons per Household and Auto Ownership 40 Table 4.4 Average Daily Person Trips (on Weekends) per Household by Persons per Household and Auto Ownership 41 Table 4.5 Average Daily Person Trips (on Weekdays) per Household by Income and Auto Ownership 42 Table 4.6 Average Daily Person Trips (on Weekends) per Household by Income and Auto Ownership 43 Table 4.7 Average Daily Vehicle Trips (on Weekdays) per Household by Persons per Household and Income 44 Table 4.8 Average Daily Vehicle Trips (on Weekends) per Household by Persons per Household and Income 45 Table 4.9 Average Daily Vehicle Trips (on Weekdays) per Household by Persons per Household and Auto Ownership 46 Table 4.10 Average Daily Vehicle Trips (on Weekends) per Household by Persons per Household and Auto Ownership 47

PAGE 7

iv Table 4.11 Average Daily Vehicle Trips (on Weekdays) per Household by Income and Auto Ownership 48 Table 4.12 Average Daily Vehicle Trips (on Weekends) per Household by Income and Auto Ownership 49 Table 4.13 Average Daily Person and Vehicle Trips (on Weekdays) by Gender and Age 56 Table 4.14 Average Daily Person and Vehicle Trips (on Weekends) by Gender and Age 57 Table 4.15 Trip Estimation Variables by Urban Size 62 Table 4.16 Distribution of Person Tr ips by Purpose, Size and Income 65 Table 5.1 Person Trip Length Dist ribution by Urban Size and Purpose on Weekdays 68 Table 5.2 Person Trip Length Dist ribution by Urban Size and Purpose on Weekends 70 Table 5.3 Vehicle Trip Length Di stribution by Urban Size and Purpose on Weekdays 72 Table 5.4 Vehicle Trip Length Di stribution by Urban Size and Purpose on Weekends 74 Table 5.5 Average Daily VMT pe r Household by Urban Size and Purpose 78 Table 5.6 Average Daily PMT per Person by Urban Size and Purpose 79 Table 5.7 Average Daily PTT per Person by Urban Size and Purpose 80 Table 5.8 Average Daily PMT pe r Person by Urban Size and Gender 81 Table 5.9 Average Daily VMT pe r Person by Urban Size and Gender 81 Table 5.10 Average Trip Length by Purpose, Mode and Urban Size on Weekdays 82 Table 5.11 Average Trip Length by Purpose, Mode and Urban Size on Weekends 83

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v Table 5.12 Average Trip Duration by Purpose, Mode and Urban Size on Weekdays 84 Table 5.13 Average Trip Duration by Purpose, Mode and Urban Size on Weekends 85 Table 5.14 Average Travel Duration by Household Income, Urban Size and Trip Purpose on Weekdays 87 Table 5.15 Average Travel Duration by Household Income, Urban Size and Trip Purpose on Weekends 88 Table 6.1 Percent Person Trips by Mode and Urban Size and Purpose on Weekdays 91 Table 6.2 Percent Person trips by M ode and Urban Size and Purpose on Weekends 94 Table 6.3 Trips by Mode, Urban Size and Length on Weekdays 98 Table 6.4 Trips by Mode, Urban Size and Length on Weekends 99 Table 6.5 Percent Person Trips by Mode, Urban Size and Gender of the Trip-maker 101 Table 7.1 Average Daily Auto-Occupancy Rates by Urbanized Area Population and Purpose for Weekdays 104 Table 7.2 Average Daily Auto-Occupancy Rates by Urbanized Area Population and Purpose for Weekends 104 Table 7.3 Average Daily Auto-Occupancy Rates by Income Category and Purpose for Weekdays 105 Table 7.4 Average Daily Auto-Occupancy Rates by Income Category and Purpose for Weekends 105 Table 7.5 Average Occupancy Rates by Trip Length and Trip Purpose 106 Table 7.6 Average Occupancy Rates by Trip Length and Gender of the Driver 107 Table 7.7 Average Occupancy by Tr ip Length, Urban Size and Gender of the Driver 107

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vi Table 8.1 Percent Person Trips by Mode, Time of Day and Urban Size on Weekdays 110 Table 8.2 Percent Person Trips by Mode, Time of Day and Urban Size on Weekends 116 Table 8.3 Percent of Vehicle Trip s by Trip Purpose in an Urban MSA Size Less Than 250,000 127 Table 8.4 Percent of Vehicle Trip s by Trip Purpose in an Urban MSA Size of 250,000 499,999 130 Table 8.5 Percent of Vehicle Trip s by Trip Purpose in an Urban MSA Size of 500,000 999,999 133 Table 8.6 Percent of Vehicle Trip s by Trip Purpose in an Urban MSA Size of 1,000,000 2,999,999 136 Table 8.7 Percent of Vehicle Trip s by Trip Purpose in an Urban MSA Size of 3 Million or More 139 Table 8.8 Percent of Vehicle Trips by Trip Purpose in an Urban Area but Not in an MSA 142 Table 8.9 Percent of Person Trips by Gender and Start Time 145 Table 8.10 Average Occupancy Rate by Time of Day and Purpose 154 Table 9.1 Activity Categorization 160 Table 9.2 Characteristics of Pe rsons Aged 16 Years and Above in Urban Areas 161 Table 9.3 Effect of Socio-Demogr aphics on Activity and Travel Time on Weekdays 166 Table 9.4 Effect of Activity Partic ipation on Travel Time on Weekdays 168 Table 9.5 Effect of Socio-Demogr aphics on Activity and Travel Time on Weekends 170 Table 9.6 Effect of Activity Partic ipation on Travel Time on Weekends 171

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vii LIST OF FIGURES Figure 2.1 Hypothetical Household Non-Work Travel Patterns 18 Figure 2.2 Comparison of Distribution of Trips on Weekdays and Weekends in New Zealand and Great Britain with Time of Day 21 Figure 2.3 Emissions from Area-Based Sources Showing Seasonal Variations in Summer and Winter Emissions, in Tonnes per Day 24 Figure 4.1 Trip Rates per Household on Weekdays and Weekends by Household Size 50 Figure 4.2 Trip Rates per Household on Weekdays and Weekends by Income 51 Figure 4.3 Trip Rates per Household on Weekdays and Weekends by Autos Owned 53 Figure 4.4 Person Trip Rates per H ousehold on Weekdays and Weekends by Income and Household Size 54 Figure 4.5 Person Trip Rates per H ousehold on Weekdays and Weekends by Number of Vehicles Own ed and Household Size 55 Figure 4.6 Trip Rates per Person on Weekdays and Weekends by Age of the Person 58 Figure 4.7 Trip Rates per Person on Weekdays by Age and Gender 60 Figure 4.8 Trip Rates per Person on Weekends by Age and Gender 60 Figure 5.1 Trip Length Di stribution for Home Based Work (HBW) Trips 76 Figure 5.2 Trip Length Di stribution for Home Based Shop (HBShop) Trips 77 Figure 8.1 Distribution of Auto Pe rson Trips by Trip Start Times 123 Figure 8.2 Distribution of Non-Motorized Person Trips by Trip Start Times 123

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viii Figure 8.3 Distribution of Transit Person Trips by Trip Start Times 125 Figure 8.4 Percent of Weekday Vehicl e Trips by Hour by Trip Purpose in an Urban MSA Size Less Than 250,000 128 Figure 8.5 Percent of Weekend Vehicl e Trips by Hour by Trip Purpose in an Urban MSA Size Less Than 250,000 129 Figure 8.6 Percent of Weekday Vehicl e Trips by Hour by Trip Purpose in an Urban MSA Size of 250,000 499,999 131 Figure 8.7 Percent of Weekend Vehicl e Trips by Hour by Trip Purpose in an Urban MSA Size of 250,000 499,999 132 Figure 8.8 Percent of Weekday Vehicl e Trips by Hour by Trip Purpose in an Urban MSA Size of 500,000 999,999 134 Figure 8.9 Percent of Weekend Vehicl e Trips by Hour by Trip Purpose in an Urban MSA Size of 500,000 999,999 135 Figure 8.10 Percent of Weekday Vehicl e Trips by Hour by Trip Purpose in an Urban MSA Size of 1,000,000 2,999,999 137 Figure 8.11 Percent of Weekend Vehicl e Trips by Hour by Trip Purpose in an Urban MSA Size of 1,000,000 2,999,999 138 Figure 8.12 Percent of Weekday Vehicl e Trips by Hour by Trip Purpose in an Urban MSA Size of 3 Million or More 140 Figure 8.13 Percent of Weekend Vehicl e Trips by Hour by Trip Purpose in an Urban MSA Size of 3 Million or More 141 Figure 8.14 Percent of Weekday Vehicl e Trips by Hour by Trip Purpose in an Urban Area but Not in an MSA 143 Figure 8.15 Percent of Weekend Vehicl e Trips by Hour by Trip Purpose in an Urban Area but Not in an MSA 144 Figure 8.16 Distribution of Person Trip s by Gender and Trip Start Time on Weekdays 152 Figure 8.17 Distribution of Person Trip s by Gender and Trip Start Time on Weekends 152 Figure 8.18 Change in Occupancies by Tr ip Purpose and Trip Start Time 156

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ix Figure 9.1 Activities Participation Model 158 Figure 9.2 Illustration of Direct Indirect and Total Effects 165

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x A COMPARISON OF WEEK END AND WEEKDAY TRAVEL BEHAVIOR CHARACTERISTICS IN URBAN AREAS Ashish Agarwal ABSTRACT Travel demand analysis has traditiona lly focused on exploring and modeling travel behavior on weekdays. This emphasis on weekday travel behavior analysis was largely motivated by the presence of well-define d peak periods, primarily associated with the journey to and from work. Most travel demand models are based on weekday travel characteristics and purport to estimate tr affic volumes for daily or peak weekday conditions. Much of the planning and policy maki ng that occurs in transportation arena in response to weekday travel behavior and forecasts. More recently, there had been a growing interest in exploring, understanding, and quantifying weekend travel characteristics. The ability to do this has been limited due to the non-availability of trav el survey data that includes weekend trip information. Most travel surveys collect inform ation about weekday travel behavior and ignore weekend days. However, the 2001 National Household Travel Survey includes a substantial sample that provided detailed trip information for weekend days and therefore this dataset offers a key opportunity to explore in-d epth weekend travel characteristics.

PAGE 14

xi Weekend travel behavior is expected to be substantially different from the weekday travel behavior for difference in se veral spatial and tempor al constraints. The difference in constraints can also lead to a change in trip chaining patterns on weekdays and weekends. Differences in constraint s coupled with socio-economic changes characterized by greater disposable inco me, time-constrained lives, and greater discretionary activity opportunities point towa rds the growing role that weekend travel behavior is going to play in tran sportation planning and policy-making. This thesis provides a comprehensive anal ysis of weekend travel behavior using the 2001 NHTS. Differences and similarities between weekday and weekend travel behavior are identified and pr esented for different urban areas sizes varying according to Metropolitan Statistical Area (MSA) size. Models of weekend and weekday travel behavior are developed to cap ture the structural relations hip of socio-demographics, activity durations, and travel duration are de veloped using structural equations modeling approaches to better understand the relationshi ps among these aspects of travel behavior on weekdays and weekends. This report is supposed to act as an updated data guide to the National Cooperative Highway Research Pr ograms (NCHRP) Repor t 365 titled Travel Estimation Techniques for Urban Planning aims at studying the changes in behavioral characteristics between two categories of th e day of week a weekday and a weekend based on personal, household and trip characteristics.

PAGE 15

1 CHAPTER 1 INTRODUCTION 1.1 Background Urban travel is accompanied with many problems, out of which two commonly encountered ones consist of congestion and air quality degradation. Both these are attributed to various reasons such as increase in travel times, vehicle miles traveled, and other household and personal structure changes. Most of these have been researched in the past for normal working days, Monday to Friday, because of being more peaked during certain hours of the day than any ot her time on any other day. However, due to lack of research attention and lack of sufficien t data in planning agencies to calibrate the models, weekend travel has not been studied well until now although the need to link the weekend travel demand has been necessitated from time to time for satisfactory highway design. This report which acts as an updated data guide to the National Cooperative Highway Research Programs (NCHRP ) Report 365 titled Travel Estimation Techniques for Urban Planning aims at studying the changes in behavioral characteristics between two categories of th e day of week a weekday and a weekend based on personal, household and trip characteristics.

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2 Individuals engage in one or the othe r activity for different purposes. For different physiological or biological needs, he or she travels from one place to another thereby making a trip to satisfy his need. Th is is commonly referred to as a derived demand nature of travel. Any sort of traveling is affected by the va rious constraints that happen to exist by default without the wish es of the person. While most of these constraints, that might occur at the individual level or his/her family level, exist due to change in demographic and socio-economic characteristics, some of them may even relate to temporal or spatia l ones. With recent social cha nges like increased work time flexibility, 24 hour shopping on Internet and at stores, activity beha vior across the seven days of the week has become more complex to study. Although an in-depth study of such a behavior with all the in-home and out-home activities recorded by the individual over a considerable time span is recommended but many a times that is not feasible leaving us with solutions to make the best use of time a nd effort to capture such a behavior as much close as possible. The activities in which a pe rson engages has normally been classified into three types: Subsistence, Maintenance and Discre tionary (or leisure). Out of these three activities, subsistence activity that refers to work or work related purpose is essential to serve towards the financial requirements for fulfilling the other two activities. A kind of analysis commonly studied as the time-use analysis where time is allocated between different activities looks at how this time is allocated by an individual for different activities over a week or a month or any othe r level. Collecting such an intra-personal travel data for the whole nation, i.e. getting an understandin g of the same persons travel

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3 for more than one day, has money, time and better reporting limitations that makes it altogether infeasible. Rather one way to captu re the travel by an individual is to do so on one particular day, generally done in United States through a National Household Travel Survey (NHTS) conducted every five years wi th the travel behavior pattern of an individual on a single day interpreted to be in optimal behavioral equilibrium. This survey captures the travel behavi or of an individual so that policies could be formulated towards providing means for a better and co mfortable living. The da taset obtained from this survey serves sufficient to carry an an alysis for comparing day of week analysis which too has been done in the past. But lik e Sullivan (1963) who used the Pittsburg Area Transportation Studys 1958 home interview survey most of them have either discussed the variations of pe rsonal travel behavior on weekda ys or has failed to address the issue on a national level with only exception being Hu (1996) in which comparison was made by the day of week. Other studies that have looked upon the day of week variation in travel behavior in the past have found significant differen ces. Like Parsons Brinckerhoff Quade and Douglas (PBQD) Inc. (2000) which compared and contrasted weekend and weekday travel, Rutherford et al. (1997) found significan t differences between weekdays, Sundays and Saturdays. Schlich (2001) used multiday data from Mobidrive and found that there is a lot of variation that occurs on weekends as compared to weekdays because of smaller number of individual obliga tions on weekends. The behavior on a weekend day was found more variable if it was c onsidered with more of trip-b ased context as compared to the time budget based context. Elaborating on how problematic had the weekend traffic

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4 congestion become for the local government po licy makers and planners in most of the urban areas in New Zealand, OFallon & Su llivan (2003) compared the weekday and weekend travel behavior using the 1997/ 98 New Zealand Household Travel Survey (NZTS). However, it must be noted that their weekend definition included the time from 4 am on Saturday to 4 am on Monday. Using a weekly time-use data diary survey conducted in 1985 in the Netherlands with 2964 respondents of 18 years and above, Yamamoto et al. (1999) found that workers daily act ivity patterns varied significantly between working and non-working days although patterns were correlated. Yai et al. (1995) explored the data from a nationwid e recreation travel survey conducted by Ministry of Construction in Japan in 1992 to investigate the in creasing congestion on weekends and indicated that the weekend re creational traffic can be as high as the weekday commuting traffic. Zhou & Golledge (2000) too found considerable differences between weekdays and weekends. Sunday was described as the most depressed travel activity intensity day as compared to the Satu rday which was considered to be the day on which activities for relaxing or clean up i.e. finishing of something that hasnt been done over the week. Even on weekdays, noon, ear ly afternoon or evening time slot in which eat-out, shopping, social or recreational ac tivities were supposedly carried, was found to be the reason behind the variations in the supposedly routinized (because of work and study) activity behavior on weekdays. In this report, a br oad categorization of weekday versus weekend is presented to assist decision and policy makers.

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5 1.2 Weekdays and Weekends A weekday refers to any day of the week from Monday to Friday in which students make a trip to school, or a work er commutes to his or her job bound by the requirements such as reaching earlier by some time. On the other hand, weekend is considered full of sportive action or more in -home maintenance activities where most of the persons would rather not depart too early and thus causing a shift in the peak period of travel. Different worker explores weeke nds in different ways. For example, some persons prefer to go to gym engaging in in tense exercise on weekend neglecting advices from professional doctors like Moran and V ogin (2001) of exercising moderately but regular exercise while others prefer going to bars to consume alcohol on weekends that too is associated with health and safety ri sks. Weekends can be days involving social trips such as going to churches to worship and/or for weddings so as to make it possible for as many persons as possible to attend while for some others like photographers, florists, musicians and caterers the same trip may be classified as a work or work related one. With different activities that can be made possible and with more members, having free time to engage in them, altogether a diffe rent travel pattern can be hypothesized on weekends as compared to weekdays. Such changes in travel characteristics are explored in this report using various attributes at person, househol d, vehicle and even the trip itself.

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6 1.3 Objectives and Scope of this Study The specific objectives of this report are: To study the effect of socio-dem ographics on weekday and weekend travel behavior To study and compare travel behavior on weekdays and weekends at the household and personal level To develop an updated data guide so as to provide estimates helpful in urban planning To study tradeoffs between activities and travel behavior on weekdays and weekends The study is limited to urbanized metropolitan areas with a trip made by the person of length no more than 75 miles to compare with other regional househ old travel surveys. 1.4 Organization The remaining part of the report has been organized as follows. Chapter 2 starts with a literature review summarizing th e trends and issues th at has been discussed with respect to the study of da y of the week dimension to the travel patterns. Before getting into the results of the analysis, a whole chapter 3 has been devoted at the description of the data that ha s been used in this study. Rest of the chapters is arranged broadly into travel characteristics. Chapter 4 gives an overview of effect of the household and personal attributes on the trip rates of th e individual. Another trip characteristic is the trip length that has been reporte d in miles as well as in minut es and has been discussed in Chapter 5. Distribution with respect to mode and with respect to numbers of persons on

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7 the trip is discussed in Chapters 6 and 7 respectively. Chapter 8 explores the temporal variations in the trips. Chapter 9 expl ains the methodology for modeling activity and travel behavior. Finally, conc lusion and the scope for furthe r research is summarized in Chapter 10.

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8 CHAPTER 2 LITERATURE REVIEW 2.1 Introduction Most of the past travel behavior research and m odeling has dealt mostly on weekdays due to lack of sufficient data on weekends. However, there had been considerable research that have dealt with some of the asp ects on travel behavior and air quality issues on weekends with some of th em making a direct co mparison with those on weekdays. The research has not been limited to difference to only two categories but has been extended to day of week and even the season of the year summer and winter and holidays too. While some of them have us ed a multi-day data to expand their horizon from inter-person travel (the travel day charac teristics comparison of different persons) to the intra-personal travel (the travel char acteristics comparisons of same person on different days of the week), they had limitations of being limited to a small city sample of households or lack of travel behavior on weekends. Failure to address these issues on a national level and for future monitoring of travel patterns has motivated this research. This chapter starts with the emphasis on the need for a multi-day travel data followed by a brief overview of the studies done on different aspects of travel behavior that led to their difference by day of week or cat egorized as weekdays and weekends.

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9 2.2 Multi-Day Versus One-Day Travel Survey Diaries Travel behavior has reached to an extent that consideration has started been given to the intra-personal travel or the travel behavior of the same person among different days. This has been made possible by the use of multi-day travel survey diaries. According to Kitamura (1988), a day which can be considered as a convenient time unit because many of the activities from sleepi ng to commuting recur after every one day cycle for psychological and in stitutional reasons can many a times not be sufficient to study the complex behaviors. For example, to analyze the shopping behavior in a region where store is open until 6 p.m. on weekda ys and closed on Sundays, Kitamura (1988) used a multi-day data (the Dutch National Mobility Panel data) that consisted of travel diaries kept over one-week periods. The st udy was limited to household members of 12 years and above of age to capture the shoppi ng behavior explicitly on Saturdays. Hanson and Huff (1988) suggested travel-behavior groups defined based on one-day diaries are likely to be unstable with the chance of misclassifying the person being high. Due to differences in activities patterns pursued during that day, daily travel (or the representative) patterns of an individual have been found to vary from day to day according to a stochastic recurrence structure. By specifying the average time intervals, possibility of identifying more than one typical travel pa tterns exhibited by the individual or any population subgroup was suggested. Most of these multi-day travel survey diaries have been restricted to a small sample of households due to under-reporting an d financial constraints. However, their

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10 need for various issues has been felt by vari ous researchers specially to study the travel behavior on weekends. For example, Pisarski (1997) necessitated need for the exploration of journey on weekends. Pudget Regional Council (2001) made the requirement of a data of about 2000 to 3000 households reinforced with data on modal (highways and transit) volume on weekends for an expansion from a normal weekday model to a separate weekdays and week ends model to analyze the effect of environmental factors, traffic operations and multi-modal cost benefit analysis for an long-term implementation of the integrated land use and travel models. Simma (2003) who reported a change in the survey me thodology from 1974 to 1979 in Switzerland where the later had the description of each pe rsons one weekday and one weekend travel to capture the growing importance of leisure travel. 2.3 Effect of Socio-Demographics Various studies have shown how change in socio-demographics at both the household and the individual level leads to the change in behavior on different days of week. For example, households with highe r vehicle ownership tend to make more recreational trips on weekends. This section gi ves a short description of all such studies. van der Hoorn (1979) examined the effect of various factors on travel time expenditures from a study conducted in Nether lands through a survey administered in October 1975 with 1100 respondents. It was found that car ownership, density of the area in which household is located, worker stat us and students status make the difference between the travel time expenditure to ex ist between a weekday and a weekend. Using

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11 the Belgium National Travel Survey, MOBEL and the travel diary survey conducted in two cities of Germany: Ha lle/Saale and Karlsruhe, Mobidrive Cirillo and Axhausen (2002) found homogeneity in workers behavi or among weekdays as compared to the non-workers who showed a significant variat ion across different days of the week. Even in New Zealand, as reported by OFallon and Sullivan (2003), although the number of trips by drivers was constant but men drivers made more trips on weekends and even lengthier trips on weekends. Using the data from the May 1991 Current Population Survey (CPS) Supplement for U.S. and 1990 wave of the German Socioeconomic Panel (GEOSP), Hamermesh (1995) found that out of all male workers, 20% work on Saturdays, 8% on Sundays as co mpared to the female workers where the percentages were roughly 14% and 7% respectively. Yun and OKelley (1997) used two week travel multi-day data from Hamilton, Ontario, Canada in 1978 with a sample of 704 households. With the assumption that the shopping choice behavior is st ochastically independent on every day, they found that households owning auto are more likely to make more shopping stops than non-auto owning households on Saturdays but no significa nt effect is observed on weekdays and Sundays. The employment status of the female head was found to have a significant and positive effect only on the wee kday participation decision. Smith-Berndtsson and strm (2001) us ed survey data from parents to investigate the behavior and mobility of th e entire family. On a particular weekday,

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12 parents were observed to spend their time with children in car traveling short distances. If the parents were at home, they were found not to have time even for themselves. Family weekdays were found to be normally pla nned except on Mondays where something unpredictable was observed to happen. Week end on the other hand was the time when families tend to socialize with each other and friends, traveling longer distances and children taking part in athletic games. Pla nning was found not to be done before in the sense that the destinations are decided duri ng the trip. Thus, the ove rall usage of the car was found to be normally planned. They conclu ded that the family role comprising of children, working and the private role overrid es the mobility defining the travel need. Based on observations from 153 families, Manke et al. (1994) found that depending on the familial earner status, the participation of mothers and husbands vary on weekdays and weekends but it is the mothers who have been found to have a drastic change in their share of time spent on hous ehold tasks. In a single earner household, mothers spent about 160 minutes on housework on weekdays as compared to 110 minutes on weekends. In full-time dual earner families, on weekends mothers were found to spend almost twice the amount of time spent on housework activit ies on weekdays (70 minutes) whereas in a part-time dual earner family, mothers ere found to spend only 30 minutes in excess on weekends. On the contrary, men were not found to show drastic differences but only a mere 5-15 minutes incr ease in time spent on household activities on weekends. A better understand ing of the in-home activities combined with the out of home activities can lead us to better representation of out-of-home travel behaviour.

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13 Bhat and Misra (1999) used the 1985 tim e-use survey of Netherlands which captured one week travel of an individual. A model was proposed to allocate the total discretionary travel of a person into the in-home and out-home activities and between weekday and weekend. Individuals were f ound to spend more time on discretionary activities, particularly the out-home ones, pe r day over the weekend as compared to that on a weekday. Income was not found to play any role in the allocation of time used in discretionary activities. Older people were found to be spending most of their time for inhome discretiona ry activities. Yamamoto et al. (1999) found that younger individua ls are oriented towards out of home activity engagement on both working and non-working days. Worker head of the household was found to be engaged in more in-home discretionary activities. Females were found to make more in -home activities on non-working days than males. Workers from larger households appear to make most part of their in-home discreti onary activities on working days but the household size was not found to be associated with any split on non-working days. Household with larger num ber of vehicles were found to make more out of home discretionary activities on non working days. Income was not found to be making a split as discretionary in-home and out-home activities with working and nonworking days. They agreed to the fact as Pas and Koppelman (1985) that intrapersonal variations are larger in individuals belonging to larger household size or having higher car availability.

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14 Bhat and Srinivasan (2004) used the 2000 San Francisco Bay Area Travel Survey (BATS) to examine the frequency participati on of individuals in the out-home episodes over the weekend and found that children tend to participate more in active recreational activities than any other i ndividuals, although they showed lower participation in maintenance shopping activities. Adults empl oyed full-time had a higher propensity to participate in non-maintenance shopping and pe rsonal business activitie s and least likely in community activities over the weekend. T hose with a valid driver license were found to travel more out of home as compared to the lower levels by the physically disabled. Households residing in Centra l Business District (CBD) a nd urban areas have a higher propensity of making physical and non-physic al recreation and lower propensity in pickup and drop-up as compared to the suburban or rural areas. Bhat and Lockwood too used the same 2000 BATS data. Their focus was on disaggregating the recreational episode on week end that constituted of about 41% of the out-home activities into two categories the ac tive and the passive along with the mode that was used i.e. walking, bicycling, and j oyride in car or other. Individuals employed full-time were found to have a higher prope nsity to participate in physically active pursuits at an out-of-home location and a lo wer propensity to participate in physically active travel-related recrea tional episodes. Both young adults (16-17 years) and individuals belonging to househol ds with higher vehicle owners hip were less inclined to participate in physically active recreation. On the other hand, i ndividuals with bicycles in their households had a high propensity to pa rticipate in physically active pursuits.

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15 Location effects (density of de velopment, land-use mix, area type, etc.) did not appear to affect the recreational activity type participation directly. 2.4 Changes in Travel Behavior 2.4.1 Trip Rates Charlton and Baas (2002) studied the travel behavior in New Zealand and found that New Zealand drivers made on an averag e 4.38 daily trips out of which 4.63 trips per day was on weekdays as compared to a lo wer value of 3.76 trips on weekend in 1998. Kumar and Levinson (1995) used the 1990 Nationwide Personal Transportation Survey (NPTS) with 21,817 households a nd 47,499 persons making almost 150,000 trips and found that non-work trips dominates all the trips made on the day. Workers were found to make more shopping and non-work tr ips on weekends as compared to the nonworkers who can make those on weekdays during relatively uncongested mid-day period. Lockwood et al. (2003) using 2000 BATS indicat ed although the number of person trips per person is lower (3.01) on w eekend days compared to 3.40 on weekdays, the average trip distances were larger on weekends relative to weekdays, 8.57 miles per weekday trip compared to 8.70 miles per weekend day trip. Parsons Brinckerhoff Quade and Douglas (PBQD) (2000) too found person trip rates during the weekend day to be only marg inally lower than t hose during the weekday did. For example in a study using data from the New York metropolitan area, the number

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16 of person trips per household was found to be 8.02 on weekend days as compared to 8.87 on weekdays. Using the 1995 NPTS, Pozsgay and Bhat (2001) found the recr eational trips in urban areas to be about 12 percent on weekdays as compared to 23 percent of weekends. 2.4.2 Activities/Trip Purposes Bhat and Srinivasan (2004) modeled the fr equency participation of individuals in the out-of-home episode over the weekend and found unobserved dependencies between the propensities to participat e in different activity purposes These were attributed to substitution or complimentary in partic ipation between diffe rent activities. In Los Angeles area, Coe et al. (2002) found that the residential or in-home activities, like barbeque, lawn/garden equipm ent, increased from weekday to weekend from 40% to 140%. On weekdays, Barbeque occurred more in evenings as compared to the weekends where it occurred mostly in afte rnoon. These residentia l in home activities were suggested to be social ac tivities that might lead to th e travel for social purposes. Sugie et al. (2003) studied the interdependency between the weekday and weekend shopping behavior at th e individual level using one week activity survey data from Utsonomiya, Japan. On weekends, as ma ny as thrice the persons went for shopping as compared to those on weekdays. While most of the persons that did shopping consisted of females, males shoppers s howed a remarkable increase on weekends.

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17 According to the authors, shopping trip frequency for a person on weekdays depends greatly on the whether the person doe s shopping on weekends or not. Used the revealed preference (RP) method with weekend time allocation data and stated preference (SP) technique with indivi dual activity extension choice data, a study was done by Prasetyo et al. (2002) in Japan. People were confirmed to use most of the time in recreational activities with family on weekends as compared to that in weekdays thus making the value of travel time savings on weekends to be higher. Zhou and Golledge (2000) used a one-week survey data from 100 households in Lexington, Kentucky, which used Global Posi tioning System (GPS) and computer equipped cars. Multivariate Analysis of Variance (MONOVA) analysis was used to measure how the activity varied by day of w eek and time series analysis was used to reveal the temporal characteris tics of the trip series. They found that difference of travel time between different days of the week was at tributed to four types of activities going to workplace, shopping, social recreational or return home and this was not found to be even across the sample week. Trip frequencie s differed during different days of the week because of three activities going to wor kplace, work related business or religious activities. A remark was made that the time spent on any day on shopping and social recreational activities depends on the day of the week th e specific activity was performed. The decrease in eating trips on weekends was at tributed to peoples desire to spend their weekend with their family and enjoy homema de food than going out for the meals. The

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only difference between weekends from weekdays found was the reduced eat out trip frequency but a longer trip time. Nelson et al. (2001) described the importance of non-work travel activities even in weekday peak periods, both am and pm. Non-work trips linked to work trips were supposed to be indirectly responsible for increasing the vehicle trips. The analysis of non-work travel was considered difficult because of its association with broad variety of purposes, destinations, and changing starting times from day-to-day (see Figure 2.1). Figure 2.1 Hypothetical Household Non-Work Travel Patterns (Nelson et al. (2001)) More than 80 percent of the trips that start from 4-7 pm peak period were non-work related. Shopping trips were found to have a higher frequency on weekdays (77 percent) than weekends. 18

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19 2.4.3 Travel Time Length or Duration Kumar and Levinson (1995) showed that da ily travel time did not changed with the day of the week but was found to in crease over the weekend amounting to 68 minutes. The reason for shorter weekend trip s as compared to those on weekdays was attributed to the difference in type of job (weekend employment being mostly part-time). Saturdays, Sundays and weekdays were all found to differ from each other significantly with Sunday being considered as a rest day so as to fulfill the need for early rise to work on Monday. Moreover, early closing of shops on Sunday was another reason cited for such a difference in behavior from Saturdays. Parsons Brinckerhoff Quade and Douglas (PBQD) (2000) indicated that, the average trip distances were larger on weekends relative to weekdays, 7.8 miles per weekend trip compared to 7.1 miles per wee kday trip in the New York metropolitan area and 63.2 person miles per household on weekend as compared to 58.9 63.2 personmiles per household on weekdays. On weekends, Bhat and Lockwood found that physically active episodes averaged at a travel time of 21 minutes were pursued later in the morning as compared to the physically passive episodes that are were found to be participated latter in the evening with mean travel time being 28 minutes.

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20 2.4.4 Vehicle Occupancy OFallon and Sullivan (2003) observed higher vehicle occupancy and more of social/recreational and shopping trips on weekends as compared to weekdays. Further higher proportion of vehicle trips were found to be made as the number of vehicle available to household increased. Sullivan and OFallon (2003) found the ve hicle occupancy to remain almost constant from Monday to Friday but then showed a gradual increase from Friday onwards. On weekdays, occupancies of fema le drivers on weekdays was found to be more than their male counterpart as compared to the weekends where the female driver occupancies was less than their male counter part on Sundays and equal on Saturdays. One interesting observation made was that women drivers have household children as occupants more often as compared to the men drivers whose trips consist mostly of more than one adult. Vehicle occupancies differed wi th respect to ethnicity of drivers, number of children in household and household type but no differences was revealed with driver age. Changes in transport infrastructure or travel demand management policies were suggested to have different effects on weekend occupancy than weekday occupancy. 2.4.5 Time of Day Cervero et al. (2002) studied the introduction of car sharing in the city of San Francisco. Weekday car-share trips were f ound to be more concentrated in afternoon whereas weekend trips were generally more evenly distributed throughout the day.

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Charlton and Baas (2002) compared a cross-country comparison on travel behavior between New Zealand and Great Britain in 1997/1999. They found similar behavior of weekend and weekday trips between the two countries (Figure 2.2). Figure 2.2 Comparison of Distribution of Trips on Weekdays and Weekends in New Zealand and Great Britain with Time of Day (Charlton & Baas (2002)) Particularly in New Zealand, weekend travel peaked at 9:00 to 13:00 as compared to weekday travel between 7:00 to 8:00 and 15:00 to 18:00 but to a much lesser extent between 10:00 to 12:00. Differences with gender and age group with time of the day were also found. Women peak times occurred later in morning and earlier in the afternoon as compared to that of the mens. Weekend trips for both men and women were similar with men reporting more number of trips in morning. Although the men reported to drive twice as far as women but the number of trips made did not differ significantly. Older drivers begin trip earlier and later than the peak times of other drivers. The deviation on weekends from weekdays was that the former began their trips earlier than the later ones did. They made most of the trips as shopping trips and almost insignificant work trips with more of those shopping ones on weekdays. Younger drivers on the other hand were 21

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22 found to make more educational trips on weekdays than the shopping ones. Young women drivers made more trips than th eir corresponding male counterpart did. Even the recent study by OFallon and Sullivan (2003) found that more than 50% of trips occurring on weekends between 9:00 to 15:00 as compared to early morning (till 9:00) and late afternoon (15:00 to 18:00) of weekdays. Hamermesh (1995) found that people do work in evening and even late at night in both the countries United States (U.S.) and Germany. These surmounted to some 7% of the workers on the job even after 3 am with mo st of them including those with very little human capital. In U.S., these constituted mos tly the minority workers but the evening and late night work was least likely in metropolit an areas. Working mothers were found to be burdened with evening and night work more because of young children. Self employed workers who have freedom to choose the ti ming of their work were found to exhibit strikingly different patterns of unusual work times from employees working about two to five times on weekends. It was believed that because American workers obtained additional earnings to purchase more attractive work times and working at night was not given any priority by the workers. Zhou and Golledge (2000) too found the peopl es go work behavior to vary with days of the week. They found that the daily peak trip counts dr opped from Monday to Wednesday but bumped on Thursday and Frid ays, the reason being attributed to psychological factors. Eat out trips were found to occur dur ing early afternoon or during

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23 lunch hours on weekdays with peak on Wednesd ay occurring at early evening indicated as short family reunion or meeting with frie nds termed as short break of a busy life. Social recreational trips were found to occu r mostly at 5o clock on Friday followed by noon of Saturdays and Sundays. Their distribution was skewed on weekdays but an Ftype distribution on weekends showed relaxed time schedule. 2.5 Seasonal/Monthly Variation Only few reports deal with the seasonal variation of travel especially when it comes down to a day of week kind of analysis. A Photochemical smog study (1996) inspired by pollution concerns at Perth, Aust ralia led to a report on how the weekdays and weekends of a season may have an effect in a change in emissions from area-based sources. The study found that although the summer season had almost half of the emissions of those in winter season, the w eekdays and weekend patterns changed quite a lot (Figure 2.3). The particulate matter emi ssions were more than Carbon Monoxide (CO) emissions in winters as compared to summers where CO em issions were more. Although emissions in winters were almost more than the twice the magnitude of those in summers, the weekends emissions tend to dominate in both the seasons over the weekday. Bhat and Srinivasan (2004) found that i ndividuals participated in recreational and maintenance shopping in winters more than any other se ason. Adults were found to be indulged in picking up or dropping up activities in fall a nd spring as compared to the winters and summers. Kumar and Levinson (1995) found that daily travel time show slight increase in the months of May and July but re mained constant in other months.

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Figure 2.3 Emissions from Area-Based Sources Showing Seasonal Variations in Summer and Winter Emissions, in Tonnes per Day (From Perth Smog Study (1996)). 2.6 Transit Ridership Although most of the transit operations shut down on weekends as compared to weekdays because of low demand, there are few studies on how an improvement in transportation services may lead to changes in ridership. Out of improvements suggested are common ones are increase in frequency of transit or running additional service. An interim handbook by Transit Cooperative Research Program (2000) provides a detailed report on how the transportation system might affect travelers usage. For example, a service enhancement in transit in New Jersey Transit (NJT) on Saturdays and Sundays with hourly headways between 8 am to 6 pm and the commuter rail service resulted in a farebox recovery ratio of about 50%. Apart from the normal weekend services that are being tried to be improved, travelers response to special services to parks on weekends or some fixed priced weekend commuter railroad (say $5) that was adopted in Chicago in 1991 has also been studied. These policies and many other such as time specific fare, free 24

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25 transfers between bus, subway and unlimited ride passes have been found to cause an increase in ridership. 2.7 Suggestions to Policy Makers Since not many studies have been done to study the differences between weekdays and weekends travel behavior, th ere had not been much discussion on changes in policies. However, Sullivan and OFallon (2 003) pointed out that changes in transport infrastructure or travel demand manageme nt policies will have different effects on weekend occupancy than weekday occupancy. Few TDM tools that were suggested by OFallon and Sullivan (2003) for weekends wa s electronic road user charging, cordon tolls, parking mechanisms, ri deshare, high-occupancy vehi cle lanes and improved public transport services.

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26 CHAPTER 3 DATA DESCRIPTION 3.1 Introduction Travel surveys have continued to be one of the important ways of obtaining all the information that transportation planne rs and decision makers need in the new millennium. Not only are these surveys used to get the demographic, socio-economic, and trip making characteristics of the all the individuals belonging to a particular household, but they have been used to study the behavior mechanism of the individual which decides his or her decision making pro cess on choice of mode, location and time of travel. Refinements in these travel survey s such as incorporation of policy related questions, maintenance of a detailed activity diary have enhanced our model forecasting capabilities. This chapter aims presenting an overview of the sample dataset used to understand the differences and model the trav el behavior on weekdays and weekends. The chapter elaborates the information on household travel survey administered on national level in United States followed by a description of the survey along with few important variables that were used in this study. The dataset used in this report provides a unique opportunity to understand the travel behavior differe nces occurring on weekdays and weekends and model the ac tivity and travel relationships The chapter concludes with an overview of the household and person demographic characteristics of the survey samples of weekdays and weekends.

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27 3.2 National Travel Surveys National Household Travel Survey (NHTS) is a cross-sectional travel survey conducted on a nationwide basis to capture th e long distance travel and the local travel. This effort made by the Unites States Department of Transportation (USDOT) of capturing the travel behavior characteristics is sponsored by three national agencies together, the Bureau of Transportation Statistics (BTS), the Federal Highway Administration (FHWA) and Na tional Highway Traffic Safety Administration (NHTSA). This survey is intended at an update of earlier surveys, the Nationwide Personal Transportation Survey (NPTS) conducted in 1969, 1977, 1983, 1990, 1995 and the American travel survey conducted in 1979 and 1995, to capture the latest trends. Almost everybody who is involved in improving the nations transportation infrastructure, no matter whether he/she is a policy maker, a st ate DOT, Metropolitan Planning Organizations (MPOs), industry prof essionals and academic researchers, uses the data. Either of them makes use of the data to explore the complex travel patterns in context of transportation safety, traffic c ongestion, special populat ion groups, economic productivity, human and natural environmen tal impact, and others thereby providing necessary solutions. The other areas where th e data is intended to be used are in quantification of travel behavi or, analysis of changes in tr avel characteristics over time, exploration of relationship between the demographic of th e persons and their travel behavior, and their study over time too, to examine the public perceptions of transportation system.

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28 3.3 2001 National Household Travel Survey (NHTS) The dataset used in this report is obtain ed from the survey that was conducted over a period from March 19, 2001 through May 4, 2002 including all the days of the week whether it is a holiday or not. The rela ted dataset that was made available as first release in January 2003 has been used in this report. The survey included only a civilian non-institutionalized popul ation of the nation excluding t hose in motels, hotels, group quarters such as nursing homes, prisons, barra cks, convents or monasteries and any living quarters with 10 or more unrelated roommates. The persons who are temporarily staying places like dorm rooms, fraternity and sorority houses were eligible for survey only if the numbers of household members in the residenc e was less than eleve n. Thus, the survey included a college student who is visiting his home whereas it included persons who stay at home and go temporarily for business, vacation or any other purpose. Few aspects of 2001 NHTS that makes it di fferent from the earlier studies that were done in the past are summarized belo w. First is the better representation of household vehicle fleet covera ge through a reminder about reporting of vehicle types such as motorcycle, mopeds and recreational vehicles. Second is the inclusion of travel characteristics of persons less than 5 years. This restricts the comparison to earlier NPTS survey which covered all those above 5 years of age. Third is the de tailed representation of the trip purpose to understand the family and personal business trips better. Another better representation is seen by the increase in bicycle and walk trips.

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29 Overall the survey sample consiste d of 60,282 individuals in 26,038 households making about 248,517 trips with 53,138 househol d vehicles. The sampling method used was random telephone sampling. The dataset contained two weights for different households one for the useable household where person interviews were completed with atleast 50% of persons being adults and the ot her being % household where person interviews were completed with all pers ons being adults in th e household. In this report, the weight corresponding to us eable household or person is used. This report focuses only on the households in urban areas that traveled on weekday, any day of week from Monday to Friday, and weekend, Saturday and Sunday. Such households sample was about 19,788 (appro x. 85 million in population) with 45, 179 persons (about 217 million in population) having 37,936 vehicles (approx. 152 million across the nation). These urban areas have been divided into six categories according to metropolitan statistical area (MSA). The general concept of such a Micropolitan or Metropolitan Statistical Area as defined by Federal Register (2000) is that an area containing a recognized populat ion nucleus and adjacent communities that have a high degree of integration with that nucleus. All such areas can contain many counties in them based on statistical m easures such as population growth, population density, commuting, employment, etc. There ha ve been several cha nges in the grouping of such areas over the seve ral years by the U.S. Office of Management and Budget (OMB). Further, this repo rt includes all trips 75 mile s or less (about 184,122 trips approximating to 315 billion trip s in population) as this is supposed to provide greater comparability to other regional household travel surveys.

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30 The income categories used in this repor t are low, medium and high. These were defined earlier in 1990 as less than $20,000, $20,000 to $39,999 and above $40,000 respectively. To preserve these categories annual households income reported in the 2001 NHTS were converted to the 1990 categorie s using the consumer price indices for all urban consumers for 1990 being 130.7 and for 2001 being 177.1 obtained from the Bureau of Labor and Statistics (2003). The revised 2001 income categories for low, medium and high became less than $25,000, between $25,000 and $54,999, and greater than $55,000 respectively. As pointed out earlier, the detailed representation of trip purpose provides user with great flexibility in grouping them fo r specific study. Two variables WHYFROM and WHYTO defined the origin and destination of the specific trip. Based on these two variables the trip purposes were classified as Home-Based Work (HBW), Home-Based Shopping (HBShop), Home-Based Social Recreational (HBSoc), Home-Based Other (HBO), Home-Based Non-Work (HBNW) a nd Non-Home Based ( NHB). Table 3.1 shows how the different trip purposes were categorized for the Home Based Trips. Table 3.2 and 3.3 gives the description of household and person characteristics of those who traveled on weekdays and weekends. 14470 households (about 60,584,152 in population) in urban areas gave their travel behavior char acteristics on weekdays as compared to the 5318 households (about 24,798,083 in population) on weekends. The distribution of households with socioeconomic characteristics that traveled on weekends was about the same as those of weekdays. About 30% of the households had their annual

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31 income below $25,000 whereas another 35% had their income above $55,000. More than 31% of the households had more than two persons as compared to about 27% having single-family status. More th an 58% of the households had two vehicles or more. About 42% of the households had a population of 3 million or more whereas 25% of the households have a population be tween 1 million and 3 million. 32917 individuals (153,871,643 in population) of those who traveled on weekdays were surveyed as compared to 12262 (63,257,134 in population) on weekends. The persons those who traveled on weekda ys had almost the same distribution on weekends. Females constituted to about 51.32% of the sample. About 42% of the persons were 40 years and above in age as compared to 23.5% in each age categories of 0-15 years and 25-39 years. About 52% of the persons were workers. About 32% of the persons aimed at bachelors level and above in education. Overall, the sample seems to be reasona ble to provide a comparison of a weekday and weekend travel behavior. Table 3.4 gi ves the distribution of households by autos owned and the household income. Where 50% of the households that had income of less than $25,000 a year had one vehicle, about 85% of the households having an income of $55,000 and above had atleast two vehicles.

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32 Table 3.1 Categorization of Home Based Trips 2001 NHTS WHYFROM/WHYTO Variable* Category Go to work (11) Return to work (12) Attend business meeting/ trip (13) Other work related (14) HBW Shopping/ errands (40) Buy goods: groceries/clothing/ hardware store (41) Buy gas (43) HBShop Social/ recreational (50) Go to gym/ exercise/ play sports (51) Go out/ hang out: entertainment/ theater/ sports event/ go to bar (54) Visit public place: histori cal site/ museum/ park/ library (55) Meals (80) Social event (81) Get/ eat meal (82) Coffee/ ice-cream/ snacks (83) HBSoc School/ religious activity (20) Go to school as student (21) Go to religious activity (22) Go to library: school related (23) OS Day care (24) Medical/ dental services (30) Buy services: video rent als/ dry cleaner/ post office/ car service/ bank (42) Rest or relaxation/ vacation (52) Visit friends/ relatives (53) Family personal busines s/ obligations (60) Use professional services: attorney/acc ountant (61) Attend funeral/ wedding (62) Use personal services: grooming/haircut/nails (63) Pet care: walk the dog/ vet visits (64) Attend meeting: PTA/ home owners association/ local government (65) Transport someone (70) Pick up someone (71) Take and wait (72) Drop someone off (73) Other reason (91) HBOther Number following the description of the variable indicates the code used in the dataset. HBOther trips include HBShop and HBSoc trips in ta bles with only three categories HBW, HBOther and NHB while HBNW trips includes HBShop, HBSoc and HBOther trips.

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33 Table 3.2 Household Characteristics of the Urban Areas from 2001 NHTS Weekday Weekend Sample Size 14,470 5,318 Population 60,584,152 24,798,083 Percent of Zero Travel Households 5.8% 8.4% Annual Income LOW (Less than $25,000) 29.05% 27.68% MEDIUM ($25,000 to $54,999) 35.48% 36.01% HIGH ($55,000 and above) 35.47% 36.31% Household Size 1 person 27.39% 26.97% 2 person 31.78% 31.23% 3 person 16.62% 15.85% 4 or more persons 24.21% 25.95% Vehicle Ownership 0 vehicle 9.22% 8.48% 1 vehicle 33.83% 33.54% 2 vehicles 37.10% 36.28% 3 or more vehicles 19.85% 21.70% Number of Drivers 0 driver 6.31% 5.62% 1 driver 33.54% 33.42% 2 drivers 47.41% 47.51% 3 or more drivers 12.74% 13.45% Household Life Cycle One adult, no children 16.18% 15.49% 2+ adults, no children 20.97% 20.28% One adult, youngest child 0-5 1.92% 1.24% 2+ adults, youngest child 0-5 14.19% 14.59% One adult, youngest child 6-15 2.90% 2.94% 2+ adults, youngest child 6-15 13.69% 13.79% One adult, youngest child 16-21 1.16% 1.12% 2+ adults, youngest child 16-21 4.33% 5.27% One adult, retired, no children 10.63% 10.96% 2+ adults, retired, no children 14.03% 14.33% Type of Housing Unit Detached single house 60.27% 60.80% Duplex 5.35% 5.63% Rowhouse or townhouse 4.43% 4.26% Apartment, condominium 26.70% 26.08% Mobile home or trailer 3.02% 2.84% Dorm room, fraternity or sorority house 0.09% 0.16% Other 0.15% 0.24% MSA size In an MSA of Less than 250,000 6.64% 6.46% In an MSA of 250,000 499,999 7.96% 8.62% In an MSA of 500,000 999,999 8.33% 8.02% In an MSA of 1,000,000 2,999,999 24.28% 23.26% In an MSA of 3 million or more 41.83% 42.15% Not in MSA 10.96% 11.50%

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34 Table 3.3 Person Characteristics of the Urban Areas from 2001 NHTS Characteristic Weekday Weekend Sample Size 32,917 12,262 Population 153,871,643 63,257,134 Age Mean (in years) 35.3 35.29 0-15 23.39% 23.83% 16-24 11.61% 12.03% 25-39 23.61% 22.28% 40-64 29.38% 29.91% 65-74 6.56% 6.62% 75-84 4.31% 4.28% 85+ 1.14% 1.06% Gender Male 48.67% 48.68% Female 51.33% 51.32% Worker 52.80% 52.30% Education level Less then high school graduate 9.67% 10.47% LOW High school graduate, include GED 27.85% 28.30% Vocational/technical training 3.36% 3.16% Some college, but no degree 18.36% 19.13% MED Associate's degree (for example, AA) 7.88% 7.00% Bachelor's degree (for example, BA, AB, BS) 19.21% 18.43% Some graduate or professional school, but no degree 2.21% 2.03% HIGH Graduate or Profesisonal School Deg (eg MA, MS, MBA, MD, DDS, PhD, EdD, JD) 11.46% 11.48%

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35 Table 3.4 Percent of Households by Autos Owned and Income Autos Owned Income 0 1 2 3+ In an urban area with MSA of less than 250,000 Low* 11.33 53.69 23.08 11.90 Medium 1.81 31.54 45.31 21.34 High 0.07 12.74 48.66 38.53 Weighted Average 5.46 34.18 38.23 22.13 In an urban area with MSA of 250,000 499,999 Low 13.44 51.86 24.77 9.93 Medium 0.96 36.55 44.68 17.81 High 0.17 13.46 46.36 40.02 Weighted Average 5.89 34.88 38.23 21.00 In an urban area with MSA of 500,000 999,999 Low 19.28 51.04 20.62 9.05 Medium 1.99 33.68 40.20 24.12 High 0.66 12.32 54.37 32.65 Weighted Average 7.92 32.83 37.81 21.44 In an urban area with MSA of 1,000,000 2,999,999 Low 19.80 50.68 22.86 6.67 Medium 1.75 40.13 40.83 17.28 High 0.63 11.30 52.32 35.75 Weighted Average 6.51 33.56 39.70 20.24 In an urban area with MSA of 3 million or more Low 31.44 45.93 15.43 7.20 Medium 7.99 42.05 36.14 13.82 High 2.25 20.88 46.65 30.21 Weighted Average 12.11 34.36 34.83 18.69 In an urban area but not in a MSA Low 17.70 49.74 22.80 9.76 Medium 1.14 25.87 42.66 30.34 High 0.32 7.44 47.18 45.05 Weighted Average 7.87 31.39 35.92 24.82 In an urban area Low 22.34 49.21 20.20 8.25 Medium 3.96 37.51 39.94 18.59 High 1.36 16.11 48.71 33.81 Weighted Average 9.01 33.74 36.87 20.39 In actual 1990 dollars: Low = Less than $20,000, Medium = $20,000 to $39,999 and High = $40,000 and above

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36 CHAPTER 4 COMPARISON OF PERSON AND VEHICLE TRIP RATES 4.1 Introduction A trip rate is defined as the number of trips made by particular person or a household in one day. A person is supposed to ma ke a trip whether he/she is a passenger or a driver on the trip. Thus, a household with more than one person can have some of the members being passengers while one of them being a driver on a particular day of the week. The term person trip rate is genera lly used to account for all the trips made by the person whether he was a passenger or a driver on that particular tr ip in one whole day. To distinguish between the driver trips, the term vehicle trip rate is used for all the trips that were made by the person as being a driver It must be noted that the person is been supposed to act as a driver of the vehicle if the vehicle is pr ivately operated one and does not belong to a public transit type. The follo wing chapter focuses on the comparison of the weekday and weekends person and vehicle trip rates for households and persons by household characteristics such as size, annual income, vehicle owners hip, urban area size and persons characteristics such as age and gender. The trip rates vary greatly with the urban size as shown in the tables attached but the discussion here ap plies generally to an overall nature of the urbani zed areas in United States.

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37 4.2 Trip Rates by Household Characteristics The household trip rates are used in the trip generation process of a normal four step urban transportation planning (UTP) pr ocess. These were calculated for mostly weekdays earlier with the vi ew that the weekend travel would be lower than that on weekdays and thus most of the policies made were supposed to apply to weekends too if they were found to be true for the weekdays. Table 4.1 through 4.6 and Table 4.7 through 4.12 give the person and vehicle trip rates respectively by househol d on weekdays and weekends. Table 4.13 and Table 4.14 give the comparison of person and vehicle trip rates per person by gender, age and urban size. All these tables include trips of 75 mile s or less made in urban areas only. As shown in Table 4.1 through 4.6, the average household in an urban area makes 9.37 person trips almost the same as those made on weeke nds (9.04) but vehicle trips was found to decrease only slightly from weekday (5.77) to weekends (4.82) by almost one trip. This reveals that peoples propens ity to make trips do not d ecrease on a non-working day or weekends but they keep on making trips, however further analysis is necessary to find the driving force for engaging them into traveling. As shown in Table 4.1 and 4.2, the increase in number of persons in the household or the household size leads to more number of trips being made by the household possibly because every person has his or her own demand for the travel.

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38 Table 4.1 Average Daily Person Trips (on Weekdays) Per Household by Persons Per Household and Income Persons per Household Income 1 2 3 4 5+ Weighted Average In an urban area with MSA of less than 250,000 Low 4.23 8.34 11.41 20.16 15.71 8.45 Medium 5.91 8.68 13.24 15.57 16.65 10.27 High 5.20 8.92 12.62 18.39 21.35 12.11 Weighted Average 4.88 8.53 12.32 17.06 17.70 9.83 In an urban area with MSA of 250,000 499,999 Low 3.68 7.04 9.55 12.28 15.63 7.28 Medium 4.87 7.91 13.28 15.79 20.51 10.69 High 5.00 8.37 12.03 15.45 24.19 12.04 Weighted Average 4.08 7.75 11.46 14.96 20.19 9.66 In an urban area with MSA of 500,000 999,999 Low 3.78 6.89 9.30 14.47 12.55 7.18 Medium 4.55 7.60 9.59 13.25 17.82 8.89 High 5.15 8.34 13.29 17.60 21.84 12.71 Weighted Average 3.93 7.56 11.01 15.27 18.13 9.24 In an urban area with MSA of 1,000,000 2,999,999 Low 3.53 6.46 9.77 11.14 15.78 6.48 Medium 4.78 7.77 10.07 14.37 18.05 8.85 High 5.72 8.68 13.07 17.32 21.24 12.84 Weighted Average 4.18 7.79 11.39 15.39 18.70 9.40 In an urban area with MSA of 3 million or more Low 3.30 5.24 9.23 10.75 16.12 6.72 Medium 4.68 7.86 10.26 13.22 16.90 8.87 High 5.01 8.22 11.68 16.31 20.32 11.68 Weighted Average 4.04 7.40 10.71 14.40 18.10 9.28 In an urban area but not in a MSA Low 3.03 7.12 10.30 13.55 16.88 6.61 Medium 5.34 8.68 12.36 15.94 20.37 10.84 High 4.31 9.07 11.32 16.82 19.60 12.18 Weighted Average 3.73 8.14 11.58 15.34 19.06 9.25 In an urban area Low 3.45 6.45 9.68 12.45 15.75 6.87 Medium 4.87 8.00 10.96 14.23 18.07 9.38 High 5.13 8.46 12.24 16.71 20.89 12.12 Weighted Average 4.09 7.71 11.16 14.98 18.48 9.37

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39 Table 4.2 Average Daily Person Trips (on Weekends) Per Household by Persons Per Household and Income Persons per Household Income 1 2 3 4 5+ Weighted Average In an urban area with MSA of less than 250,000 Low 3.90 5.74 11.88 13.09 11.92 7.06 Medium 4.56 7.49 9.52 16.03 10.35 8.78 High 4.68 7.99 13.94 14.64 16.28 11.72 Weighted Average 4.06 7.31 11.70 14.65 13.15 8.91 In an urban area with MSA of 250,000 499,999 Low 3.28 5.45 8.35 11.63 16.53 6.51 Medium 4.35 6.73 9.25 12.60 24.72 9.51 High 2.77 9.63 12.96 20.13 15.53 12.35 Weighted Average 3.62 7.27 10.84 15.45 20.17 9.24 In an urban area with MSA of 500,000 999,999 Low 3.02 6.53 7.50 17.07 18.25 7.71 Medium 3.58 7.77 14.28 12.75 22.21 9.24 High 2.91 9.26 12.23 15.11 16.78 11.46 Weighted Average 3.03 7.96 12.29 14.36 18.68 9.20 In an urban area with MSA of 1,000,000 2,999,999 Low 3.44 5.90 11.77 9.66 16.54 6.26 Medium 4.84 7.91 10.31 16.36 18.05 9.41 High 3.63 8.41 10.92 15.90 20.65 11.89 Weighted Average 3.95 7.50 10.76 15.37 19.40 9.30 In an urban area with MSA of 3 million or more Low 2.92 5.51 7.62 10.78 16.76 6.75 Medium 4.46 7.35 10.85 12.87 15.26 8.68 High 4.72 7.33 10.96 14.76 19.96 11.23 Weighted Average 3.69 6.91 10.12 13.21 17.49 8.92 In an urban area but not in a MSA Low 3.15 4.67 9.06 17.16 17.30 7.07 Medium 4.59 7.84 10.52 15.92 16.62 9.79 High 3.46 8.71 10.47 13.33 21.12 11.02 Weighted Average 3.46 7.25 9.92 15.12 17.96 8.76 In an urban area Low 3.19 5.64 9.00 12.01 16.62 6.78 Medium 4.49 7.56 10.77 14.48 17.44 9.14 High 4.21 8.08 11.38 15.25 19.69 11.49 Weighted Average 3.69 7.25 10.57 14.25 18.04 9.04

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40 Table 4.3 Average Daily Person Trips (on Weekdays) Per Household by Persons Per Household and Auto Ownership Persons per Household Autos Owned 1 2 3 4 5+ Weighted Average In an urban area with MSA of less than 250,000 Zero 3.51 6.44 6.00 8.94 8.00 4.73 One 5.00 7.95 14.13 18.13 17.48 7.77 Two 5.33 8.70 10.82 16.73 16.20 10.49 Three Plus 6.46 9.12 12.91 17.58 19.92 13.36 Weighted Average 4.88 8.53 12.32 17.06 17.70 9.83 In an urban area with MSA of 250,000 499,999 Zero 2.05 5.58 9.40 8.00 24.67 4.02 One 4.34 7.29 8.94 15.57 12.21 6.29 Two 5.40 7.95 12.53 14.11 19.46 10.98 Three Plus 3.47 8.29 11.47 16.21 24.41 14.10 Weighted Average 4.08 7.75 11.46 14.96 20.19 9.66 In an urban area with MSA of 500,000 999,999 Zero 1.23 5.80 8.43 11.86 20.00 3.99 One 4.42 7.08 10.37 12.58 10.22 6.46 Two 4.87 7.85 11.17 16.40 20.02 11.05 Three Plus 3.90 8.05 11.75 15.42 18.99 12.88 Weighted Average 3.93 7.56 11.01 15.27 18.13 9.24 In an urban area with MSA of 1,000,000 2,999,999 Zero 2.47 3.39 11.50 6.18 14.37 4.19 One 4.53 7.36 10.23 13.15 16.46 6.72 Two 4.20 8.03 11.52 15.92 18.02 10.63 Three Plus 5.22 8.21 11.89 16.48 21.08 13.16 Weighted Average 4.18 7.79 11.39 15.39 18.70 9.40 In an urban area with MSA of 3 million or more Zero 2.93 5.17 8.76 8.24 13.25 4.98 One 4.40 7.13 10.42 12.14 14.67 6.87 Two 4.57 7.67 10.89 15.51 18.46 11.09 Three Plus 4.76 8.23 11.04 15.57 20.25 13.18 Weighted Average 4.04 7.40 10.71 14.40 18.10 9.28 In an urban area but not in a MSA Zero 1.63 5.76 8.88 11.17 22.00 3.12 One 4.23 7.04 10.46 14.69 17.98 6.67 Two 4.43 8.52 10.83 16.20 20.10 10.59 Three Plus 4.25 8.72 12.67 14.92 18.61 12.66 Weighted Average 3.73 8.14 11.58 15.34 19.06 9.25 In an urban area Zero 2.55 5.16 9.21 8.19 14.07 4.54 One 4.45 7.24 10.48 13.20 15.07 6.79 Two 4.59 7.99 11.22 15.69 18.55 10.86 Three Plus 4.74 8.37 11.72 15.87 20.46 13.17 Weighted Average 4.09 7.71 11.16 14.98 18.48 9.37

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41 Table 4.4 Average Daily Person Trips (on Weekends) Per Household by Persons Per Household and Auto Ownership Persons per Household Autos Owned 1 2 3 4 5+ Weighted Average In an urban area with MSA of less than 250,000 Zero 0.46 4.28 N/A 8.00 4.00 2.33 One 4.28 6.61 13.01 18.90 15.98 6.69 Two 6.16 7.27 12.17 14.17 13.84 9.89 Three Plus 1.82 8.77 11.20 14.12 13.28 11.31 Weighted Average 4.06 7.31 11.70 14.65 13.15 8.91 In an urban area with MSA of 250,000 499,999 Zero 1.38 5.05 0.00 13.63 9.00 3.90 One 3.89 5.87 11.14 12.11 12.67 6.02 Two 4.29 7.86 11.43 15.20 24.42 11.23 Three Plus 8.76 8.19 10.52 16.92 20.10 13.36 Weighted Average 3.62 7.27 10.84 15.45 20.17 9.24 In an urban area with MSA of 500,000 999,999 Zero 1.20 5.63 4.00 N/A 13.06 3.97 One 3.27 6.59 8.20 18.62 20.04 5.84 Two 3.27 8.14 11.40 13.56 17.34 9.94 Three Plus 4.79 9.39 14.33 14.12 20.13 13.39 Weighted Average 3.03 7.96 12.29 14.36 18.68 9.20 In an urban area with MSA of 1,000,000 2,999,999 Zero 1.84 5.22 11.02 10.45 13.14 4.12 One 4.31 7.90 12.98 9.61 25.05 6.42 Two 3.69 7.31 9.88 15.95 18.37 10.73 Three Plus 5.09 7.91 10.63 16.40 20.75 12.74 Weighted Average 3.95 7.50 10.76 15.37 19.40 9.30 In an urban area with MSA of 3 million or more Zero 2.52 4.49 5.58 7.77 7.41 3.72 One 4.06 6.69 8.38 13.34 14.18 6.54 Two 4.05 7.45 10.37 13.58 19.71 10.96 Three Plus 4.60 6.84 11.79 13.54 17.69 12.49 Weighted Average 3.69 6.91 10.12 13.21 17.49 8.92 In an urban area but not in a MSA Zero 1.98 5.33 5.40 23.62 22.00 5.01 One 3.59 4.95 8.75 20.50 16.34 5.53 Two 4.32 7.32 9.53 15.48 17.36 10.28 Three Plus 6.49 8.86 10.96 13.33 18.83 11.54 Weighted Average 3.46 7.25 9.92 15.12 17.96 8.76 In an urban area Zero 2.13 4.82 5.26 9.91 10.90 3.92 One 4.01 6.73 9.74 13.63 15.86 6.32 Two 4.06 7.48 10.52 14.54 19.13 10.69 Three Plus 5.15 8.02 11.53 14.57 18.52 12.48 Weighted Average 3.69 7.25 10.57 14.25 18.04 9.04

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42 Table 4.5 Average Daily Person Trips (on Weekdays) Per Household by Income and Auto Ownership Autos Owned Income 0 1 2 3+ Weighted Average In an urban area with MSA of less than 250,000 Low 5.52 7.81 9.77 11.19 8.45 Medium 5.71 8.23 10.46 13.59 10.27 High 8.00 7.37 11.74 14.31 12.11 Weighted Average 4.73 7.77 10.49 13.36 9.83 In an urban area with MSA of 250,000 499,999 Low 4.69 6.06 9.32 12.50 7.28 Medium 7.38 7.14 11.51 15.37 10.69 High 5.00 5.85 11.91 14.18 12.04 Weighted Average 4.02 6.29 10.98 14.10 9.66 In an urban area with MSA of 500,000 999,999 Low 4.91 6.56 9.68 11.53 7.18 Medium 4.47 6.55 9.93 11.26 8.89 High 3.00 7.50 12.95 14.54 12.71 Weighted Average 3.99 6.46 11.05 12.88 9.24 In an urban area with MSA of 1,000,000 2,999,999 Low 4.35 6.23 7.69 11.19 6.48 Medium 4.73 6.89 9.87 11.31 8.85 High 7.80 8.80 12.64 14.48 12.84 Weighted Average 4.19 6.72 10.63 13.16 9.40 In an urban area with MSA of 3 million or more Low 4.59 6.61 9.23 12.32 6.72 Medium 6.25 7.44 10.09 11.57 8.87 High 8.15 7.23 12.36 14.07 11.68 Weighted Average 4.98 6.87 11.09 13.18 9.28 In an urban area but not in a MSA Low 2.92 6.15 9.07 9.84 6.61 Medium 2.05 8.17 11.11 13.18 10.84 High 12.84 6.08 11.71 13.66 12.18 Weighted Average 3.12 6.67 10.59 12.66 9.25 In an urban area Low 4.41 6.48 8.88 11.45 6.87 Medium 5.82 7.33 10.33 12.33 9.38 High 8.00 7.42 12.38 14.20 12.12 Weighted Average 4.54 6.79 10.86 13.17 9.37

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43 Table 4.6 Average Daily Person Trips (on Weekends) Per Household by Income and Auto Ownership Autos Owned Income 0 1 2 3+ Weighted Average In an urban area with MSA of less than 250,000 Low 2.92 6.04 10.31 9.32 7.06 Medium 0.00 7.13 9.27 9.98 8.78 High N/A 10.85 10.92 12.87 11.72 Weighted Average 2.33 6.69 9.89 11.31 8.91 In an urban area with MSA of 250,000 499,999 Low 3.63 5.15 8.11 12.52 6.51 Medium 2.00 5.67 12.11 13.51 9.51 High N/A 8.49 12.43 13.89 12.35 Weighted Average 3.90 6.02 11.23 13.36 9.24 In an urban area with MSA of 500,000 999,999 Low 3.35 7.75 7.73 13.16 7.71 Medium 18.92 4.23 9.21 13.48 9.24 High 2.00 7.13 11.33 13.41 11.46 Weighted Average 3.97 5.84 9.94 13.39 9.20 In an urban area with MSA of 1,000,000 2,999,999 Low 4.62 5.92 7.81 7.69 6.26 Medium 2.24 6.80 11.52 12.03 9.41 High 4.12 6.76 11.57 14.16 11.89 Weighted Average 4.12 6.42 10.73 12.74 9.30 In an urban area with MSA of 3 million or more Low 3.29 6.51 10.78 12.03 6.75 Medium 4.55 6.81 10.43 12.05 8.68 High 6.39 7.14 11.91 13.16 11.23 Weighted Average 3.72 6.54 10.96 12.49 8.92 In an urban area but not in a MSA Low 6.11 5.45 10.73 9.52 7.07 Medium 4.46 6.12 10.77 11.44 9.79 High N/A 5.90 9.99 13.00 11.02 Weighted Average 5.01 5.53 10.28 11.54 8.76 In an urban area Low 3.94 6.14 9.33 10.88 6.78 Medium 4.61 6.46 10.69 12.07 9.14 High 5.76 7.25 11.62 13.44 11.49 Weighted Average 3.92 6.32 10.69 12.48 9.04

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44 Table 4.7 Average Daily Vehicle Trips (o n Weekdays) Per Household by Persons Per Household and Income Persons per Household Income 1 2 3 4 5+ Weighted Average In an urban area with MSA of less than 250,000 Low 3.24 5.31 8.99 7.89 6.59 5.04 Medium 5.20 6.40 8.90 8.89 8.64 6.98 High 4.02 6.70 8.69 9.83 11.00 7.76 Weighted Average 3.91 6.13 8.55 8.96 8.76 6.37 In an urban area with MSA of 250,000 499,999 Low 2.95 4.46 5.56 5.03 6.53 4.20 Medium 4.21 5.97 7.74 8.29 9.66 6.60 High 3.43 6.80 7.85 9.13 12.92 7.82 Weighted Average 3.28 5.80 7.05 8.13 10.03 6.06 In an urban area with MSA of 500,000 999,999 Low 2.79 4.37 4.03 7.70 9.10 4.26 Medium 4.05 5.58 6.31 7.36 7.28 5.69 High 4.12 6.81 9.46 10.10 12.19 8.47 Weighted Average 3.17 5.60 7.15 8.57 9.73 5.95 In an urban area with MSA of 1,000,000 2,999,999 Low 2.27 4.52 4.68 4.94 7.49 3.61 Medium 4.02 5.81 6.43 8.06 7.17 5.75 High 4.82 6.93 8.82 9.72 11.04 8.30 Weighted Average 3.19 5.96 7.24 8.56 9.01 6.00 In an urban area with MSA of 3 million or more Low 1.80 2.93 4.45 4.89 5.74 3.04 Medium 3.45 5.52 6.01 6.97 7.01 5.29 High 3.44 5.94 7.73 8.71 9.80 7.01 Weighted Average 2.65 5.21 6.62 7.65 8.15 5.40 In an urban area but not in a MSA Low 2.23 4.80 6.05 6.04 6.43 3.84 Medium 4.59 6.53 8.58 9.62 9.76 7.24 High 3.68 7.41 8.43 9.35 9.98 8.14 Weighted Average 2.95 6.10 7.92 8.43 8.86 5.97 In an urban area Low 2.27 4.15 5.07 5.66 6.58 3.68 Medium 3.95 5.86 6.92 7.85 7.87 5.94 High 3.76 6.47 8.28 9.17 10.54 7.60 Weighted Average 2.99 5.66 7.11 8.13 8.73 5.77

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45 Table 4.8 Average Daily Vehicle Trips (o n Weekends) Per Household by Persons Per Household and Income Persons per Household Income 1 2 3 4 5+ Weighted Average In an urban area with MSA of less than 250,000 Low 3.01 3.56 5.18 3.71 5.30 3.75 Medium 4.22 4.79 4.61 7.52 3.89 5.03 High 4.68 5.51 7.37 6.64 7.93 6.41 Weighted Average 3.41 4.73 5.74 6.47 5.87 4.95 In an urban area with MSA of 250,000 499,999 Low 2.08 3.52 4.50 6.20 4.55 3.33 Medium 3.55 4.10 4.99 5.77 7.61 4.72 High 2.53 5.65 6.78 10.06 5.89 6.49 Weighted Average 2.61 4.40 5.71 7.40 6.13 4.64 In an urban area with MSA of 500,000 999,999 Low 1.89 3.21 3.31 4.38 7.13 3.28 Medium 3.03 4.92 9.10 6.63 8.40 5.48 High 2.14 6.28 7.29 7.08 6.49 6.34 Weighted Average 2.32 4.92 7.50 6.51 7.21 5.03 In an urban area with MSA of 1,000,000 2,999,999 Low 2.55 3.68 6.02 3.61 3.16 3.37 Medium 4.14 4.72 5.87 8.75 7.15 5.51 High 3.01 5.54 6.86 8.12 9.28 6.65 Weighted Average 3.17 4.79 6.32 7.85 7.87 5.29 In an urban area with MSA of 3 million or more Low 1.54 3.46 3.37 5.15 5.43 2.91 Medium 3.02 4.53 5.90 5.42 6.08 4.56 High 3.35 4.62 6.46 7.22 7.89 5.87 Weighted Average 2.34 4.35 5.67 6.18 6.85 4.57 In an urban area but not in a MSA Low 1.97 2.39 4.14 5.62 5.93 3.09 Medium 3.75 5.39 6.11 6.01 6.75 5.40 High 3.37 5.95 6.30 6.62 9.95 6.39 Weighted Average 2.52 4.79 5.52 6.11 7.28 4.67 In an urban area Low 2.03 3.35 4.27 4.87 5.40 3.18 Medium 3.50 4.72 6.04 6.78 6.63 5.03 High 3.20 5.24 6.68 7.53 8.21 6.20 Weighted Average 2.64 4.60 5.94 6.72 7.02 4.82

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46 Table 4.9 Average Daily Vehicle Trips (o n Weekdays) Per Household by Persons Per Household and Auto Ownership Persons per Household Autos Owned 1 2 3 4 5+ Weighted Average In an urban area with MSA of less than 250,000 Zero 0.18 0.10 0.00 11.00 N/A 0.42 One 4.39 4.40 7.82 6.82 5.27 4.83 Two 4.68 6.90 7.36 8.51 7.81 7.06 Three Plus 6.34 7.01 10.16 10.32 10.96 9.11 Weighted Average 3.91 6.13 8.55 8.96 8.76 6.37 In an urban area with MSA of 250,000 499,999 Zero 0.00 1.13 0.00 0.00 0.45 0.19 One 3.82 4.61 4.01 7.04 6.44 4.23 Two 4.52 6.47 7.87 7.13 9.28 7.03 Three Plus 2.02 6.32 7.63 9.89 12.33 8.58 Weighted Average 3.28 5.80 7.05 8.13 10.03 6.06 In an urban area with MSA of 500,000 999,999 Zero 0.04 1.80 0.41 1.65 N/A 0.56 One 3.73 4.43 5.35 6.56 5.44 4.28 Two 4.15 6.30 7.58 8.86 9.68 7.16 Three Plus 3.78 6.54 9.10 9.88 10.63 8.70 Weighted Average 3.17 5.60 7.15 8.57 9.73 5.95 In an urban area with MSA of 1,000,000 2,999,999 Zero 0.20 0.59 0.58 2.24 1.44 0.42 One 3.76 4.64 5.36 6.28 6.98 4.36 Two 3.59 6.36 7.24 8.15 7.78 6.72 Three Plus 4.64 6.94 8.65 10.43 11.88 8.97 Weighted Average 3.19 5.96 7.24 8.56 9.01 6.00 In an urban area with MSA of 3 million or more Zero 0.10 0.34 1.35 0.50 2.34 0.33 One 3.47 4.13 4.48 4.90 4.74 3.90 Two 3.96 5.96 6.98 7.83 7.45 6.62 Three Plus 4.14 6.45 8.46 9.94 10.94 8.70 Weighted Average 2.65 5.21 6.62 7.65 8.15 5.40 In an urban area but not in a MSA Zero 0.13 0.68 4.04 10.00 0.00 0.42 One 3.58 4.20 5.56 6.33 7.14 4.19 Two 3.95 6.85 6.65 8.04 8.92 6.86 Three Plus 4.25 6.97 9.77 9.44 10.01 8.73 Weighted Average 2.95 6.10 7.92 8.43 8.86 5.97 In an urban area Zero 0.11 0.60 1.09 1.21 1.93 0.37 One 3.68 4.34 4.99 5.68 5.80 4.17 Two 3.96 6.32 7.17 8.00 7.99 6.78 Three Plus 4.23 6.69 8.78 10.00 11.12 8.79 Weighted Average 2.99 5.66 7.11 8.13 8.73 5.77

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47 Table 4.10 Average Daily Vehicle Trips (o n Weekends) Per Household by Persons Per Household and Auto Ownership Persons per Household Autos Owned 1 2 3 4 5+ Weighted Average In an urban area with MSA of less than 250,000 Zero 0.00 0.00 0.00 0.00 N/A 0.00 One 3.57 3.58 4.89 5.58 5.44 3.83 Two 5.82 4.74 5.29 5.65 5.41 5.11 Three Plus 1.82 6.66 6.72 8.18 6.39 6.90 Weighted Average 3.41 4.73 5.74 6.47 5.87 4.95 In an urban area with MSA of 250,000 499,999 Zero 0.00 0.33 0.00 0.00 2.00 0.27 One 3.02 2.78 5.34 6.26 3.16 3.39 Two 3.17 5.31 5.57 6.00 6.07 5.31 Three Plus 5.73 4.90 6.63 9.80 7.99 7.15 Weighted Average 2.61 4.40 5.71 7.40 6.13 4.64 In an urban area with MSA of 500,000 999,999 Zero 0.00 1.66 0.00 N/A 11.41 1.03 One 2.67 3.24 3.71 4.17 5.02 3.02 Two 2.39 5.40 6.19 6.12 5.62 5.42 Three Plus 4.56 6.11 9.93 7.29 8.74 7.73 Weighted Average 2.32 4.92 7.50 6.51 7.21 5.03 In an urban area with MSA of 1,000,000 2,999,999 Zero 0.00 0.86 2.65 0.00 0.00 0.24 One 3.72 4.30 5.78 3.90 5.19 4.04 Two 3.01 4.97 5.76 7.06 7.23 5.68 Three Plus 4.00 5.58 7.35 10.44 9.87 7.91 Weighted Average 3.17 4.79 6.32 7.85 7.87 5.29 In an urban area with MSA of 3 million or more Zero 0.11 1.11 0.81 0.00 0.00 0.30 One 3.06 3.75 3.59 5.14 3.91 3.47 Two 3.33 4.90 5.70 5.83 6.49 5.40 Three Plus 3.16 4.88 7.50 7.81 8.45 7.17 Weighted Average 2.34 4.35 5.67 6.18 6.85 4.57 In an urban area but not in a MSA Zero 0.15 0.48 0.00 3.72 6.00 0.77 One 2.91 2.84 3.53 5.91 6.48 3.23 Two 3.14 4.89 5.07 5.68 6.64 5.13 Three Plus 6.45 6.65 6.79 6.81 8.63 6.99 Weighted Average 2.52 4.79 5.52 6.11 7.28 4.67 In an urban area Zero 0.08 0.97 0.72 0.46 2.59 0.39 One 3.21 3.64 4.27 4.99 4.49 3.56 Two 3.23 4.98 5.66 6.18 6.56 5.41 Three Plus 4.16 5.67 7.46 8.47 8.62 7.35 Weighted Average 2.64 4.60 5.94 6.72 7.02 4.82

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48 Table 4.11 Average Daily Vehicle Trips (o n Weekdays) Per Household by Income and Auto Ownership Autos Owned Income 0 1 2 3+ Weighted Average In an urban area with MSA of less than 250,000 Low 0.55 4.28 6.90 8.36 5.04 Medium 0.68 5.73 7.08 9.37 6.98 High 5.00 4.57 7.58 9.15 7.76 Weighted Average 0.42 4.83 7.06 9.11 6.37 In an urban area with MSA of 250,000 499,999 Low 0.19 3.95 5.61 6.99 4.20 Medium 0.00 4.91 7.31 8.32 6.60 High 5.00 3.82 7.59 9.36 7.82 Weighted Average 0.19 4.23 7.03 8.58 6.06 In an urban area with MSA of 500,000 999,999 Low 0.70 4.15 6.59 8.66 4.26 Medium 0.94 4.59 6.23 6.99 5.69 High 0.00 4.78 8.36 10.25 8.47 Weighted Average 0.56 4.28 7.16 8.70 5.95 In an urban area with MSA of 1,000,000 2,999,999 Low 0.25 3.81 4.82 7.68 3.61 Medium 1.27 4.66 6.30 7.42 5.75 High 3.39 5.46 7.81 9.97 8.30 Weighted Average 0.42 4.36 6.72 8.97 6.00 In an urban area with MSA of 3 million or more Low 0.19 3.48 5.21 7.35 3.04 Medium 0.63 4.50 6.18 7.80 5.29 High 0.57 3.76 7.27 9.27 7.01 Weighted Average 0.33 3.90 6.62 8.70 5.40 In an urban area but not in a MSA Low 0.30 3.62 5.70 6.62 3.84 Medium 0.00 5.45 7.23 9.17 7.24 High 10.31 3.75 7.62 9.36 8.14 Weighted Average 0.42 4.19 6.86 8.73 5.97 In an urban area Low 0.27 3.76 5.49 7.46 3.68 Medium 0.69 4.76 6.55 8.11 5.94 High 1.10 4.16 7.56 9.54 7.60 Weighted Average 0.37 4.17 6.78 8.79 5.77

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49 Table 4.12 Average Daily Vehicle Trips (o n Weekends) Per Household by Income and Auto Ownership Autos Owned Income 0 1 2 3+ Weighted Average In an urban area with MSA of less than 250,000 Low 0.00 3.31 5.54 4.80 3.75 Medium 0.00 4.37 4.74 6.67 5.03 High N/A 5.49 5.56 7.64 6.41 Weighted Average 0.00 3.83 5.11 6.90 4.95 In an urban area with MSA of 250,000 499,999 Low 0.32 3.17 4.49 5.48 3.33 Medium 0.48 3.63 4.97 7.10 4.72 High N/A 3.52 6.45 7.79 6.49 Weighted Average 0.27 3.39 5.31 7.15 4.64 In an urban area with MSA of 500,000 999,999 Low 0.60 2.99 3.99 6.01 3.28 Medium 7.31 2.90 5.16 8.14 5.48 High 0.00 4.09 6.20 7.57 6.34 Weighted Average 1.03 3.02 5.42 7.73 5.03 In an urban area with MSA of 1,000,000 2,999,999 Low 0.14 3.64 4.60 5.51 3.37 Medium 0.00 4.46 5.96 7.53 5.51 High 2.06 4.38 5.92 8.52 6.65 Weighted Average 0.24 4.04 5.68 7.91 5.29 In an urban area with MSA of 3 million or more Low 0.15 3.22 4.45 5.79 2.91 Medium 0.72 3.67 5.42 7.19 4.56 High 0.53 3.88 5.75 7.55 5.87 Weighted Average 0.30 3.47 5.40 7.17 4.57 In an urban area but not in a MSA Low 0.95 2.78 4.23 6.31 3.09 Medium 0.81 4.03 5.21 6.92 5.40 High N/A 4.07 5.78 7.45 6.39 Weighted Average 0.77 3.23 5.13 6.99 4.67 In an urban area Low 0.32 3.22 4.53 5.76 3.18 Medium 0.85 3.90 5.39 7.30 5.03 High 0.89 4.02 5.87 7.81 6.20 Weighted Average 0.39 3.56 5.41 7.35 4.82

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Figure 4.1 shows the comparison of the person and vehicle trip rates on weekdays and weekends with the household size. Figure 4.1 Trip Rates per Household on Weekdays and Weekends by Household Size 0246810121416182012345+Number of Persons in the HouseholdDaily Trips Weekday Person Trips Weekday Vehicle Trips Weekend Person Trips Weekend Vehicle Trips As the number of persons in the households increase, both the weekday and weekend person trips increased in the same proportion but the vehicle trips increased at a lower rate with almost flattening after two or more persons in the household. There is almost no change in person trips being made by household of any size on weekdays and weekends, however the total vehicle trips made by the household on weekends tend to be much lower than those on weekends with the gap increasing as the household size increases. 50

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This may be because lower sized household have more flexibility in their time schedules with less obligations as compared to the bigger households sizes where many members from same household can make a collective trip. As the income increases, households make more person trips on both weekdays and weekends. Figure 4.2 shows that lower income households make almost the same number of trips whether it is a weekday or a weekend but the difference increase drastically as the household income increases. However the vehicle trips made by higher income households do not increase in direct proportion to the person trips. This may Figure 4.2 Trip Rates per Household on Weekdays and Weekends by Income 51 02468101214LowMediumHighAnnual Household IncomeDaily Trips Weekday Person Trips Weekday Vehicle Trips Weekend Person Trips Weekend Vehicle Trips

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52 possibly be because of higher income househol ds making the work or work related trips on weekdays as compared to involvement in some recreational or family related travel activities on weekends. Contra stingly, low-income househol ds may possibly be making all their travel for work only and that too without any flexible in choosing their time schedule. Not only is the demand for the travel vary ing with the number of persons in the household and income important, but also is th e vehicle availability in the household that makes the fulfillment of such a demand of trav el to take place in reality. Figure 4.3 show the comparison of trip rates per househol d on weekdays and weekend by numbers of vehicle owned by the household. The household with no vehicle makes slightly lesser number of person trips on weekends (3.94) th an that made on weekdays (4.41). This may be because of the unavailability of public tr ansit on weekends to make their travel possible. However, such households were found to make more ve hicle trips about 0.39 trips on weekends as compared to the 0.37 tr ips on weekdays possibl y because of rented vehicle been utilized more on weekends. As the number of vehicles increase, more and more vehicles are being driven. Weekday ve hicle trips tend to be more than that on weekends due to more diversity in the de stinations on weekdays to be reached by a vehicle as compared to the weekends where more numbers of persons have the same purpose to be fulfilled by that trip.

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Figure 4.3 Trip Rates per Household on Weekdays and Weekends by Autos Owned 024681012140123+Number of Vehicles in the HouseholdDaily Trips Weekday Person Trips Weekday Vehicle Trips Weekend Person Trips Weekend Vehicle Trips Although the person trips tend to similar for the weekdays and the weekends but there a combination of two or more household attributes that may lead to a better understanding of the travel behavior. For example as shown in Figure 4.4, about 25% more trips are been made by a household with five or more persons and high income to those compared of having low income. The differences tend to dampen down on weekends due to non-working nature of the weekend days. Further, one person households do not show as much variation with household income and day of week as do the complex behavior that is exhibited by households of more than one person. Households without any vehicles show a drastic change in daily trips with the number of 53

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Figure 4.4 Person Trip Rates Per Household on Weekdays and Weekends by Income and Household Size LowWeekdayLowWeekendMediumWeekdayMediumWeekendHighWeekdayHighWeekend 12345+ 0510152025Daily TripsIncomeHousehold Size persons in the household. Households having one or more vehicles and any number of persons show a lesser number of trips on weekends as compared to the weekdays. Figure 4.5 shows households with more than five persons and having one or two vehicles making almost the same number of trips on weekends as made by them on weekdays. A household with two persons and with no vehicle is found to make almost as many trips on weekdays as those made by households with one vehicle and two persons on weekends. 54

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Figure 4.5 Person Trip Rates per Household on Weekdays and Weekends by Number of Vehicles Owned and Household Size ZeroWeekdayZeroWeekendOneWeekdayOneWeekendTwoWeekdayTwoWeekendThree PlusWeekdayThree PlusWeekend 12345+ 0510152025Daily tripsNumber of Autos OwnedHousehold Size 4.3 Trip Rates by Person Characteristics An average person is found to make more person trips and vehicle trips on weekdays as compared to those on weekends. In an urban area, a person makes about 4.14 trips on weekdays slightly short of those made on weekends (3.88). As a driver, he/she made about 2.44 vehicle trips on weekdays as compared to 1.95 trips on weekends. Tables 4.13 and 4.14 show a comparison of daily person and vehicle trips made by the person by his gender and age categories. Children between 0-15 years of age are found to make more trips on weekends (3.43) as compared to those on weekdays (3.36). This may be because on weekdays they cannot be left alone at home unattended 55

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56 Table 4.13 Average Daily Person and Vehicl e Trips (on Weekdays) by Gender and Age Person Trips Vehicle Trips Age Male Female All Male Female All In an urban area with MSA of less than 250,000 0-15 3.26 3.81 3.53 0.03 0.01 0.02 16-24 5.09 4.87 4.98 3.71 3.02 3.36 25-39 4.88 5.20 5.04 4.04 3.79 3.91 40-64 4.87 4.87 4.87 4.10 3.72 3.90 65+ 4.78 4.20 4.44 4.03 2.44 3.11 Weighted Average 4.50 4.63 4.57 3.04 2.69 2.85 In an urban area with MSA of 250,000 499,999 0-15 3.43 3.32 3.38 0.02 0.00 0.01 16-24 4.42 4.54 4.48 3.08 2.64 2.86 25-39 4.58 4.96 4.77 3.67 3.72 3.69 40-64 4.61 4.74 4.68 3.89 3.61 3.74 65+ 3.84 3.30 3.52 3.11 2.05 2.48 Weighted Average 4.20 4.22 4.21 2.71 2.46 2.58 In an urban area with MSA of 500,000 999,999 0-15 3.50 3.30 3.41 0.00 0.05 0.02 16-24 3.92 4.75 4.33 2.53 2.68 2.61 25-39 4.15 4.96 4.56 3.48 4.08 3.78 40-64 4.45 4.83 4.66 3.81 3.55 3.66 65+ 4.16 3.03 3.50 3.35 1.94 2.53 Weighted Average 4.04 4.28 4.16 2.54 2.60 2.57 In an urban area with MSA of 1,000,000 2,999,999 0-15 3.33 3.27 3.30 0.02 0.03 0.02 16-24 3.97 4.60 4.27 2.45 2.68 2.56 25-39 4.45 4.85 4.65 3.76 3.75 3.75 40-64 4.62 4.64 4.63 3.96 3.41 3.68 65+ 4.12 3.24 3.59 3.42 1.85 2.47 Weighted Average 4.14 4.19 4.16 2.71 2.45 2.58 In an urban area with MSA of 3 million or more 0-15 3.37 3.32 3.35 0.01 0.01 0.01 16-24 3.82 3.90 3.86 2.12 1.83 1.99 25-39 4.21 4.68 4.45 2.96 3.08 3.02 40-64 4.33 4.65 4.50 3.48 3.27 3.37 65+ 3.86 3.13 3.43 2.91 1.64 2.16 Weighted Average 3.95 4.10 4.03 2.26 2.14 2.20 In an urban area but not in a MSA 0-15 3.42 3.47 3.44 0.05 0.03 0.04 16-24 4.21 4.49 4.35 2.74 2.65 2.69 25-39 4.67 5.18 4.92 4.06 3.98 4.02 40-64 4.65 4.60 4.62 4.07 3.43 3.74 65+ 4.14 3.37 3.68 3.45 2.10 2.65 Weighted Average 4.23 4.23 4.23 2.84 2.45 2.64 In an urban area 0-15 3.37 3.35 3.36 0.02 0.02 0.02 16-24 4.03 4.33 4.18 2.48 2.35 2.42 25-39 4.37 4.83 4.61 3.41 3.48 3.45 40-64 4.50 4.68 4.59 3.75 3.40 3.57 65+ 4.04 3.26 3.58 3.23 1.86 2.42 Weighted Average 4.09 4.19 4.14 2.53 2.35 2.44

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57 Table 4.14 Average Daily Person and Vehicl e Trips (on Weekends) by Gender and Age Person Trips Vehicle Trips Age Male Female All Male Female All In an urban area with MSA of less than 250,000 0-15 3.38 3.95 3.66 0.01 0.02 0.01 16-24 4.49 4.83 4.63 2.16 2.58 2.33 25-39 4.02 4.19 4.11 3.25 2.56 2.88 40-64 4.26 4.02 4.14 3.71 2.43 3.05 65+ 3.83 2.86 3.32 3.00 1.34 2.13 Weighted Average 4.00 3.96 3.98 2.48 1.80 2.14 In an urban area with MSA of 250,000 499,999 0-15 4.25 3.51 3.92 0.04 0.01 0.03 16-24 4.24 3.57 3.85 2.46 1.89 2.13 25-39 4.22 4.58 4.42 3.20 2.04 2.57 40-64 4.61 4.20 4.41 3.64 2.33 2.99 65+ 2.88 2.80 2.84 1.86 1.27 1.53 Weighted Average 4.19 3.88 4.03 2.32 1.61 1.95 In an urban area with MSA of 500,000 999,999 0-15 3.47 3.58 3.53 0.00 0.00 0.00 16-24 4.58 4.25 4.41 3.25 2.17 2.70 25-39 4.07 4.76 4.42 3.04 2.74 2.89 40-64 4.61 4.69 4.65 3.94 2.43 3.14 65+ 3.89 2.60 3.10 3.11 1.10 1.88 Weighted Average 4.14 4.07 4.10 2.65 1.67 2.12 In an urban area with MSA of 1,000,000 2,999,999 0-15 3.49 3.53 3.51 0.02 0.01 0.02 16-24 4.26 4.73 4.47 2.37 2.50 2.43 25-39 4.20 4.41 4.30 3.37 2.62 3.02 40-64 4.42 4.51 4.47 3.66 2.81 3.21 65+ 3.66 3.12 3.34 2.74 1.65 2.11 Weighted Average 4.05 4.10 4.08 2.48 1.95 2.21 In an urban area with MSA of 3 million or more 0-15 3.41 3.13 3.27 0.01 0.01 0.01 16-24 3.66 3.73 3.70 1.99 1.42 1.69 25-39 3.98 4.00 3.99 2.94 2.02 2.49 40-64 4.24 4.07 4.15 3.33 2.20 2.74 65+ 3.40 2.68 2.98 2.58 1.34 1.86 Weighted Average 3.82 3.62 3.71 2.15 1.42 1.77 In an urban area but not in a MSA 0-15 3.43 3.50 3.46 0.04 0.00 0.03 16-24 3.96 4.04 4.00 2.44 1.28 1.83 25-39 3.80 4.01 3.91 3.12 2.16 2.61 40-64 4.24 4.33 4.29 3.33 2.47 2.91 65+ 3.28 2.90 3.05 2.54 1.55 1.93 Weighted Average 3.80 3.82 3.81 2.21 1.61 1.91 In an urban area 0-15 3.50 3.36 3.43 0.02 0.01 0.01 16-24 4.01 4.05 4.03 2.26 1.78 2.02 25-39 4.05 4.21 4.13 3.10 2.25 2.68 40-64 4.34 4.26 4.30 3.50 2.41 2.94 65+ 3.47 2.82 3.09 2.62 1.41 1.92 Weighted Average 3.93 3.82 3.88 2.30 1.62 1.95

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while the other members of the household (adults) have to go to work thereby dropping them to day care facilities whereas on weekends they go to all the places as a passenger with the other adults. The person trips show a rise on weekends as compared to the weekdays due to more non-motorized modes (like bicycling and walking) dependencies of persons of these age groups. Persons belonging to 25-39 years of age make about 0.77 more trips on weekdays as compared to those made on weekends due to more driving for the work. Persons in 16-24 years age group make far more person trips on both Figure 4.6 Trip Rates per Person on Weekdays and Weekends by Age of the Person 00.511.522.533.544.550-1516-2425-3940-6465+AgeDaily Trips Weekday Person Trips Weekend Person Trips Weekday Vehicle Trips Weekend Vehicle Trips weekdays and weekends than those of 65 years and above do although both of them make the same number of vehicle trips. However, older age persons do make much lesser 58

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59 person trips on weekends as compared to t hose made on weekdays. This may be because of younger age groups make more social recreational trips as compared to the older age groups who may rather enjoy being at home utilizing most of the time in in-home activities. Figure 4.7 and 4.8 shows the comparison of person and vehicle trips per person by gender, age and weekday or weekend status Females are found to make more person trips on weekdays but almost the same on w eekends than males. On weekdays, females may be engaged into more activities as compar ed to men such as taking care of children. On the other hand, males generally make more vehicle trips than females, the difference being much larger on weekends than that on weekday. This may possibly be because of men being doing the most of the driving w ith females being as a passenger on the trip. However, for persons with 65 years and above, males dominate females in both the person trips as well as vehicle trips on bot h weekdays and weekends. Other exceptions include women from 25-39 years of age who ma ke slightly more vehicle trips than males of the same age group on weekdays possibly due to much more obligations to be fulfilled as compared to the males. Females in 015 years age group are found to be making less trips than males on weekends as compared to weekdays where both of them makes almost the same number of trips.

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Figure 4.7 Trip Rates per Person on Weekdays by Age and Gender 00.511.522.533.544.555.50-1516-2425-3940-6465+ Male Person Trips Female Person Trips Male Vehicle Trips Female Vehicle Trips Figure 4.8 Trip Rates per Person on Weekends by Age and Gender 00.511.522.533.544.550-1516-2425-3940-6465+ Male Person Trips Female Person Trips Male Vehicle Trips Female Vehicle Trips 60

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61 4.4 Trips by Purpose This section of this chapter deals with the variation of person trips by purpose, household income and household size. Tables 4.15 and 4.16 shows that home-based work (HBW) trips are the maximum number of tr ips (14%) made on wee kdays whereas their decrement on weekends is distributed to ot her trips such as for shopping and social recreational purposes. Both the shopping trips and social recreational trips increase on weekends whereas trips for other purposes decrease. High-income households show the maximum decrease in the percen tage of home based work trips and increase in shop and social recreational trips implying that weekends tend to constitute most of their non-work related trips. Percent of non-home based tr ips are maximum for single person households with more flexibility to make a trip whereas as the household size increases the percentage decreases for home being the only place where most of the members can meet and make a trip.

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Table 4.15 Trip Estimation Variables by Urban Size Weekdays Weekends % Average Daily Person Trips % Average Daily Person Trips Average Autos per Household Average Daily Person Trips per Household Average Daily Vehicle Trips per Household HBW HBO NHB Average Daily Person Trips per Household Average Daily Vehicle Trips per Household HBW HBO NHB In an urban area with MSA of less than 250,000 Income Low 1.40 8.45 5.04 9.78 60.14 30.08 7.06 3.75 7.54 64.66 27.79 Medium 1.94 10.27 6.98 15.96 52.39 31.65 8.78 5.03 5.08 60.57 34.35 High 2.49 12.11 7.76 14.77 49.54 35.69 11.72 6.41 4.75 66.86 28.39 Weighted Avg. 1.87 9.83 6.37 13.86 53.89 32.25 8.91 4.95 5.83 64.32 29.85 Household Size 1 1.06 4.88 3.91 13.46 48.23 38.31 4.06 3.41 2.77 66.32 30.90 2 1.95 8.53 6.13 16.19 50.58 33.23 7.31 4.73 6.26 63.03 30.71 3 2.37 12.32 8.55 16.07 51.02 32.91 11.70 5.74 6.96 61.63 31.40 4 2.33 17.06 8.96 10.06 58.56 31.38 14.65 6.47 5.51 65.73 28.77 5+ 2.51 17.70 8.76 12.38 61.26 26.36 13.15 5.87 5.18 68.22 26.60 Weighted Avg. 1.87 9.83 6.37 13.86 53.89 32.25 8.91 4.95 5.83 64.32 29.85 In an urban area with MSA of 250,000 499,999 Income Low 1.33 7.28 4.20 11.76 58.91 29.33 6.51 3.33 6.71 62.13 31.16 Medium 1.89 10.69 6.60 13.96 55.43 30.62 9.51 4.72 4.67 61.90 33.43 High 2.50 12.04 7.82 15.26 50.90 33.85 12.35 6.49 4.04 63.86 32.10 Weighted Avg. 1.85 9.66 6.06 13.74 54.89 31.38 9.24 4.64 4.75 62.55 32.70 Household Size 1 1.01 4.08 3.28 13.48 51.64 34.88 3.62 2.61 4.07 64.80 31.13 2 1.88 7.75 5.80 15.29 52.08 32.63 7.27 4.40 4.14 63.14 32.73 3 2.21 11.46 7.05 14.55 51.13 34.31 10.84 5.71 6.41 62.96 30.63 4 2.60 14.96 8.13 14.19 57.90 27.92 15.45 7.40 4.32 65.99 29.69 5+ 2.37 20.19 10.03 10.57 60.15 29.28 20.17 6.13 4.58 57.93 37.49 Weighted Avg. 1.85 9.66 6.06 13.74 54.89 31.38 9.24 4.64 4.75 62.55 32.70

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Table 4.15 Continued Weekdays Weekends % Average Daily Person Trips % Average Daily Person Trips Average Autos per Household Average Daily Person Trips per Household Average Daily Vehicle Trips per Household HBW HBO NHB Average Daily Person Trips per Household Average Daily Vehicle Trips per Household HBW HBO NHB In an urban area with MSA of 500,000 999,999 Income Low 1.24 7.18 4.26 11.50 60.16 28.34 7.71 3.28 4.50 74.42 21.08 Medium 1.93 8.89 5.69 15.57 55.32 29.11 9.24 5.48 5.64 62.33 32.03 High 2.39 12.71 8.47 14.05 50.54 35.41 11.46 6.34 4.07 68.99 26.95 Weighted Avg. 1.83 9.24 5.95 13.89 54.46 31.65 9.20 5.03 4.59 67.73 27.67 Household Size 1 1.04 3.93 3.17 15.80 49.24 34.96 3.03 2.32 8.20 62.49 29.30 2 1.87 7.56 5.60 16.39 51.22 32.39 7.96 4.92 4.12 66.05 29.83 3 2.24 11.01 7.15 15.04 53.04 31.92 12.29 7.50 4.22 60.60 35.17 4 2.24 15.27 8.57 12.50 56.34 31.16 14.36 6.51 4.32 73.71 21.98 5+ 2.68 18.13 9.73 10.60 59.82 29.58 18.68 7.21 4.88 72.79 22.33 Weighted Avg. 1.83 9.24 5.95 13.89 54.46 31.65 9.20 5.03 4.59 67.73 27.67 In an urban area with MSA of 1,000,000 2,999,999 Income Low 1.18 6.48 3.61 13.07 59.07 27.86 6.26 3.37 4.40 67.31 28.28 Medium 1.81 8.85 5.75 16.50 54.21 29.29 9.41 5.51 5.66 61.20 33.14 High 2.43 12.84 8.30 15.45 52.64 31.92 11.89 6.65 4.47 65.62 29.91 Weighted Avg. 1.84 9.40 6.00 15.25 54.34 30.41 9.30 5.29 4.92 64.31 30.77 Household Size 1 1.03 4.18 3.19 15.88 50.02 34.11 3.95 3.17 4.14 66.94 28.92 2 1.94 7.79 5.96 18.29 48.93 32.78 7.50 4.79 4.64 63.00 32.36 3 2.24 11.39 7.24 17.27 52.24 30.49 10.76 6.32 6.04 65.10 28.86 4 2.35 15.39 8.56 12.66 58.94 28.40 15.37 7.85 4.87 64.04 31.09 5+ 2.41 18.70 9.01 11.19 61.40 27.42 19.40 7.87 4.79 64.60 30.61 Weighted Avg. 1.84 9.40 6.00 15.25 54.34 30.41 9.30 5.29 4.92 64.31 30.77

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Table 4.15 Continued Weekdays Weekends % Average Daily Person Trips % Average Daily Person Trips Average Autos per Household Average Daily Person Trips per Household Average Daily Vehicle Trips per Household HBW HBO NHB Average Daily Person Trips per Household Average Daily Vehicle Trips per Household HBW HBO NHB In an urban area with MSA of 3 million or more Income Low 1.01 6.72 3.04 13.62 60.70 25.68 6.75 2.91 4.48 68.52 27.00 Medium 1.62 8.87 5.29 14.94 55.50 29.56 8.68 4.56 4.64 65.28 30.08 High 2.19 11.68 7.01 14.89 53.99 31.12 11.23 5.87 4.06 66.74 29.20 Weighted Avg. 1.69 9.28 5.40 14.69 55.78 29.53 8.92 4.57 4.37 66.54 29.09 Household Size 1 0.87 4.04 2.65 15.92 47.18 36.91 3.69 2.34 3.65 61.86 34.49 2 1.75 7.40 5.21 17.15 49.93 32.93 6.91 4.35 4.12 63.04 32.84 3 2.04 10.71 6.62 17.47 51.87 30.67 10.12 5.67 4.81 65.14 30.05 4 2.13 14.40 7.65 13.00 59.92 27.07 13.21 6.18 4.92 66.82 28.27 5+ 2.33 18.10 8.15 11.11 64.04 24.84 17.49 6.85 3.97 71.34 24.69 Weighted Avg. 1.69 9.28 5.40 14.69 55.78 29.53 8.92 4.57 4.37 66.54 29.09 In an urban area but not in a MSA Income Low 1.29 6.61 3.84 10.32 59.20 30.47 7.07 3.09 5.06 66.81 28.13 Medium 2.18 10.84 7.24 15.19 55.02 29.80 9.79 5.40 5.10 61.36 33.54 High 2.68 12.18 8.14 16.43 50.62 32.95 11.02 6.39 4.72 60.72 34.56 Weighted Avg. 1.92 9.25 5.97 14.19 55.10 30.71 8.76 4.67 4.89 62.98 32.13 Household Size 1 1.00 3.73 2.95 12.78 52.37 34.84 3.46 2.52 6.75 64.05 29.20 2 2.04 8.14 6.10 15.37 52.64 31.99 7.25 4.79 5.75 63.07 31.18 3 2.49 11.58 7.92 16.59 52.90 30.51 9.92 5.52 5.01 61.64 33.35 4 2.58 15.34 8.43 13.21 56.53 30.26 15.12 6.11 3.44 65.03 31.53 5+ 2.48 19.06 8.86 11.79 60.59 27.62 17.96 7.28 4.55 61.58 33.87 Weighted Avg. 1.92 9.25 5.97 14.19 55.10 30.71 8.76 4.67 4.89 62.98 32.13

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65 Table 4.16 Distribution of Person Trip s by Purpose, Size and Income Weekdays Weekends HBW HBShop HBSoc HBOther NHB HBW HBShop HBSoc HBOther NHB Income Low 10.81 16.61 10.30 34.08 28. 21 4.57 21.44 16.49 30.37 27.13 Medium 14.59 13.46 11.75 29.84 30.36 4.63 19.43 17.16 27.38 31.39 High 14.90 10.80 13.21 28.63 32. 46 4.05 18.75 20.77 26.44 30.00 All (%) 14.02 12.78 12.30 30.00 30. 91 4.32 19.54 18.86 27.40 29.88 Household Size HBW HBShop HBSoc HBOther NHB HBW HBShop HBSoc HBOther NHB 1 14.55 16.04 12.99 21.60 34.82 4.17 21.17 17.47 26.08 31.12 2 16.05 15.66 13.36 22.14 32.79 4.18 21.03 19.34 24.33 31.13 3 16.12 12.13 10.84 29.07 31.84 4.86 19.90 17.36 27.27 30.61 4+ 11.42 10.16 12.01 38.26 28. 15 4.21 17.97 19.50 29.91 28.41 All (%) 14.02 12.78 12.30 30.00 30. 91 4.32 19.54 18.86 27.40 29.88

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66 CHAPTER 5 DIFFERENCES IN TRIP LENGTH AND DURATION 5.1 Introduction A trip is associated with the distance th e vehicle (including pub lic transit) travels along with the time taken to cover that distance. The trip may take a longer duration than it would have taken to cover the same dist ance in some other area possibly because of change in the mode that is being taken in the trip, or the segment traversed being a noncongested or lesser congested one the purpose of the trip or ev en the gender of the driver. Not only are the person trip characteristics important in defining how much travel is being desired by each person also is the vehicle trip characteristics for how much household vehicle is being driven defining the collective participation of persons from the same or different households to vanpool or car pool. The present discussion explores some of these distinctions in trips length s and duration that occurs on weekdays and weekends. The section assumes all the trip lengths to be reported in miles and the trip duration in minutes. All the trips that were made by persons belonging to urban households were included however those whic h involved greater trip lengths to exceed 75 miles were discarded from the original 2001 NHTS dataset.

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67 5.2 Distribution of Trip Lengths Table 5.1 through 5.4 gives the distribution of person and vehicle trips by trip length and trip purpose for each urban size. Alon g with the total perc entages, the average trip lengths (in miles) and dur ation (minutes) are also given. On an average, a trip takes about 14.5 to 19.5 minutes with a average di stance of 5.75 to 6.77 miles on weekdays as compared to 16.5 to 19.8 minutes for traveling 6.85 to 7.80 miles on an average on weekends. This implies that person travel fo r longer duration and distance on weekends. On weekdays, about 60% of the home-based wo rk trips are greater than 5 miles. The percent of home-based work trips increases with the urban size implying work locations being shifted to the outskirts of more densely populated area s. On weekends, percent of trips greater than 5 miles reduces to some 52%. All other purpose trips show lengthier trips being made on weekends as compared to that on weekdays. People utilize the weekend or the non-working day to fulfill activi ties that were inaccessible due to the time constraint on weekdays or the working da ys. Tables 5.3 and 5.4 reveal that speeds increase only slightly on weekends averagi ng about 27 to 28 mph. More than 65% of the home-based work trips made on privately ow ned vehicles on weekdays are more than 5 miles as compared to 55% on weekends. Ther e may be a possibility that on weekends, people are generating some extra income through some nearby part time jobs that require frequent traveling. Figure 5.1 to 5.2 show s trip lengths dist ribution for HBW and HBShop purposes respectively for ur ban areas irrespective of size.

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68 Table 5.1 Person Trip Length Distribution by Urban Size and Purpose on Weekdays Purpose Trip Length HBW HBShop HBSoc HBOther NHB Total In an urban area with MSA of less than 250,000 1 mile or Less 14.36 26.73 26.11 31.78 28.60 27.06 1 mile to 2 miles 12.90 17.98 16.51 16.49 16.86 16.30 2 miles to 3 miles 13.53 13.79 12.74 11.33 10.48 11.83 3 miles to 4 miles 7.39 8.83 9.01 7.74 7.11 7.77 4 miles to 5 miles 9.84 7.92 10.15 7.18 8.45 8.39 5 miles to 10 miles 31.14 18.72 20.28 20.17 20.85 21.74 10 miles to 25 miles 6.19 2.51 3.29 3.11 3.82 3.71 More than 25 miles 4.66 3.53 1.91 2.20 3.83 3.19 Total % 100.00 100.00 100.00 100.00 100.00 100.00 Average Trip Length 7.65 5.50 5.07 5.00 5.98 5.75 Average Trip Duration 15.77 13.70 15.40 13.81 15.63 14.84 In an urban area with MSA of 250,000 499,999 1 mile or Less 11.85 28.15 32.42 29.69 27.57 26.67 1 mile to 2 miles 8.23 16.33 12.44 14.71 12.68 13.14 2 miles to 3 miles 12.07 13.52 9.88 12.76 10.36 11.69 3 miles to 4 miles 5.40 9.98 5.21 6.45 7.14 6.84 4 miles to 5 miles 7.20 6.31 9.02 8.82 8.28 8.12 5 miles to 10 miles 37.28 20.87 23.32 21.37 24.85 24.8 10 miles to 25 miles 10.93 3.10 4.71 3.35 4.58 4.90 More than 25 miles 7.03 1.74 3.01 2.85 4.54 3.83 Total % 100.00 100.00 100.00 100.00 100.00 100.00 Average Trip Length 9.49 4.85 5.64 5.44 6.40 6.24 Average Trip Duration 18.49 13.18 17.12 15.40 15.63 15.80 In an urban area with MSA of 500,000 999,999 1 mile or Less 10.08 27.93 28.54 29.04 26.75 25.49 1 mile to 2 miles 8.85 14.44 12.83 12.03 14.85 12.87 2 miles to 3 miles 8.38 12.09 9.87 10.73 9.64 10.12 3 miles to 4 miles 4.79 9.04 8.80 6.13 6.77 6.82 4 miles to 5 miles 9.64 5.46 9.81 8.60 8.59 8.51 5 miles to 10 miles 38.84 25.36 25.02 26.75 25.87 27.77 10 miles to 25 miles 12.51 2.94 3.28 4.79 4.85 5.47 More than 25 miles 6.90 2.74 1.85 1.92 2.68 2.94 Total % 100.00 100.00 100.00 100.00 100.00 100.00 Average Trip Length 10.03 5.46 5.26 5.65 6.07 6.32 Average Trip Duration 21.15 15.09 17.07 15.64 15.20 16.37

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69 Table 5.1 Continued Purpose Trip Length HBW HBShop HBSoc HBOther NHB Total In an urban area with MSA of 1,000,000 2,999,999 1 mile or Less 9.25 28.20 33.27 29.64 28.69 26.51 1 mile to 2 miles 7.27 17.41 13.44 13.88 11.91 12.67 2 miles to 3 miles 8.38 13.08 11.06 11.54 10.04 10.74 3 miles to 4 miles 5.38 6.96 7.01 6.74 6.44 6.50 4 miles to 5 miles 7.42 8.78 7.56 6.47 6.90 7.18 5 miles to 10 miles 40.48 21.30 21.35 23.53 25.42 26.13 10 miles to 25 miles 14.99 2.90 3.78 5.00 6.32 6.50 More than 25 miles 6.83 1.37 2.54 3.21 4.28 3.77 Total % 100.00 100.00 100.00 100.00 100.00 100.00 Average Trip Length 10.76 4.65 5.23 6.01 6.85 6.72 Average Trip Duration 23.42 13.44 17.88 16.65 16.64 17.41 In an urban area with MSA of 3 million or more 1 mile or Less 9.43 36.42 35.55 34.69 32.82 30.80 1 mile to 2 miles 7.69 15.59 12.85 14.76 12.47 12.92 2 miles to 3 miles 6.83 9.75 10.32 9.20 8.81 8.95 3 miles to 4 miles 5.67 7.27 7.02 6.57 5.93 6.40 4 miles to 5 miles 6.78 6.17 7.26 6.08 6.92 6.59 5 miles to 10 miles 34.79 19.62 19.72 20.58 21.52 22.69 10 miles to 25 miles 16.41 3.46 4.25 4.99 6.29 6.75 More than 25 miles 12.38 1.72 3.03 3.13 5.23 4.90 Total % 100.00 100.00 100.00 100.00 100.00 100.00 Average Trip Length 12.66 4.58 5.33 5.47 6.76 6.77 Average Trip Duration 29.86 14.40 19.23 17.59 18.28 19.42 In an urban area but not in a MSA 1 mile or Less 20.49 34.43 38.39 38.15 37.03 34.86 1 mile to 2 miles 16.30 17.57 16.92 15.81 16.55 16.45 2 miles to 3 miles 8.47 10.30 10.77 9.00 8.42 9.11 3 miles to 4 miles 6.54 7.11 4.98 5.48 5.48 5.77 4 miles to 5 miles 5.54 6.11 3.99 6.73 5.49 5.78 5 miles to 10 miles 23.32 15.99 15.08 16.93 16.43 17.35 10 miles to 25 miles 8.05 4.55 3.62 3.38 4.60 4.59 More than 25 miles 11.30 3.94 6.24 4.53 6.00 6.07 Total % 100.00 100.00 100.00 100.00 100.00 100.00 Average Trip Length 9.76 5.49 6.16 5.56 6.35 6.47 Average Trip Duration 17.72 13.59 16.60 14.40 14.34 15.02

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70 Table 5.2 Person Trip Length Distribution by Urban Size and Purpose on Weekends Purpose Trip Length HBW HBShop HBSoc HBOther NHB Total In an urban area with MSA of less than 250,000 1 mile or Less 16.26 30.13 26.36 23.18 30.88 26.92 1 mile to 2 miles 16.44 19.55 15.20 13.56 10.75 14.26 2 miles to 3 miles 11.46 13.23 10.04 13.50 10.90 11.90 3 miles to 4 miles 3.58 3.54 5.14 9.07 6.53 6.27 4 miles to 5 miles 11.79 10.63 9.65 8.38 7.54 8.97 5 miles to 10 miles 27.58 18.95 23.09 21.64 22.81 22.13 10 miles to 25 miles 9.56 2.01 4.07 6.04 3.78 4.48 More than 25 miles 3.33 1.96 6.45 4.64 6.79 5.08 Total % 100.00 100.00 100.00 100.00 100.00 100.00 Average Trip Length 7.19 4.45 7.36 7.24 7.52 6.85 Average Trip Duration 16.58 11.31 21.55 17.45 16.73 16.90 In an urban area with MSA of 250,000 499,999 1 mile or Less 9.90 33.78 23.13 27.97 25.31 26.61 1 mile to 2 miles 8.20 13.23 8.16 9.10 13.25 11.07 2 miles to 3 miles 13.07 12.97 15.19 10.61 11.32 12.18 3 miles to 4 miles 9.50 10.69 6.98 4.94 4.47 6.49 4 miles to 5 miles 5.64 8.17 9.23 11.19 8.59 9.16 5 miles to 10 miles 42.14 16.68 26.22 21.32 24.99 23.38 10 miles to 25 miles 6.07 2.88 4.09 6.96 6.27 5.41 More than 25 miles 5.48 1.59 7.00 7.91 5.82 5.70 Total % 100.00 100.00 100.00 100.00 100.00 100.00 Average Trip Length 8.48 4.50 8.11 7.99 7.51 7.18 Average Trip Duration 17.29 13.24 20.72 17.80 18.87 17.71 In an urban area with MSA of 500,000 999,999 1 mile or Less 16.65 23.46 21.64 26.61 25.76 24.38 1 mile to 2 miles 7.61 15.85 12.92 10.85 13.42 12.83 2 miles to 3 miles 6.32 9.67 12.30 9.47 9.72 9.94 3 miles to 4 miles 11.08 9.51 8.42 6.76 9.45 8.57 4 miles to 5 miles 7.91 9.19 8.62 12.62 5.91 9.13 5 miles to 10 miles 30.76 24.74 23.16 25.18 25.92 25.18 10 miles to 25 miles 13.68 5.40 7.14 3.00 4.58 5.15 More than 25 miles 5.99 2.17 5.80 5.51 5.23 4.80 Total % 100.00 100.00 100.00 100.00 100.00 100.00 Average Trip Length 8.99 5.98 7.59 6.69 6.88 6.86 Average Trip Duration 18.29 15.17 19.22 15.98 16.89 16.75

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71 Table 5.2 Continued Purpose Trip Length HBW HBShop HBSoc HBOther NHB Total In an urban area with MSA of 1,000,000 2,999,999 1 mile or Less 10.13 26.52 25.41 24.85 27.19 25.25 1 mile to 2 miles 10.05 15.07 9.72 13.97 11.45 12.42 2 miles to 3 miles 6.75 13.86 10.38 8.38 8.53 9.71 3 miles to 4 miles 7.11 8.39 9.12 6.70 8.00 7.87 4 miles to 5 miles 11.99 7.90 6.91 7.93 6.97 7.64 5 miles to 10 miles 33.46 22.49 25.47 26.85 26.42 26.00 10 miles to 25 miles 12.97 3.86 9.66 6.85 6.82 7.11 More than 25 miles 7.54 1.90 3.32 4.47 4.63 3.99 Total % 100.00 100.00 100.00 100.00 100.00 100.00 Average Trip Length 10.04 5.05 7.15 7.16 7.21 6.93 Average Trip Duration 19.54 13.16 18.59 16.43 16.95 16.54 In an urban area with MSA of 3 million or more 1 mile or Less 17.05 30.44 28.92 26.91 30.03 28.51 1 mile to 2 miles 6.45 13.43 11.35 13.84 12.05 12.43 2 miles to 3 miles 7.83 10.54 8.83 8.26 7.90 8.71 3 miles to 4 miles 7.16 7.94 5.47 5.33 6.86 6.41 4 miles to 5 miles 8.13 7.42 8.58 6.58 7.80 7.57 5 miles to 10 miles 29.58 21.91 23.72 23.54 23.61 23.52 10 miles to 25 miles 11.38 3.07 6.12 7.35 5.94 6.00 More than 25 miles 12.41 5.24 7.00 8.19 5.81 6.84 Total % 100.00 100.00 100.00 100.00 100.00 100.00 Average Trip Length 11.45 6.14 7.76 8.38 7.23 7.60 Average Trip Duration 25.80 16.35 21.22 21.10 19.02 19.76 In an urban area but not in a MSA 1 mile or Less 18.06 30.23 27.58 36.11 31.17 31.17 1 mile to 2 miles 20.18 16.34 15.38 14.76 12.11 14.56 2 miles to 3 miles 15.68 9.67 14.79 9.65 10.18 10.98 3 miles to 4 miles 1.92 5.58 4.03 5.47 5.74 5.16 4 miles to 5 miles 5.47 5.64 5.76 6.08 5.38 5.69 5 miles to 10 miles 22.53 16.36 20.69 16.98 18.76 18.33 10 miles to 25 miles 5.43 5.09 7.70 5.54 6.56 6.14 More than 25 miles 10.72 11.10 4.07 5.41 10.10 7.97 Total % 100.00 100.00 100.00 100.00 100.00 100.00 Average Trip Length 9.09 9.33 6.65 6.50 8.51 7.80 Average Trip Duration 16.86 16.54 16.77 14.69 18.2 16.6

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72 Table 5.3 Vehicle Trip Length Distribution by Urban Size and Purpose on Weekdays Purpose Trip Length HBW HBShop HBSoc HBOther NHB Total Average Trip Length Average Trip Duration In an urban area with MSA of less than 250,000 1 mile or Less 11.17 24.21 17.32 21.98 27.04 21.38 0.75 6.02 1 mile to 2 miles 12.65 18.63 17.24 17.71 16.32 16.32 1.98 8.73 2 miles to 3 miles 14.59 14.69 15.64 12.74 11.81 13.31 3.00 10.55 3 miles to 4 miles 7.61 9.83 8.63 9.84 7.13 8.39 4.00 12.55 4 miles to 5 miles 10.06 8.00 11.98 8.13 8.09 8.82 5.00 13.53 5 miles to 10 miles 32.08 18.91 25.70 23.32 22.03 24.27 9.08 18.07 10 miles to 25 miles 6.67 2.76 1.94 3.17 3.73 3.89 20.35 30.45 More than 25 miles 5.17 2.97 1.55 3.11 3.86 3.61 43.67 53.47 Total % 100.00 100.00 100.00 100.00 100.00 100.00 6.23 13.84 Average Trip Length 8.08 5.44 5.27 5.91 5.94 6.23 Average Trip Duration 15.75 13.11 13.12 13.29 14.18 14.04 In an urban area with MSA of 250,000 499,999 1 mile or Less 10.41 24.63 17.96 21.81 22.16 19.70 0.75 5.55 1 mile to 2 miles 8.48 18.67 14.38 15.09 13.65 13.70 1.98 8.38 2 miles to 3 miles 12.14 13.26 10.01 14.18 11.74 12.50 3.00 10.68 3 miles to 4 miles 5.36 10.19 7.81 6.84 8.12 7.49 3.99 12.84 4 miles to 5 miles 7.08 6.80 8.69 10.01 8.65 8.44 5.00 13.80 5 miles to 10 miles 37.79 21.18 31.06 24.23 25.36 27.47 9.13 19.53 10 miles to 25 miles 11.13 3.59 7.03 4.48 5.44 6.22 20.26 30.58 More than 25 miles 7.60 1.67 3.06 3.37 4.88 4.47 40.04 51.13 Total % 100.00 100.00 100.00 100.00 100.00 100.00 7.08 15.18 Average Trip Length 9.82 5.05 6.83 6.22 6.94 7.08 Average Trip Duration 18.64 12.72 15.81 14.50 14.59 15.23 In an urban area with MSA of 500,000 999,999 1 mile or Less 7.28 26.45 16.31 22.53 23.30 19.79 0.71 5.88 1 mile to 2 miles 8.71 14.82 15.27 12.96 15.02 13.28 1.99 8.78 2 miles to 3 miles 7.73 14.10 11.01 11.38 10.12 10.56 3.00 10.84 3 miles to 4 miles 4.65 9.67 9.91 6.87 6.76 7.03 4.00 13.82 4 miles to 5 miles 9.50 5.94 9.37 8.53 8.43 8.43 5.00 14.42 5 miles to 10 miles 40.79 23.48 30.64 30.36 28.43 30.87 9.44 20.04 10 miles to 25 miles 13.47 3.24 5.26 5.15 5.30 6.57 20.20 31.32 More than 25 miles 7.88 2.31 2.23 2.21 2.64 3.47 39.43 49.08 Total % 100.00 100.00 100.00 100.00 100.00 100.00 7.03 15.54 Average Trip Length 10.74 5.37 6.41 6.17 6.35 7.03 Average Trip Duration 20.71 13.68 14.62 15.18 14.58 15.81

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73 Table 5.3 Continued Purpose Trip Length HBW HBShop HBSoc HBOther NHB Total Average Trip Length Average Trip Duration In an urban area with MSA of 1,000,000 2,999,999 1 mile or Less 6.64 26.59 17.86 20.93 23.99 19.41 0.75 5.96 1 mile to 2 miles 6.91 19.06 15.06 15.37 12.20 13.05 1.98 8.99 2 miles to 3 miles 8.59 14.02 12.90 12.20 10.77 11.29 3.00 11.45 3 miles to 4 miles 5.35 7.26 8.43 7.71 6.76 6.90 4.00 13.03 4 miles to 5 miles 7.66 7.96 10.03 7.56 7.08 7.69 5.00 14.06 5 miles to 10 miles 41.44 20.92 28.06 26.74 27.29 29.33 9.74 21.15 10 miles to 25 miles 16.18 2.94 4.46 5.92 7.09 7.94 20.04 33.05 More than 25 miles 7.24 1.26 3.20 3.56 4.82 4.39 39.29 52.42 Total % 100.00 100.00 100.00 100.00 100.00 100.00 7.57 16.67 Average Trip Length 11.20 4.63 6.47 6.69 7.41 7.57 Average Trip Duration 22.26 12.61 15.22 15.69 16.23 16.79 In an urban area with MSA of 3 million or more 1 mile or Less 6.24 29.61 20.23 25.03 24.26 21.10 0.76 6.53 1 mile to 2 miles 7.11 17.55 14.80 14.45 13.66 13.13 1.97 9.05 2 miles to 3 miles 6.90 10.80 13.35 9.97 9.50 9.61 3.00 11.10 3 miles to 4 miles 5.38 8.72 8.45 7.67 6.76 7.12 4.00 13.61 4 miles to 5 miles 6.06 6.67 8.70 7.39 7.76 7.26 5.00 14.79 5 miles to 10 miles 37.33 21.28 25.55 25.19 24.71 27.05 9.64 22.46 10 miles to 25 miles 17.59 3.60 5.16 6.34 7.48 8.55 20.39 36.22 More than 25 miles 13.40 1.75 3.77 3.96 5.86 6.20 38.81 57.63 Total % 100.00 100.00 100.00 100.00 100.00 100.00 8.11 18.35 Average Trip Length 13.42 4.89 6.58 6.58 7.67 8.11 Average Trip Duration 27.50 13.37 15.97 16.06 17.71 18.58 In an urban area but not in a MSA 1 mile or Less 18.94 33.91 26.94 31.39 33.16 29.33 0.74 5.56 1 mile to 2 miles 16.67 17.74 19.44 17.10 17.78 17.52 1.97 8.30 2 miles to 3 miles 8.81 11.08 12.43 11.17 9.61 10.28 3.00 9.77 3 miles to 4 miles 6.57 7.39 6.89 6.12 5.83 6.36 3.99 11.36 4 miles to 5 miles 5.88 6.37 4.90 6.22 6.08 6.01 5.00 12.97 5 miles to 10 miles 22.94 15.29 18.42 18.53 16.85 18.46 9.50 17.72 10 miles to 25 miles 8.51 4.08 3.95 3.68 4.67 5.07 20.47 31.24 More than 25 miles 11.70 4.15 7.04 5.78 6.02 6.97 40.80 52.38 Total % 100.00 100.00 100.00 100.00 100.00 100.00 7.06 14.01 Average Trip Length 9.94 5.50 6.94 6.37 6.43 7.06 Average Trip Duration 17.40 12.85 15.14 13.15 13.34 14.22

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74 Table 5.4 Vehicle Trip Length Distribution by Urban Size and Purpose on Weekends Purpose Trip Length HBW HBShop HBSoc HBOther NHB Total Average Trip Length Average Trip Duration In an urban area with MSA of less than 250,000 1 mile or Less 16.18 28.14 19.21 20.29 27.54 23.48 0.78 5.84 1 mile to 2 miles 12.18 22.66 15.62 16.74 11.30 15.86 1.97 8.17 2 miles to 3 miles 11.62 13.51 13.51 14.36 12.19 13.19 2.99 9.75 3 miles to 4 miles 4.10 2.77 7.63 9.32 8.57 6.99 3.99 22.93 4 miles to 5 miles 13.12 9.92 8.63 9.34 7.48 9.17 5.00 13.13 5 miles to 10 miles 29.17 20.49 26.98 20.89 23.57 23.24 9.32 19.25 10 miles to 25 miles 9.82 1.76 2.89 4.48 3.87 3.98 19.56 29.15 More than 25 miles 3.82 0.76 5.53 4.59 5.48 4.10 45.47 53.48 Total % 100.00 100.00 100.00 100.00 100.00 100.00 6.43 14.50 Average Trip Length 7.53 4.10 7.18 6.89 7.01 6.43 Average Trip Duration 15.68 10.88 18.59 14.87 14.25 14.48 In an urban area with MSA of 250,000 499,999 1 mile or Less 8.38 27.82 18.48 17.74 23.13 20.88 0.71 5.45 1 mile to 2 miles 6.37 16.43 8.58 12.29 13.07 12.39 2.00 8.91 2 miles to 3 miles 12.78 11.90 17.47 12.25 11.85 12.86 3.00 10.28 3 miles to 4 miles 9.50 9.62 6.52 7.39 6.35 7.59 4.00 12.31 4 miles to 5 miles 6.85 9.88 9.52 12.00 9.90 10.14 5.00 17.57 5 miles to 10 miles 43.36 19.37 26.33 25.69 25.60 25.81 9.14 18.43 10 miles to 25 miles 7.37 3.71 5.37 7.29 4.61 5.44 20.38 31.72 More than 25 miles 5.39 1.29 7.75 5.35 5.49 4.88 42.48 55.59 Total % 100.00 100.00 100.00 100.00 100.00 100.00 7.13 15.46 Average Trip Length 8.75 4.76 8.73 7.51 7.28 7.13 Average Trip Duration 17.53 12.16 17.83 15.99 16.19 15.63 In an urban area with MSA of 500,000 999,999 1 mile or Less 16.27 23.06 12.89 18.97 23.82 20.19 0.77 5.70 1 mile to 2 miles 7.62 18.79 10.83 12.10 12.97 13.36 2.00 9.15 2 miles to 3 miles 7.65 12.49 13.83 11.06 9.67 11.15 3.00 10.52 3 miles to 4 miles 11.96 8.60 11.55 8.36 9.14 9.35 4.00 13.25 4 miles to 5 miles 3.15 9.29 8.18 13.37 6.23 8.96 5.00 14.89 5 miles to 10 miles 34.68 22.09 27.07 24.86 27.15 25.90 9.47 19.08 10 miles to 25 miles 13.18 3.64 8.18 4.11 5.34 5.58 20.44 31.48 More than 25 miles 5.49 2.04 7.48 7.17 5.68 5.51 40.08 51.55 Total % 100.00 100.00 100.00 100.00 100.00 100.00 7.38 15.63 Average Trip Length 9.14 5.51 9.25 7.65 7.23 7.38 Average Trip Duration 18.28 13.34 20.35 15.70 15.57 16.01

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75 Table 5.4 Continued Purpose Trip Length HBW HBShop HBSoc HBOther NHB Total Average Trip Length Average Trip Duration In an urban area with MSA of 1,000,000 2,999,999 1 mile or Less 7.64 25.79 17.74 18.90 25.71 21.39 0.75 5.50 1 mile to 2 miles 8.46 17.54 10.53 14.94 12.64 13.67 1.98 8.40 2 miles to 3 miles 6.71 13.86 12.00 10.30 8.87 10.61 3.00 10.86 3 miles to 4 miles 7.45 8.59 9.72 6.77 7.58 7.89 4.00 12.72 4 miles to 5 miles 12.42 8.08 8.01 8.46 7.12 8.21 5.00 14.50 5 miles to 10 miles 35.41 21.51 29.12 29.26 27.02 27.38 9.40 20.08 10 miles to 25 miles 13.09 3.42 9.43 7.39 6.74 7.07 20.32 30.84 More than 25 miles 8.82 1.21 3.46 3.98 4.33 3.78 39.44 52.46 Total % 100.00 100.00 100.00 100.00 100.00 100.00 6.98 15.25 Average Trip Length 10.66 4.69 7.73 7.29 7.03 6.98 Average Trip Duration 19.82 12.15 16.70 15.25 16.10 15.40 In an urban area with MSA of 3 million or more 1 mile or Less 10.62 27.86 19.43 18.78 25.30 22.31 0.75 6.40 1 mile to 2 miles 5.56 15.38 12.37 14.73 13.55 13.57 1.96 9.40 2 miles to 3 miles 8.20 11.12 10.18 9.93 8.99 9.86 3.00 11.77 3 miles to 4 miles 6.45 8.53 5.29 5.80 6.95 6.73 4.00 13.70 4 miles to 5 miles 9.64 8.50 9.91 6.85 7.58 8.11 5.00 14.41 5 miles to 10 miles 30.57 21.43 27.46 27.43 24.65 25.46 9.51 20.96 10 miles to 25 miles 14.25 2.95 7.19 8.26 6.83 6.85 20.15 33.81 More than 25 miles 14.71 4.23 8.17 8.22 6.14 7.12 40.61 54.50 Total % 100.00 100.00 100.00 100.00 100.00 100.00 8.10 17.40 Average Trip Length 12.82 5.72 8.82 8.94 7.77 8.10 Average Trip Duration 23.12 14.24 18.59 19.67 17.71 17.91 In an urban area but not in a MSA 1 mile or Less 17.51 30.65 21.57 29.80 29.82 27.92 0.74 5.77 1 mile to 2 miles 18.26 18.86 16.03 17.37 13.44 16.45 1.98 8.31 2 miles to 3 miles 17.20 11.49 17.35 11.89 10.97 12.68 3.00 11.09 3 miles to 4 miles 2.29 5.80 5.59 4.58 6.27 5.29 4.00 12.15 4 miles to 5 miles 3.00 6.11 4.26 7.59 5.17 5.75 5.00 18.10 5 miles to 10 miles 22.93 15.88 21.77 17.78 18.40 18.49 9.45 18.33 10 miles to 25 miles 6.02 3.91 8.73 5.73 6.25 5.90 20.52 30.45 More than 25 miles 12.78 7.29 4.70 5.26 9.68 7.55 42.77 52.96 Total % 100.00 100.00 100.00 100.00 100.00 100.00 7.59 15.13 Average Trip Length 9.95 7.05 7.31 6.72 8.30 7.59 Average Trip Duration 16.76 13.45 15.35 13.76 17.27 15.17

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Figure 5.1 Trip Length Distribution for Home Based Work (HBW) Trips 024681012141612345678910111213141516171819202122232425262728293031323334353637383940414243444546Trip Length (miles)Percent of Total Trips Weekdays Weekends

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Figure 5.2 Trip Length Distribution for Home Based Shop (HBShop) Trips 0510152025303512345678910111213141516171819202122232425262728293031323334353637383940414243444546Trip Length (miles)Percent of Total Trips Weekdays Weekends

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78 5.3 Total Travel Per Household and Per Person Vehicle miles traveled (VMT) denotes th e distance (in miles) traveled by the vehicle. The vehicle may have more than one occupant but since only one vehicle is been driven; only one vehicle is accounted in calcula ting the distance traveled. However, since each person traveled the same distance, the person miles traveled can be obtained by aggregating the miles of each occupant on th e trip. Table 5.5 gives the total vehicles miles traveled per day by all the househol d members of a household. The overall miles traveled on weekends tend to be some 510 miles per household lesser than that on weekdays. The household may not be utilizing all the vehicles on weekends, as it would have done so on weekdays. This is clearly illustrated by the individual vehicle miles being driven by purpose. Week end vehicle miles traveled for the home based work are about 30% of those on weekdays but all othe r purposes home based trips were more on weekends for most of the urban sizes. Table 5.5 Average Daily VMT Per Hous ehold by Urban Size and Purpose HBW HBShop HBSoc HBOther NHB All In an urban area with MSA of less than 250,000 weekdays 9.87 4.52 2.94 9.51 12.57 39.47 weekends 3.27 4.16 5.34 8.86 9.27 30.90 In an urban area with MSA of 250,000 499,999 weekdays 11.47 4.08 3.35 9.38 13.38 41.65 weekends 2.96 4.66 5.72 9.18 9.98 32.52 In an urban area with MSA of 500,000 999,999 weekdays 11.78 3.92 3.26 9.02 12.69 40.78 weekends 3.00 6.27 6.43 10.40 9.95 36.10 In an urban area with MSA of 1,000,000 2,999,999 weekdays 13.61 3.96 3.28 9.34 13.87 44.10 weekends 3.98 5.35 6.13 9.99 10.80 36.40 In an urban area with MSA of 3 million or more weekdays 14.00 3.43 3.23 8.64 12.86 42.30 weekends 3.69 5.85 6.09 10.28 9.87 35.81 In an urban area but not in a MSA weekdays 11.32 4.44 3.72 9.29 12.17 40.96 weekends 3.87 6.69 4.49 8.76 11.39 35.20

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79 Table 5.6 gives the total miles traveled per person on a day. Every person belonging to urban household travels a distance of about 28 miles on an average every day. Almost in every urban size, traveling done by almost every person for every non-work trip is more on weekends as compared to that on weekdays. Table 5.6 Average Daily PMT Per Person by Urban Size and Purpose HBW HBShop HBSoc HBOther NHB All In an urban area with MSA of less than 250,000 weekdays 4.80 3.07 2.67 6.83 8.74 26.18 weekends 1.59 3.09 5.53 7.92 8.82 26.92 In an urban area with MSA of 250,000 499,999 weekdays 5.44 2.64 2.62 7.00 8.37 26.13 weekends 1.57 3.50 5.21 8.41 9.66 28.61 In an urban area with MSA of 500,000 999,999 weekdays 5.68 2.69 2.55 7.09 7.95 26.09 weekends 1.62 5.06 5.45 7.84 7.67 27.70 In an urban area with MSA of 1,000,000 2,999,999 weekdays 6.74 2.48 2.66 7.22 8.61 27.88 weekends 1.99 3.69 5.26 8.03 8.91 27.98 In an urban area with MSA of 3 million or more weekdays 7.27 2.26 2.61 6.73 7.91 26.99 weekends 1.77 4.55 5.62 8.16 7.67 27.89 In an urban area but not in a MSA weekdays 5.82 2.82 3.02 7.29 8.16 27.24 weekends 1.69 6.27 4.18 7.06 10.34 29.65 Table 5.7 gives the corresponding time spent on traveling for different purposes by individual on weekday and weekend. The pers on spent about the one-fourth to one-third time on weekends for the home based work trip s as compared to that spent on weekends. As pointed out earlier, some persons may be commuting to shorter distances for some another work quite different from that th ey have to do on weekdays. Thus, weekdays work differs from that on weekends. An av erage person spends about one third of the time and distance in traveli ng between non-home locations.

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80 Table 5.7 Average Daily PTT Per Person by Urban Size and Purpose HBW HBShop HBSoc HBOther NHB All In an urban area with MSA of less than 250,000 weekdays 9.87 7.66 8.07 18.75 22.91 67.40 weekends 3.83 7.81 16.26 18.77 19.72 66.16 In an urban area with MSA of 250,000 499,999 weekdays 10.57 7.15 7.89 19.63 20.24 65.52 weekends 3.20 10.23 13.22 18.91 24.26 69.87 In an urban area with MSA of 500,000 999,999 weekdays 12.02 7.48 8.14 19.41 19.87 67.01 weekends 3.39 12.75 13.98 18.77 19.03 68.06 In an urban area with MSA of 1,000,000 2,999,999 weekdays 14.66 7.17 8.99 19.85 20.83 71.45 weekends 3.85 9.64 13.70 18.19 21.02 66.24 In an urban area with MSA of 3 million or more weekdays 17.31 6.97 9.41 21.44 21.36 76.45 weekends 3.98 12.00 15.40 20.36 20.16 72.18 In an urban area but not in a MSA weekdays 10.55 6.95 8.08 18.61 18.40 62.76 weekends 3.12 10.99 10.46 15.81 21.87 62.25 5.4 Gender Differences Table 5.8 and 5.9 gives the comparison of the total person miles and vehicle miles traveled by person based on urban size and ge nder. Although, females travel lesser on a weekday than males but on weekends their total travel (in terms of person miles) becomes almost equal to males. Although tota l vehicle miles in case of driver being male decreases slightly, the females driver m iles tend to show a large drop as compared to the males, possibly due to being a passenger mostly on weekends. Combining the results from the previous ch apter of this report, female s may be making more trips on weekdays than males but their total travel is lesser than males possibly due to much shorter trips than males.

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81 Table 5.8 Average Daily PMT Per Person by Urban Size and Gender Weekdays Weekends Male Female All Male Female All In an urban area with MSA of less than 250,000 27.82 24.67 26.18 27.63 26.23 26.92 In an urban area with MSA of 250,000 499,999 28.13 24.27 26.13 31.37 25.98 28.61 In an urban area with MSA of 500,000 999,999 27.75 24.55 26.09 29.69 25.99 27.70 In an urban area with MSA of 1,000,000 2,999,999 30.47 25.38 27.88 28.46 27.52 27.98 In an urban area with MSA of 3 million or more 29.83 24.27 26.99 29.60 26.28 27.89 In an urban area but not in a MSA 30.36 24.28 27.24 30.29 29.02 29.65 Table 5.9 Average Daily VMT Per Person by Urban Size and Gender Weekdays Weekends Male Female All Male Female All In an urban area with MSA of less than 250,000 20.84 14.84 17.72 16.23 11.31 13.75 In an urban area with MSA of 250,000 499,999 21.36 15.16 18.13 18.06 9.80 13.83 In an urban area with MSA of 500,000 999,999 20.42 15.72 17.98 21.20 10.69 15.54 In an urban area with MSA of 1,000,000 2,999,999 23.49 15.55 19.43 18.79 11.84 15.28 In an urban area with MSA of 3 million or more 21.27 14.21 17.67 18.54 10.15 14.21 In an urban area but not in a MSA 22.75 14.54 18.54 17.61 11.27 14.43 5.5 Modal Differences Tables 5.10 through 5.13 give the weekda y and weekend comparisons of trip distance and duration by mode and trip purpos e. Urban areas havi ng a population of 3 million or more has been split into two categ ories one without heavy transit and one with heavy transit. Single Occupant Vehicle (S OV) refers to vehicle used in trips with

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82 only one person in the trip and Higher Occupant Vehicle (HOV) refers to vehicle used in trips with more than one persons. These m odes along with heavy transit showing two Table 5.10 Average Trip Length by Purpos e, Mode and Urban Size on Weekdays Purpose HBW HBShop HBSoc HBOther NHB All In an urban area with MSA of less than 250,000 SOV 8.03 4.34 4.57 5.93 5.83 6.17 HOV 7.56 7.00 6.55 5.44 6.66 6.29 All 7.65 5.50 5.07 5.00 5.98 5.75 In an urban area with MSA of 250,000 499,999 SOV 9.93 4.68 6.26 6.31 6.93 7.31 HOV 7.97 5.61 7.34 5.99 6.61 6.37 All 9.49 4.85 5.64 5.44 6.40 6.24 In an urban area with MSA of 500,000 999,999 SOV 10.81 4.23 6.02 6.62 6.30 7.30 HOV 7.53 7.14 6.31 5.95 6.44 6.37 All 10.03 5.46 5.26 5.65 6.07 6.32 In an urban area with MSA of 1,000,000 2,999,999 SOV 11.10 4.27 6.10 6.63 7.51 7.78 HOV 10.95 5.65 6.91 6.89 7.04 6.96 All 10.76 4.65 5.23 6.01 6.85 6.72 In an urban area with MSA of 3 million or more w/o heavy transit SOV 13.72 4.52 6.40 6.98 8.02 8.77 HOV 13.59 6.40 7.42 6.53 7.52 7.23 All 13.49 5.07 5.65 5.80 7.25 7.18 In an urban area with MSA of 3 million or more w/ heavy transit SOV 12.58 4.24 5.36 6.73 7.36 8.19 HOV 13.55 5.43 7.42 5.76 7.40 6.82 Bus and Light Rail 7.32 5.53 7.48 5.63 7.70 6.51 Metro, Subway and Heavy Rail 10.45 7.07 6.44 7.64 7.81 8.92 All 11.89 4.06 5.01 5.13 6.26 6.34 In an urban area but not in a MSA SOV 9.60 4.58 5.90 6.07 6.02 6.81 HOV 12.60 6.90 8.20 6.36 7.15 7.20 All 9.76 5.49 6.16 5.56 6.35 6.47

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83 Table 5.11 Average Trip Length by Purpose, Mode and Urban Size on Weekends Purpose HBW HBShop HBSoc HBOther NHB All In an urban area with MSA of less than 250,000 SOV 6.83 3.37 4.39 6.41 5.11 5.16 HOV 9.25 5.64 9.75 8.18 8.80 8.34 All 7.19 4.45 7.36 7.24 7.52 6.85 In an urban area with MSA of 250,000 499,999 SOV 8.45 3.96 6.03 6.73 5.89 6.02 HOV 10.27 5.21 9.52 9.66 8.59 8.40 All 8.48 4.50 8.11 7.99 7.51 7.18 In an urban area with MSA of 500,000 999,999 SOV 9.11 4.30 10.05 7.59 6.95 7.16 HOV 9.01 7.02 8.23 7.06 7.03 7.29 All 8.99 5.98 7.59 6.69 6.88 6.86 In an urban area with MSA of 1,000,000 2,999,999 SOV 10.92 3.88 6.06 6.38 5.85 6.17 HOV 8.40 6.24 8.94 8.43 8.19 8.08 All 10.04 5.05 7.15 7.16 7.21 6.93 In an urban area with MSA of 3 million or more w/o heavy transit SOV 11.29 4.11 7.18 7.48 5.69 6.60 HOV 12.54 7.83 9.71 9.70 8.41 8.94 All 10.73 6.18 7.83 7.99 7.35 7.52 In an urban area with MSA of 3 million or more w/ heavy transit SOV 13.90 4.03 6.74 8.03 7.17 7.36 HOV 16.75 8.77 10.01 10.63 7.97 9.35 Bus and Light Rail 5.63 5.50 4.96 6.57 5.45 5.76 Metro, Subway and Heavy Rail 7.52 4.84 6.91 8.22 8.38 7.64 All 12.10 6.10 7.70 8.76 7.12 7.68 In an urban area but not in a MSA SOV 9.43 4.46 6.69 6.17 6.84 6.39 HOV 9.55 13.00 8.10 7.67 9.49 9.31 All 9.09 9.33 6.65 6.50 8.51 7.80

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84 Table 5.12 Average Trip Duration by Purpose, Mode and Urban Size on Weekdays Purpose HBW HBShop HBSoc HBOther NHB All In an urban area with MSA of less than 250,000 SOV 15.70 11.85 11.88 13.33 14.26 13.98 HOV 17.16 15.48 14.36 13.51 14.95 14.50 All 15.77 13.70 15.40 13.81 15.63 14.84 In an urban area with MSA of 250,000 499,999 SOV 18.73 12.14 14.54 14.60 14.27 15.33 HOV 17.29 13.66 16.94 14.36 14.74 14.80 All 18.49 13.18 17.12 15.40 15.63 15.80 In an urban area with MSA of 500,000 999,999 SOV 20.75 12.34 13.97 15.26 14.67 16.08 HOV 18.37 17.09 16.59 14.98 15.06 15.62 All 21.15 15.09 17.07 15.64 15.20 16.37 In an urban area with MSA of 1,000,000 2,999,999 SOV 22.06 12.17 14.06 15.65 16.39 17.07 HOV 27.12 14.06 17.07 15.80 16.42 16.47 All 23.42 13.44 17.88 16.65 16.64 17.41 In an urban area with MSA of 3 million or more w/o heavy transit SOV 26.20 12.64 14.83 15.55 17.00 18.46 HOV 26.88 14.60 17.26 16.03 17.51 16.92 All 27.80 14.45 18.75 16.72 17.58 18.49 In an urban area with MSA of 3 million or more w/ heavy transit SOV 27.97 12.93 14.57 17.02 17.96 19.77 HOV 31.08 14.82 18.12 16.35 18.47 17.81 Bus and Light Rail 50.55 46.67 62.66 49.32 54.15 50.99 Metro, Subway and Heavy Rail 53.98 33.93 53.19 48.61 42.04 49.58 All 31.70 14.35 19.71 18.46 19.00 20.35 In an urban area but not in a MSA SOV 17.07 11.64 13.63 12.47 12.44 13.71 HOV 21.00 14.99 16.43 14.30 15.43 15.34 All 17.72 13.59 16.60 14.40 14.34 15.02

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85 Table 5.13 Average Trip Duration by Purpose, Mode and Urban Size on Weekends Purpose HBW HBShop HBSoc HBOther NHB All In an urban area with MSA of less than 250,000 SOV 14.44 9.67 11.50 13.75 11.80 12.12 HOV 24.45 12.96 23.58 18.07 16.86 18.13 All 16.58 11.31 21.55 17.45 16.73 16.90 In an urban area with MSA of 250,000 499,999 SOV 17.23 11.04 14.55 15.84 15.69 14.69 HOV 18.07 14.64 20.32 18.55 17.71 17.82 All 17.29 13.24 20.72 17.80 18.87 17.71 In an urban area with MSA of 500,000 999,999 SOV 18.39 10.86 20.37 15.55 13.98 15.08 HOV 18.01 17.27 18.38 15.30 16.99 16.85 All 18.29 15.17 19.22 15.98 16.89 16.75 In an urban area with MSA of 1,000,000 2,999,999 SOV 20.18 10.58 14.23 14.67 13.96 14.14 HOV 16.90 14.95 18.41 16.93 17.33 17.02 All 19.54 13.16 18.59 16.43 16.95 16.54 In an urban area with MSA of 3 million or more w/o heavy transit SOV 19.88 11.33 14.98 16.58 14.37 14.89 HOV 23.79 18.47 19.45 18.85 18.39 18.80 All 22.68 15.92 19.65 17.92 18.23 18.15 In an urban area with MSA of 3 million or more w/ heavy transit SOV 25.73 12.52 16.43 18.92 16.94 17.34 HOV 32.11 18.55 22.19 24.01 19.03 21.09 Bus and Light Rail 50.98 46.61 53.82 63.17 46.00 52.66 Metro, Subway and Heavy Rail 66.32 45.81 53.23 91.93 54.42 65.09 All 28.62 16.77 22.73 24.10 19.77 21.28 In an urban area but not in a MSA SOV 16.06 9.70 14.31 13.30 13.25 12.87 HOV 19.94 21.15 15.68 14.94 18.93 17.60 All 16.86 16.54 16.77 14.69 18.20 16.60 additional modes Bus and light rail; and me tro, subway and heavy rail are compared in urban area with population of 3 million or mo re. On weekdays, with single occupant on the vehicle, the vehicle is driven for longer distance as compared to when the vehicle is driven with more than one occupant, po ssibly because of occupants being having different work destinations in the former case. On weekdays the trips lengths of homebased work trips on HOV is lesser than that on SOV in almost all urban areas whereas

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86 when it comes to shopping and social recreati on activities, more pe rsons are driven on HOV so that the demand for the travel for each of them would be sati sfied such as going to bigger marts. On weekends, lengthier trip lengths, over 9 miles per trip, in an urban area with 3 million or more population and re inforced with heavy transit, on HOV are observed possibly due to more availability of more number of household persons on a non-working day. The similar trend is observed for trip duration too except for one urban area. On weekends, the urban area of size 3 million or more and having heavy transit shows an increase in trip time although the tr ip distance reduces as compared to that on weekdays with all the effect coming from the transit trip. This is understandable due to lesser transit frequency on weekends. On weekdays even between the transit modes, the group that consist of metro, subway and heavy rails takes almost 50 minutes the same as that of the other group consisting of bus a nd light rail. However, on weekends, bus and light rail seems to take slightly more time 52 minutes as compared to the metro group that totals about 65 minutes for a trip. 5.6 Effect of Income Table 5.14 and 5.15 shows the cross-classifi cation of trip duration with purpose and household income categories on weekdays and weekends. Household income has a mixed effect on the travel patterns on weekdays and weekends. On a weekday, an average trip made by high income household takes more time than the trip on weekend. A trip taken by low-income household generally takes more time on weekends than it did on weekdays probably because of lower vehi cle ownership making them to make less frequent but a le ngthier trip.

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87 Table 5.14 Average Travel Duration by Household Income, Urban Size and Trip Purpose on Weekdays Income HBW HBShop HBSoc HBOther NHB Total In an urban area with MSA of less than 250,000 Low 15.24 15.13 15.48 15.36 16.11 15.56 Medium 15.03 12.36 15.17 13.29 15.75 14.47 High 16.51 14.58 15.78 12.95 15.26 14.85 Weighted Average 15.77 13.70 15.40 13.81 15.63 14.84 In an urban area with MSA of 250,000 499,999 Low 17.91 14.46 22.29 15.80 15.34 16.19 Medium 17.99 12.94 14.97 13.80 14.63 14.65 High 19.54 11.86 16.94 16.89 16.62 16.71 Weighted Average 18.49 13.18 17.12 15.40 15.63 15.80 In an urban area with MSA of 500,000 999,999 Low 19.32 14.51 17.99 16.49 15.92 16.48 Medium 21.14 16.39 18.84 15.78 16.23 17.21 High 22.30 14.20 14.90 14.89 14.05 15.56 Weighted Average 21.15 15.09 17.07 15.64 15.20 16.37 In an urban area with MSA of 1,000,000 2,999,999 Low 26.57 15.85 20.33 20.08 19.48 20.12 Medium 23.27 12.82 17.05 16.12 16.69 17.11 High 22.85 12.97 17.90 15.51 15.87 16.79 Weighted Average 23.42 13.44 17.88 16.65 16.64 17.41 In an urban area with MSA of 3 million or more Low 30.95 14.85 26.47 20.74 20.96 21.78 Medium 27.79 14.73 19.22 17.82 18.40 19.24 High 30.38 13.08 17.77 15.99 17.73 18.63 Weighted Average 29.86 14.40 19.23 17.59 18.28 19.42 In an urban area but not in a MSA Low 17.89 15.99 16.53 17.09 14.95 16.32 Medium 17.57 12.30 16.48 13.43 13.80 14.40 High 17.87 12.90 16.55 12.85 14.69 14.73 Weighted Average 17.72 13.59 16.60 14.40 14.34 15.02

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88 Table 5.15 Average Travel Duration by Household Income, Urban Size and Trip Purpose on Weekends Income HBW HBShop HBSoc HBOther NHB Total In an urban area with MSA of less than 250,000 Low 18.48 10.99 15.41 24.11 16.25 17.77 Medium 15.75 10.57 19.78 15.29 18.36 16.14 High 15.78 12.53 24.94 16.20 14.01 16.89 Weighted Average 16.58 11.31 21.55 17.45 16.73 16.90 In an urban area with MSA of 250,000 499,999 Low 18.95 16.18 24.43 24.67 18.97 20.89 Medium 13.86 12.99 19.42 16.75 18.21 16.74 High 19.23 11.13 19.45 13.70 17.55 15.71 Weighted Average 17.29 13.24 20.72 17.80 18.87 17.71 In an urban area with MSA of 500,000 999,999 Low 16.60 17.30 20.67 14.69 17.94 17.37 Medium 18.93 14.61 20.21 16.36 16.97 16.96 High 18.14 13.65 17.16 16.08 16.15 15.93 Weighted Average 18.29 15.17 19.22 15.98 16.89 16.75 In an urban area with MSA of 1,000,000 2,999,999 Low 22.68 15.27 20.59 19.97 17.26 18.43 Medium 17.84 12.71 17.90 16.80 17.36 16.58 High 20.18 12.83 18.75 15.03 16.87 16.16 Weighted Average 19.54 13.16 18.59 16.43 16.95 16.54 In an urban area with MSA of 3 million or more Low 25.40 20.42 24.05 26.34 18.53 22.52 Medium 29.05 15.15 24.64 21.64 19.21 20.42 High 23.57 14.86 18.97 18.60 18.90 18.26 Weighted Average 25.80 16.35 21.22 21.10 19.02 19.76 In an urban area but not in a MSA Low 18.01 22.00 20.07 15.79 16.27 17.85 Medium 17.57 14.74 15.98 14.52 17.99 16.14 High 14.74 14.74 15.47 12.40 18.70 15.61 Weighted Average 16.86 16.54 16.77 14.69 18.20 16.60

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89 CHAPTER 6 MODAL COMPARISON 6.1 Introduction This chapter focuses on travel distinctions on weekdays and weekends by the mode that was used. The discussion here is subjected to seven majo r classifications of mode auto, transit, non-motorized travel, motorcycle, school bus, taxicab and all others. The auto mode is further classified into tw o more categories the SOV (single occupant vehicle) and the HOV (higher occupant vehicle) The term SOV refers to the trip being made with only one person on the personal vehicle as compared to the HOV where more than one person is supposed to be present on the vehicle. The pers onal vehicle includes all modes: car, van, sport-utility vehicle (S UV), pickup truck, other truck or recreational vehicle (RV). Further, the trips that specified only one person on the trip and the person was not a driver are considered in HOV cat egory assuming some non-household member acted as driver on the trip. Tran sit is categorized into three types. First group that includes bus and light rail consists of local public transit bus, commuter bus, charter/tour bus, city to city bus, streetcar/trolley and passenger line/ferry. Second group includes metro, subway and elevated (heavy) rail while the third group includes commuter rail consisting of commuter and Amtrak/intercity trains. Nonmotorized travel is divided into walking and bicycling. All othe r modes that included motorcycle, commercial or charter airplane,

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90 private or corporate airplane, school bus, ship or cruise, sailboat, motorboat or yacht, taxicab, limousine, hotel or airport shuttle a nd other modes. The discussion is not limited to modes only but stretches to different urba n area size groups too. There are seven urban area sizes that have been defi ned here. Apart from the generally five categories, the urban area size of 3 million or more is divided into two categories, one without heavy rail and one with it. 6.2 Distribution of Person Trips Table 6.1 and 6.2 gives the percent distribut ion of person trips made on weekdays and weekends. On weekdays, almost 85-90% trips are made on auto in almost all urban areas except the one with the heavy transit wh ere the decrease of about 10% is shared by the transit and the non-motorized modes. The auto share increases on weekends by almost 2-3% with a whopping 7.5% increase in urban areas with heavy transit. HOV takes almost the same share as the SOV but on weekends, more than twice the trips made on SOV are made on HOV. The share of wa lking trips is maximum (11.53%) in urban areas with population of 3 million or more a nd heavy transit. The share of walking trips decreases from weekdays to weekends alt hough the share of other non-motorized mode remains almost the same. Almost 50% of the trips made on HOV are for social recreational purposes as compared to 65% of the trips on weekends. Shopping is preferred on SOV more as compared to the social recreational trip s which are preferred on HOV.

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91 Table 6.1 Percent Person Trips by Mode and Urban size and Purpose on Weekdays HBW HBShop HBSoc HBOther NHB Total In an urban area with MSA of less than 250,000 Auto 94.83 94.87 81.70 84.37 91.01 88.95 SOV 85.57 43.67 27.76 31.69 43.46 43.98 HOV 9.26 51.20 53.94 52.68 47.55 44.97 Transit 0.98 0.08 0.15 0.76 0.32 0.49 Bus and Light Rail 0.98 0.08 0.15 0.76 0.32 0.49 Metro, Subway and Heavy Rail N/A N/A N/A N/A N/A N/A Commuter Rail N/A N/A N/A N/A N/A N/A Non-Motorized Travel 3.63 5.02 17.46 10.87 6.04 8.35 Walk 3.33 4.95 13.79 10.37 5.71 7.62 Bicycle 0.30 0.06 3.67 0.49 0.34 0.73 Motorcycle 0.54 0.03 0.06 N/A 0.26 0.17 School Bus N/A N/A N/A 3.78 1.75 1.69 Taxicab 0.03 N/A N/A 0.10 0.19 0.09 All Other N/A N/A 0.62 0.12 0.43 0.25 In an urban area with MSA of 250,000 499,999 Auto 97.19 91.26 75.21 83.15 90.22 87.46 SOV 85.20 40.53 25.60 28.23 42.83 41.91 HOV 11.99 50.73 49.61 54.91 47.39 45.55 Transit 0.92 1.74 1.19 0.68 1.60 1.20 Bus and Light Rail 0.92 1.74 1.10 0.67 1.39 1.12 Metro, Subway and Heavy Rail N/A N/A 0.08 0.01 0.21 0.08 Commuter Rail N/A N/A N/A N/A N/A N/A Non-Motorized Travel 1.77 6.25 20.95 10.36 6.46 8.61 Walk 1.66 6.25 18.22 9.36 6.17 7.89 Bicycle 0.11 N/A 2.74 1.00 0.29 0.72 Motorcycle 0.06 0.38 0.08 0.22 0.09 0.16 School Bus 0.02 N/A N/A 5.30 1.08 1.97 Taxicab N/A N/A N/A N/A 0.09 0.03 All Other 0.04 0.37 2.56 0.30 0.46 0.57 In an urban area with MSA of 500,000 999,999 Auto 94.41 93.07 79.46 85.21 92.62 89.10 SOV 81.97 43.49 25.54 28.73 43.57 42.20 HOV 12.44 49.58 53.91 56.48 49.05 46.90 Transit 1.93 0.79 0.70 0.99 0.57 0.93 Bus and Light Rail 1.93 0.79 0.70 0.99 0.56 0.93 Metro, Subway and Heavy Rail N/A N/A N/A N/A N/A N/A Commuter Rail N/A N/A N/A N/A 0.01 0.00 Non-Motorized Travel 3.11 6.11 19.40 8.14 5.48 7.69 Walk 2.25 5.98 15.22 7.59 5.26 6.82 Bicycle 0.86 0.13 4.19 0.55 0.22 0.87 Motorcycle 0.34 0.04 N/A 0.02 0.06 0.08 School Bus 0.19 N/A N/A 4.99 1.01 1.87 Taxicab 0.02 N/A N/A 0.24 0.04 0.09 All Other N/A N/A 0.44 0.39 0.22 0.24 N/A implies insufficient data

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92 Table 6.1 Continued HBW HBShop HBSoc HBOther NHB Total In an urban area with MSA of 1,000,000 2,999,999 Auto 93.85 92.39 73.11 81.67 90.35 86.50 SOV 80.96 48.69 24.89 29.87 44.35 43.87 HOV 12.89 43.69 48.22 51.80 46.00 42.63 Transit 2.87 1.44 0.82 1.27 1.02 1.40 Bus and Light Rail 2.74 1.32 0.81 1.25 0.90 1.33 Metro, Subway and Heavy Rail 0.02 0.12 0.01 0.01 0.10 0.05 Commuter Rail 0.11 N/A N/A N/A 0.02 0.02 Non-Motorized Travel 2.91 5.80 24.56 11.22 7.07 9.63 Walk 2.42 5.47 20.73 10.44 6.78 8.73 Bicycle 0.49 0.33 3.83 0.78 0.29 0.91 Motorcycle 0.22 0.21 0.18 0.12 0.10 0.15 School Bus 0.05 N/A N/A 5.50 1.19 1.97 Taxicab 0.05 0.02 0.05 0.04 0.16 0.08 All Other 0.05 0.14 1.28 0.19 0.11 0.27 In an urban area with MSA of 3 million or more w/o heavy transit Auto 91.17 88.80 75.53 80.46 88.96 84.95 SOV 77.81 40.93 24.44 26.32 41.67 39.70 HOV 13.37 47.88 51.09 54.14 47.29 45.25 Transit 5.19 1.30 0.47 1.42 1.24 1.76 Bus and Light Rail 3.51 1.30 0.32 1.29 0.78 1.33 Metro, Subway and Heavy Rail 0.31 N/A 0.11 0.12 0.28 0.18 Commuter Rail 1.37 N/A 0.03 0.01 0.19 0.25 Non-Motorized Travel 2.95 9.40 22.48 12.38 7.90 10.60 Walk 2.07 8.94 19.59 11.38 7.62 9.66 Bicycle 0.88 0.46 2.89 1.01 0.28 0.93 Motorcycle 0.52 0.02 0.02 0.15 0.07 0.14 School Bus 0.02 0.01 0.01 5.19 1.16 1.96 Taxicab 0.03 0.34 0.05 0.08 0.33 0.18 All Other 0.12 0.13 1.45 0.32 0.33 0.41 In an urban area with MSA of 3 million or more w/ heavy transit Auto 79.24 76.84 65.54 71.96 75.65 73.94 SOV 66.34 38.48 20.21 23.12 37.01 35.31 HOV 12.90 38.35 45.33 48.84 38.65 38.63 Transit 14.93 3.94 2.90 6.33 4.79 6.49 Bus and Light Rail 6.32 2.82 1.45 4.73 2.24 3.61 Metro, Subway and Heavy Rail 6.72 1.13 1.37 1.43 1.90 2.34 Commuter Rail 1.88 N/A 0.07 0.18 0.65 0.54 Non-Motorized Travel 5.15 18.49 29.72 15.63 17.67 16.71 Walk 4.75 17.91 26.55 15.07 16.95 15.80 Bicycle 0.40 0.58 3.17 0.56 0.72 0.91 Motorcycle 0.14 N/A 0.15 0.06 0.04 0.07 School Bus 0.04 0.07 0.18 5.32 1.05 1.99 Taxicab 0.33 0.13 0.43 0.39 0.56 0.40 All Other 0.18 0.52 1.08 0.31 0.24 0.39 N/A implies insufficient data

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93 Table 6.1 Continued HBW HBShop HBSoc HBOther NHB Total In an urban area but not in a MSA Auto 97.29 93.53 79.63 81.02 92.02 88.08 SOV 84.33 47.41 27.82 30.03 42.57 43.45 HOV 12.96 46.13 51.81 51.00 49.45 44.63 Transit 0.30 0.26 0.20 0.41 0.13 0.26 Bus and Light Rail 0.30 0.26 0.14 0.39 0.12 0.25 Metro, Subway and Heavy Rail N/A N/A N/A N/A N/A N/A Commuter Rail N/A N/A 0.06 0.02 0.00 0.01 Non-Motorized Travel 2.00 5.28 18.90 10.88 6.04 8.38 Walk 1.91 5.14 15.86 10.06 5.62 7.61 Bicycle 0.09 0.14 3.03 0.82 0.42 0.77 Motorcycle 0.29 0.51 0.30 0.07 0.08 0.19 School Bus N/A N/A 0.01 7.34 1.19 2.66 Taxicab N/A 0.36 0.21 0.15 0.25 0.19 All Other 0.11 0.05 0.75 0.13 0.30 0.24 N/A implies insufficient data

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94 Table 6.2 Percent Person Trips by Mode and Urban Size and Purpose on Weekends HBW HBShop HBSoc HBOther NHB Total In an urban area with MSA of less than 250,000 Auto 97.23 94.95 82.89 92.04 93.39 91.50 SOV 74.96 41.58 17.79 26.91 21.72 28.97 HOV 22.27 53.37 65.10 65.13 71.67 62.53 Transit 0.00 0.00 0.00 0.00 0.00 0.00 Bus and Light Rail N/A N/A N/A N/A N/A N/A Metro, Subway and Heavy Rail N/A N/A N/A N/A N/A N/A Commuter Rail N/A N/A N/A N/A N/A N/A Non-Motorized Travel 2.77 4.85 15.61 7.32 6.07 7.84 Walk 1.89 4.73 12.18 6.40 5.55 6.70 Bicycle 0.88 0.12 3.43 0.92 0.51 1.14 Motorcycle N/A N/A 0.13 0.09 0.18 0.10 School Bus N/A N/A N/A 0.08 0.08 0.05 Taxicab N/A N/A N/A 0.18 N/A 0.05 All Other N/A 0.20 1.38 0.29 0.29 0.47 In an urban area with MSA of 250,000 499,999 Auto 96.34 92.76 84.65 89.08 92.04 90.40 SOV 78.58 31.97 18.04 25.29 18.76 25.81 HOV 17.77 60.79 66.61 63.79 73.28 64.58 Transit 0.00 0.47 0.26 0.41 0.36 0.36 Bus and Light Rail N/A 0.47 0.26 0.41 0.36 0.36 Metro, Subway and Heavy Rail N/A N/A N/A N/A N/A N/A Commuter Rail N/A N/A N/A N/A N/A N/A Non-Motorized Travel 3.66 6.78 12.66 9.83 7.11 8.51 Walk 3.66 5.47 11.84 8.62 6.14 7.48 Bicycle N/A 1.31 0.82 1.22 0.97 1.03 Motorcycle N/A N/A 2.27 0.11 0.07 0.42 School Bus N/A N/ A N/A N/A N/A N/A Taxicab N/A N/A N/A 0.09 0.29 0.12 All Other N/A N/A 0.16 0.47 0.13 0.19 In an urban area with MSA of 500,000 999,999 Auto 98.93 96.06 85.78 91.00 96.61 93.03 SOV 72.73 30.64 19.02 28.29 21.45 27.26 HOV 26.20 65.42 66.76 62.72 75.16 65.77 Transit 0.00 0.89 0.88 0.12 0.18 0.43 Bus and Light Rail N/A 0.89 0.88 0.12 0.18 0.43 Metro, Subway and Heavy Rail N/A N/A N/A N/A N/A N/A Commuter Rail N/A N/A N/A N/A N/A N/A Non-Motorized Travel 1.07 2.77 12.28 8.27 3.06 6.08 Walk 1.07 1.87 11.21 7.52 2.32 5.28 Bicycle N/A 0.90 1.07 0.74 0.74 0.80 Motorcycle N/A 0.10 0.11 0.16 0.12 0.12 School Bus N/A N/ A N/A 0.11 N/A 0.03 Taxicab N/A 0.18 0.13 N/A N/A 0.06 All Other N/A N/A 0.83 0.33 0.04 0.26 N/A implies insufficient data

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95 Table 6.2 Continued HBW HBShop HBSoc HBOther NHB Total In an urban area with MSA of 1,000,000 2,999,999 Auto 95.81 94.97 81.93 89.82 92.93 90.55 SOV 74.64 39.09 19.08 27.88 23.39 29.19 HOV 21.17 55.88 62.85 61.95 69.54 61.36 Transit 1.35 0.40 1.56 0.98 1.03 1.02 Bus and Light Rail 1.35 0.40 1.56 0.94 1.03 1.01 Metro, Subway and Heavy Rail N/A N/A N/A 0.04 N/A 0.01 Commuter Rail N/A N/A N/A N/A N/A N/A Non-Motorized Travel 2.84 4.50 15.41 9.01 5.51 7.99 Walk 2.84 4.21 12.35 8.51 5.02 7.09 Bicycle N/A 0.28 3.06 0.50 0.48 0.90 Motorcycle N/A 0.02 0.11 0.07 0.05 0.06 School Bus N/A N/ A N/A N/A 0.02 0.01 Taxicab N/A N/A 0.03 N/A 0.20 0.07 All Other N/A 0.11 0.96 0.11 0.26 0.31 In an urban area with MSA of 3 million or more w/o heavy transit Auto 86.52 93.64 81.81 87.20 90.71 88.41 SOV 72.67 32.89 14.71 25.01 19.96 25.07 HOV 13.85 60.75 67.10 62.19 70.76 63.34 Transit 5.10 0.52 0.51 0.94 0.84 0.92 Bus and Light Rail 5.10 0.52 0.45 0.85 0.70 0.84 Metro, Subway and Heavy Rail N/A N/A 0.05 0.04 0.10 0.05 Commuter Rail N/A N/A N/A 0.05 0.04 0.03 Non-Motorized Travel 5.68 5.37 17.06 10.53 7.35 9.67 Walk 5.53 5.31 14.25 9.83 7.10 8.83 Bicycle 0.14 0.06 2.81 0.70 0.25 0.84 Motorcycle 1.58 0.17 0.20 0.34 0.25 0.30 School Bus N/A N/A 0.02 N/A 0.05 0.02 Taxicab N/A N/A N/A 0.07 0.08 0.04 All Other 1.13 0.30 0.41 0.92 0.72 0.64 In an urban area with MSA of 3 million or more w/ heavy transit Auto 75.56 82.75 76.58 83.11 83.44 81.50 SOV 65.75 30.42 14.45 22.94 19.82 23.80 HOV 9.81 52.33 62.13 60.17 63.62 57.70 Transit 15.29 4.38 4.11 4.62 3.12 4.52 Bus and Light Rail 7.25 3.97 1.56 2.93 1.68 2.70 Metro, Subway and Heavy Rail 5.16 0.38 2.55 1.62 1.44 1.66 Commuter Rail 2.88 0.03 N/A 0.07 N/A 0.15 Non-Motorized Travel 8.02 12.14 18.30 11.04 10.96 12.53 Walk 5.47 11.87 16.16 9.95 10.51 11.53 Bicycle 2.55 0.27 2.14 1.08 0.45 1.01 Motorcycle N/A N/A 0.03 0.12 0.01 0.04 School Bus N/A N/ A N/A N/A 0.15 0.04 Taxicab 1.13 0.36 0.54 1.00 1.55 0.94 All Other N/A 0.37 0.45 0.12 0.78 0.42 N/A implies insufficient data

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96 Table 6.2 Continued HBW HBShop HBSoc HBOther NHB Total In an urban area but not in a MSA Auto 95.12 95.98 80.65 88.54 91.15 89.72 SOV 77.72 37.91 16.38 24.31 17.15 25.72 HOV 17.40 58.08 64.27 64.23 74.00 64.00 Transit 0.00 0.03 0.00 0.19 0.81 0.32 Bus and Light Rail N/A 0.03 N/A N/A 0.29 0.10 Metro, Subway and Heavy Rail N/A N/A N/A N/A 0.12 0.04 Commuter Rail N/A N/A N/A 0.19 0.40 0.18 Non-Motorized Travel 4.53 3.38 18.06 11.05 6.94 9.21 Walk 4.53 2.71 16.50 10.05 6.58 8.43 Bicycle N/A 0.67 1.56 1.00 0.36 0.78 Motorcycle 0.35 0.10 0.68 N/A 0.11 0.18 School Bus N/A N/ A N/A N/A N/A N/A Taxicab N/A 0.51 0.28 0.14 0.85 0.45 All Other N/A N/A 0.32 0.09 0.15 0.13 N/A implies insufficient data 6.3 Distribution of Trips by Mode and Trip Length Table 6.3 and 6.4 gives the distribution of trip lengths by each mode on weekdays and weekends. About 40% of the trips made on weekdays are 2 miles or less. On weekends, in about every urban size, there is a slight (1%) decrease in this shorter trips share. In urban area with 3 million or more population and with heavy transit, this share of shorter trips, i.e. less than 2 miles, decrease from 46% by about 5%. Share of SOV trips made for shorter distances increase on weekends as compared to the weekdays. Compared to weekdays, there is an increase of an about 9% in HOV trips of more than 5 miles in some of the areas on weekends. Walk trips become longer than 1 miles for most of the areas on weekends except the urban areas with more than 3 million population where the percent of trips with 1 mile or less increase by almost 4% from 88% on weekdays. The distribution of bicycle trips is dependent on the urban size. There are some areas where the percent of shorter bicycl e trips generally increase on weekends but there are others where the percentage of trip s less than 1 miles decrease. Urban areas with

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97 3 million and more and with heavy transit can be used to compare the behavior of different public transit on weekdays and w eekends. On weekdays, 50% of the trips made on bus and light rail for a distance of 2-10 m iles whereas this increases by about 23% on weekends. Metro, Subway and Heavy Rail which constituted about mere 21.84% trips of 3-5 miles on weekdays constitute about 51.32% on weekends, i.e. more than twice of the weekdays.

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98 Table 6.3 Trips by Mode, Urban Size and Length on Weekdays Trip Length (Miles) -> Mode (0-1] (1-2] (2-3] (3-4] (4-5] (510] (1025] 25+ Row% Mode Share Avg. Trip Length In an urban area with MSA of less than 250,000 SOV 21.07 16.48 13.81 8.42 8.34 24.48 4.07 3.33 100% 43.98 6.17 HOV 22.72 16.40 11.82 8.26 10.01 22.97 4.09 3.73 100% 44.97 6.29 Walk 85.06 12.66 1.01 1.00 0.06 0.20 N/A N/A 100% 7.62 0.76 Bicycle 58.23 10.92 11.79 13.03 N/A 3.90 2.12 N/A 100% 0.73 2.01 Total 27.06 16.30 11.83 7.77 8.39 21.74 3.71 3.19 100% 2.70 5.75 In an urban area with MSA of 250,000 499,999 SOV 19.47 12.99 12.04 7.66 8.09 28.46 6.75 4.56 100% 41.91 7.31 HOV 21.52 14.59 13.06 7.38 9.66 25.28 4.47 4.06 100% 45.55 6.37 Walk 89.40 5.56 2.21 1.42 0.10 1.31 N/A N/A 100% 7.89 0.76 Bicycle 81.24 2.42 6.42 1.39 2.08 5.86 N/A 0.59 100% 0.72 1.57 Total 26.67 13.14 11.69 6.84 8.12 24.80 4.90 3.83 100% 3.93 6.24 In an urban area with MSA of 500,000 999,999 SOV 18.85 13.11 10.47 6.39 8.33 31.53 7.64 3.68 100% 42.20 7.30 HOV 21.48 13.65 11.02 8.07 9.83 28.59 4.54 2.82 100% 46.88 6.37 Walk 90.90 5.37 1.24 0.35 0.51 1.54 N/A 0.09 100% 6.82 0.70 Bicycle 56.76 14.68 5.35 7.46 8.40 7.35 N/A N/A 100% 0.87 2.21 Total 25.48 12.87 10.12 6.81 8.55 27.76 5.47 2.94 100% 3.23 6.32 In an urban area with MSA of 1,000,000 2,999,999 SOV 18.63 12.96 10.85 6.77 7.56 30.14 8.60 4.49 100% 43.87 7.78 HOV 21.71 12.97 12.33 7.31 8.18 27.67 5.92 3.91 100% 42.63 6.96 Walk 88.02 7.80 2.20 0.87 0.42 0.63 0.05 N/A 100% 8.73 0.73 Bicycle 69.60 19.24 1.75 0.91 1.82 5.52 1.05 0.11 100% 0.90 1.72 Total 26.51 12.69 10.74 6.50 7.18 26.12 6.50 3.77 100% 3.87 6.72 In an urban area with MSA of 3 million or more w/o heavy transit SOV 19.03 13.06 9.19 6.75 7.60 27.31 9.87 7.20 100% 39.69 8.77 HOV 23.05 15.07 9.47 8.11 7.83 24.68 6.84 4.95 100% 45.24 7.23 Walk 88.56 8.16 1.76 0.76 0.10 0.57 0.02 0.06 100% 9.68 0.72 Bicycle 70.83 11.92 10.93 0.60 1.67 4.04 N/A N/A 100% 0.93 1.42 Total 28.02 13.54 8.75 6.84 7.04 23.05 7.38 5.37 100% 4.45 7.18 In an urban area with MSA of 3 million or more w/ heavy transit SOV 20.75 12.38 9.78 7.11 6.41 28.34 9.14 6.10 100% 35.31 8.19 HOV 26.05 13.25 10.75 6.75 7.95 24.73 5.78 4.72 100% 38.64 6.82 Bus and Light Rail 17.38 22.79 10.72 8.03 7.67 23.69 6.66 3.05 100% 3.61 6.51 Metro, Subway and Heavy Rail 6.06 7.78 11.40 8.53 13.31 39.15 8.68 5.10 100% 2.34 8.92 Commuter Rail 9.40 1.26 3.63 1.80 2.52 23.41 25.85 32.14 100% 0.54 20.80 Walk 88.33 6.99 2.01 0.95 0.28 1.44 N/A N/A 100% 15.80 0.74 Bicycle 72.82 9.44 5.27 1.58 3.87 5.87 0.43 0.71 100% 0.91 2.06 Total 33.61 12.30 9.15 5.95 6.13 22.32 6.10 4.43 100% 2.86 6.34 In an urban area but not in a MSA SOV 29.50 17.67 10.37 6.58 5.72 18.60 5.06 6.50 100% 43.46 6.81 HOV 30.50 17.13 9.41 5.62 6.58 18.92 4.91 6.93 100% 44.62 7.20 Walk 91.09 6.05 1.88 0.24 0.34 0.40 N/A N/A 100% 7.61 0.64 Bicycle 66.73 19.50 8.26 N/A 3.48 2.02 N/A N/A 100% 0.77 1.37 Total 34.85 16.45 9.13 5.77 5.78 17.35 4.59 6.07 100% 3.54 6.47 N/A implies insufficient data

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99 Table 6.4 Trips by Mode, Urban Size and Length on Weekends Trip Length (Miles) -> Mode (0-1] (1-2] (2-3] (3-4] (4-5] (510] (1025] 25+ Row% Mode Share Avg. Trip Length In an urban area with MSA of less than 250,000 SOV 27.27 19.32 12.60 6.66 7.67 20.94 2.81 2.74 100% 28.97 5.16 HOV 19.55 12.38 12.71 6.95 10.59 25.41 5.70 6.72 100% 62.53 8.34 Walk 85.59 9.50 2.26 0.11 1.46 0.44 0.64 N/A 100% 6.70 0.84 Bicycle 52.94 14.97 14.01 N/A 1.64 10.76 5.66 N/A 100% 1.14 3.25 Total 26.92 14.26 11.90 6.27 8.97 22.13 4.48 5.08 100% 0.66 6.85 In an urban area with MSA of 250,000 499,999 SOV 21.54 13.92 12.20 8.80 10.82 25.11 5.06 2.56 100% 25.81 6.02 HOV 21.03 10.15 13.43 6.43 9.54 25.65 6.21 7.57 100% 64.58 8.40 Walk 84.82 9.41 3.16 0.87 0.41 1.33 N/A N/A 100% 7.48 0.81 Bicycle 56.48 16.17 7.13 N/A 17.85 2.37 N/A N/A 100% 1.03 1.98 Total 26.61 11.07 12.18 6.49 9.16 23.38 5.41 5.70 100% 1.10 7.18 In an urban area with MSA of 500,000 999,999 SOV 22.09 13.91 11.39 9.51 7.76 24.03 5.63 5.67 100% 27.26 7.16 HOV 19.69 12.79 9.96 8.83 10.32 28.09 5.47 4.84 100% 65.77 7.29 Walk 87.43 8.18 3.00 N/A 1.39 N/A N/A N/A 100% 5.28 0.74 Bicycle 72.86 8.11 5.66 11.52 N/A N/A N/A 1.85 100% 0.80 2.44 Total 24.38 12.83 9.94 8.57 9.13 25.18 5.15 4.80 100% 0.90 6.86 In an urban area with MSA of 1,000,000 2,999,999 SOV 24.51 13.91 11.28 7.57 8.07 26.14 5.64 2.88 100% 29.19 6.17 HOV 17.76 12.17 9.97 8.90 8.36 29.08 8.74 5.02 100% 61.36 8.08 Walk 87.75 7.67 2.01 1.26 0.38 0.68 0.25 N/A 100% 7.09 0.77 Bicycle 65.73 10.81 3.27 3.81 2.23 11.65 2.05 0.45 100% 0.90 2.53 Total 25.25 12.42 9.71 7.87 7.64 26.00 7.11 3.99 100% 1.46 6.93 In an urban area with MSA of 3 million or more w/o heavy transit SOV 25.79 15.49 10.02 6.95 8.48 23.16 5.28 4.82 100% 25.07 6.60 HOV 18.46 13.43 9.04 8.06 8.22 27.90 6.52 8.36 100% 63.34 8.94 Walk 93.26 3.24 1.33 0.91 0.53 0.72 N/A N/A 100% 8.83 0.65 Bicycle 76.04 13.50 0.59 N/A 2.66 4.83 2.38 N/A 100% 0.84 1.72 Total 27.75 13.12 8.38 7.04 7.62 23.88 5.61 6.60 100% 1.92 7.52 In an urban area with MSA of 3 million or more w/ heavy transit SOV 24.43 14.87 10.92 6.00 7.98 22.79 6.66 6.36 100% 23.80 7.36 HOV 19.79 11.98 8.96 6.38 8.25 27.73 7.75 9.15 100% 57.70 9.35 Bus and Light Rail 13.08 8.92 19.74 7.76 13.84 31.53 4.39 0.74 100% 2.70 5.76 Metro, Subway and Heavy Rail 3.96 3.55 10.80 26.00 25.32 18.82 7.35 4.20 100% 1.66 7.64 Commuter Rail 60.25 N/A N/A N/A N/A 15.35 N/A 24.40 100% 0.15 9.43 Walk 91.82 3.40 3.14 0.28 0.42 0.90 N/A 0.04 100% 11.53 0.64 Bicycle 61.67 14.57 12.25 1.39 2.22 5.49 2.41 N/A 100% 1.01 2.41 Total 29.25 11.77 9.03 5.80 7.52 23.18 6.37 7.08 100% 1.45 7.68 In an urban area but not in a MSA SOV 31.18 19.23 13.45 3.84 5.69 15.89 4.91 5.79 100% 25.75 6.39 HOV 24.18 13.34 10.85 6.35 6.13 21.89 7.40 9.88 100% 63.97 9.31 Walk 81.83 10.85 3.20 0.57 1.66 1.90 N/A N/A 100% 8.43 0.86 Bicycle 86.99 9.21 1.40 N/A N/A N/A 2.39 N/A 100% 0.78 1.25 Total 31.19 14.55 10.97 5.16 5.69 18.33 6.14 7.96 100% 1.07 7.80 N/A implies insufficient data

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100 6.4 Gender Differences Table 6.5 shows the differences in share of male versus females on different transportation modes. The tabl e shows comparison of only the major modes in that urban area size. Comparison of other modes was not possible because of low share of trips on them. On weekdays, males dominate in person trips made on SOV or bicycle but females person trips are more on HOV. A 15-20% d ecrease in share of trips on SOV by both males and females on weekends is shown to a ppear as in increase in their share of HOV trips. Compared to weekdays, on weekends both males and females show a decrease in the percent of trips made on transit. In urba n area with a population of 3 million or more and with heavy transit, the d ecrease in share of trips made on bus and light rail is about twice that of males. On weekda ys, in most of the urban areas, percent of walking trips are more for females as compared to the females. On the other hand, it is the males who have more percent of walking trips than females, except in areas with 3 million or more population with heavy transit. Although percent of walk trips by males show both an increase on weekends depending on the urban size, there is a decrease in share of female walk trips on weekends. Trips made on bicycl e by males constitute roughly the same of about 1.2% of the trips on weekdays or on w eekends. Percent of bicycle trips by females vary a lot with urban sizes from about 0.25% 0.63% on weekdays to 0.34% 0.97% on weekends. However generally in most of the ur ban areas, there is an increase in the share of bicycling trips by both males and females.

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101 Table 6.5 Percent Person Trips by Mode, Ur ban Size and Gender of the Trip-maker Weekdays Weekends Mode Male FemaleTotal Male Female Total In an urban area with MSA of less than 250,000 SOV 47.79 40.58 43.98 30.94 27.01 28.97 HOV 40.85 48.65 44.97 60.11 64.94 62.53 Walk 7.13 8.05 7.62 6.73 6.67 6.70 Bicycle 1.27 0.25 0.73 1.30 0.97 1.14 In an urban area with MSA of 250,000 499,999 SOV 45.04 39.06 41.91 26.35 25.27 25.81 HOV 41.84 48.94 45.55 62.71 66.48 64.58 Walk 7.88 7.90 7.89 8.00 6.94 7.48 Bicycle 1.13 0.34 0.72 1.43 0.62 1.03 In an urban area with MSA of 500,000 999,999 SOV 43.95 40.69 42.20 31.04 23.95 27.26 HOV 44.00 49.38 46.88 61.96 69.10 65.77 Walk 7.15 6.53 6.82 4.95 5.57 5.28 Bicycle 1.30 0.49 0.87 1.18 0.46 0.80 In an urban area with MSA of 1,000,000 2,999,999 SOV 47.41 40.55 43.87 32.07 26.41 29.19 HOV 38.89 46.14 42.63 58.00 64.59 61.36 Walk 8.27 9.16 8.73 7.39 6.80 7.09 Bicycle 1.20 0.63 0.90 1.15 0.66 0.90 In an urban area with MSA of 3 million or more w/o heavy transit SOV 43.35 36.32 39.69 27.37 22.76 25.07 HOV 41.16 49.01 45.24 60.30 66.39 63.34 Walk 9.19 10.12 9.68 9.43 8.23 8.83 Bicycle 1.44 0.46 0.93 0.81 0.86 0.84 In an urban area with MSA of 3 million or more w/ heavy transit SOV 38.84 32.02 35.31 28.20 19.49 23.80 HOV 35.65 41.41 38.64 52.88 62.42 57.70 Bus and Light Rail 3.23 3.96 3.61 2.63 2.77 2.70 Metro, Subway and Heavy Rail 2.49 2.20 2.34 1.75 1.57 1.66 Commuter Rail 0.67 0.42 0.54 0.19 0.12 0.15 Walk 14.81 16.72 15.80 10.93 12.11 11.53 Bicycle 1.25 0.59 0.91 1.46 0.56 1.01 In an urban area but not in a MSA SOV 47.11 40.00 43.46 29.75 21.81 25.75 HOV 40.12 48.88 44.62 58.91 68.95 63.97 Walk 7.73 7.50 7.61 9.13 7.74 8.43 Bicycle 1.28 0.28 0.77 1.22 0.34 0.78

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102 CHAPTER 7 VARIATION IN VEHICLE OCCUPANCIES 7.1 Introduction This chapter focuses on differences in numb er of persons on the trip or the vehicle occupancies on weekdays and weekends. Even though more number of persons may be present on the trip, that partic ular trip may not be lengthier as opposed to a single person trip which may be driven for longer distances. To account for the trip length, the each trip was weighted with its trip length before ca lculating the average vehicle occupancy rate for that trip. The final occupancy rate thus calculated is often termed as mileage based occupancy rate. Another issue that comes while analyz ing occupancy rates is which trips to take, that is should we c onsider all the trips made no matter the person was a driver on the trip or passenger on the trip or only cas es belonging to driver trips. Consider a household having two members been interviewed on travel survey day. Suppose they make two vehicle trips such th at on the first one th ey traveled along with three other nonhousehold members while on the second vehi cle trip one of the household members drove alone. In both the trips, we further assume that only one member of the household did all the driving. Assuming the trips of sa me length, the average occupancy rate should be about three persons per vehicle trip. Bu t in the trip file consisting of only the

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103 household members with none of the non-house hold members been interviewed on that survey day, one of the persons would report hi s single trip consisti ng of five persons on the trip while the second one would report two trips, first consisting of five persons on the trip while the second consisting of only one person being himself. Taking all the trips, average occupancy rate comes to about 3.67. Ho wever, taking only the driver trips into account yields three persons per vehicle trip or a value closer to a realistic value. To account for this fact, only vehicle trips were taken to calculate the average occupancy rates. This takes care of the fact that trips made on public transit are excluded from the analysis too. 7.2 Occupancy by Trip Purpose 7.2.1 Urban Area Size and Purpose Table 7.1 and 7.2 shows variation in aver age daily occupancy rate by urban area size and trip purpose. There is generally an increase in th e occupancy rates from 1.44 on weekdays to about 2.00 on weekends. Vehicle o ccupancy rates increase slightly in home based work trip from weekdays to weekends whereas they increase to almost 2.37 in case for social recreational purposes. HBSo c trips which had about 1.74 occupancy on weekdays increase to an about 2.20 on weekends.

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104 Table 7.1 Average Daily Auto-Occupancy Rates by Urbanized Area Population and Purpose for Weekdays Trip Purpose Urban Area MSA Size HBW HBShop HBSoc HBOther HBNW NHB All Less than 250,000 1.07 1.62 1.72 1.55 1.60 1.48 1.43 250,000 499,999 1.05 1.51 1.80 1.66 1.65 1.51 1.44 500,000 999,999 1.05 1.78 1.75 1.58 1.66 1.55 1.45 1,000,000 2,999,999 1.09 1.47 1.75 1.63 1.62 1.49 1.41 3,000,000+ 1.11 1.61 1.86 1.66 1.69 1.50 1.44 Not in MSA (CMSA) 1.17 1.58 1.69 1.57 1.60 1.54 1.46 Table 7.2 Average Daily Auto-Occupancy Rates by Urbanized Area Population and Purpose for Weekends Trip Purpose Urban Area MSA Size HBW HBShop HBSoc HBOther HBNW NHB All Less than 250,000 1.34 1.67 2.37 1.91 1.99 2.12 1.96 250,000 499,999 1.08 1.83 2.22 1.99 2.02 2.17 1.98 500,000 999,999 1.21 1.97 1.82 1.71 1.81 1.99 1.80 1,000,000 2,999,999 1.10 1.71 2.01 1.90 1.88 1.97 1.82 3,000,000+ 1.07 2.10 2.24 2.03 2.11 2.14 2.01 Not in MSA (CMSA) 1.24 2.31 2.30 1.98 2.17 2.41 2.14 7.2.2 Trip Purpose and Income Table 7.3 and 7.4 gives the comparison of vehicle occupancy rates on weekday and weekends by household income and trip pur pose. As evident from the table, higher income households have lesser number of occupa nts on the trip as compared to the lower income ones. However, trips made for social recreational purposes by those having higher income have higher occupancy rates as compared to the lower income households. There is almost an increase of one pers on on a trip made for shopping by lower income households on weekends as compared to 1.57 on weekdays.

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105 Table 7.3 Average Daily Auto-Occupancy Rates by Income Category and Purpose for Weekdays Trip Purpose Income HBW HBShop HBSoc HBOther NHB Total Low 1.13 1.57 1.61 1.64 1.59 1.59 Medium 1.09 1.61 1.76 1.62 1.65 1.52 High 1.11 1.54 1.85 1.65 1.67 1.48 All 1.10 1.58 1.79 1.63 1.65 1.51 Table 7.4 Average Daily Auto-Occupancy Rates by Income Category and Purpose for Weekends Trip Purpose Income HBW HBShop HBSoc HBOther NHB Total Low 1.07 2.62 1.97 1.89 2.13 2.14 Medium 1.10 1.87 2.19 1.94 1.99 2.15 High 1.15 1.90 2.21 2.00 2.03 2.07 All 1.12 2.00 2.16 1.96 2.02 2.12 7.2.3 Trip Purpose and Trip Length The variation of occupancy rates for differe nt purposes with different trip lengths is shown in Table 7.5. Vehicle occupancy ra tes increase from wee kdays to weekends with an increase in trip lengths too. Where the increase in occupancy on weekends for trip of length less than one mile is some 0.15, the same is 0.68 for trips more than 25 miles. Major share of this increase in occupa ncy rate on weekends in trips greater than 25 miles comes from the trips made for shopping where the increase was 0.90 apart from the increase in non-home based trips where the in crease is 0.69. There is almost no effect on the increase in occupancy rates for the home based work trips. Trips made for social recreational purposes have hi gh occupancy rates on both wee kdays and weekends but the maximum increase is in trips having length from 1-3 miles. Non-home based trips show

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106 the maximum increase of 0.62 in vehicle occ upancy on weekends as compared to any other purposed trip. Table 7.5 Average Occupancy Rates by Trip Length and Trip Purpose Trip Length HBW HBShop HBSoc HBOther NHB All Weekday 1 Mile or Less 1.07 1.34 1.55 1.73 1.47 1.49 1 mile to 2 mile 1.09 1.35 1.51 1.62 1.46 1.44 2 mile to 3 mile 1.07 1.42 1.64 1.59 1.54 1.47 3 mile to 4 mile 1.08 1.46 1.77 1.59 1.48 1.47 4 mile to 5 mile 1.06 1.51 1.82 1.63 1.52 1.49 5 mile to 10 mile 1.06 1.57 1.69 1.62 1.50 1.42 10 mile to 25 mile 1.09 1.66 1.99 1.55 1.44 1.36 More than 25 mile 1.16 1.86 1.96 1.68 1.56 1.47 Weighted Average 1.10 1.58 1.79 1.62 1.51 1.43 Weekend 1 Mile or Less 1.08 1.44 1.76 1.72 1.77 1.64 1 mile to 2 mile 1.05 1.41 1.93 1.76 1.87 1.69 2 mile to 3 mile 1.05 1.60 2.10 1.66 1.96 1.76 3 mile to 4 mile 1.16 1.69 1.96 1.74 2.06 1.81 4 mile to 5 mile 1.05 1.74 1.93 1.86 2.01 1.82 5 mile to 10 mile 1.12 1.82 2.07 1.86 2.08 1.88 10 mile to 25 mile 1.09 2.04 2.20 2.03 2.13 1.96 More than 25 mile 1.15 2.77 2.32 2.10 2.25 2.15 Weighted Average 1.12 2.00 2.16 1.95 2.12 1.96 7.3 Occupancy by Gender and Trip Length Table 7.6 shows the occupancy rates on tr ips with male and females as the drivers. The trips with females as the dr iver have more vehicle occupancy rates on weekdays whatever the trip length may be. On weekends, the occupancy rates are more for trips with males as the driver but are stri kingly lesser than females in trips of length 25 miles. From Table 7.7 it is clear that this ki nd of behavior is e xhibited in urban areas with population of less than 250,000 and the other having the population between of 1 million or more and less than 3 million.

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107 Table 7.6 Average Occupancy Rates by Tr ip Length and Gender of the Driver Weekday Weekend Trip Length Male Female All Male Female All 1 Mile or Less 1.42 1.55 1.49 1.68 1.58 1.64 1 mile to 2 mile 1.39 1.49 1.44 1.71 1.65 1.69 2 mile to 3 mile 1.43 1.50 1.47 1.83 1.67 1.76 3 mile to 4 mile 1.44 1.50 1.47 1.89 1.71 1.81 4 mile to 5 mile 1.45 1.53 1.49 1.88 1.74 1.82 5 mile to 10 mile 1.38 1.47 1.42 1.92 1.81 1.88 10 mile to 25 mile 1.34 1.39 1.36 2.00 1.91 1.96 More than 25 mile 1.44 1.54 1.47 2.08 2.28 2.15 Weighted Average 1.40 1.48 1.43 1.97 1.93 1.96 Table 7.7 Average Occupancy by Trip Length Urban Size and Gender of the Driver Weekdays Weekends Trip Miles Male FemaleAll Male Female All In an urban area with MSA of less than 250,000 1 mile or Less 1.49 1.40 1.44 1.67 1.53 1.60 1 mile to 2 miles 1.43 1.34 1.38 1.65 1.56 1.61 2 miles to 3 miles 1.32 1.48 1.40 1.75 1.72 1.74 3 miles to 4 miles 1.29 1.56 1.42 1.64 1.84 1.71 4 miles to 5 miles 1.41 1.53 1.47 1.81 1.76 1.79 5 miles to 10 miles 1.33 1.53 1.42 1.97 1.68 1.86 10 miles to 25 miles 1.37 1.42 1.39 2.23 1.71 2.06 More than 25 miles 1.44 1.48 1.45 2.41 2.08 2.25 Weighted Average 1.38 1.49 1.43 2.05 1.82 1.96 In an urban area with MSA of 250,000 499,999 1 mile or Less 1.44 1.53 1.49 2.07 1.54 1.82 1 mile to 2 miles 1.43 1.59 1.51 1.92 1.37 1.65 2 miles to 3 miles 1.48 1.51 1.50 1.91 1.64 1.80 3 miles to 4 miles 1.42 1.41 1.42 1.49 1.58 1.53 4 miles to 5 miles 1.47 1.57 1.52 1.58 1.83 1.69 5 miles to 10 miles 1.41 1.45 1.43 1.72 1.88 1.78 10 miles to 25 miles 1.30 1.45 1.37 2.28 1.60 2.08 More than 25 miles 1.44 1.53 1.47 2.21 2.71 2.37 Weighted Average 1.41 1.48 1.44 1.97 1.99 1.98

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108 Table 7.7 Continued Weekdays Weekends Trip Miles Male FemaleAll Male Female All In an urban area with MSA of 500,000 999,999 1 mile or Less 1.49 1.60 1.55 1.70 1.49 1.60 1 mile to 2 miles 1.45 1.45 1.45 1.82 1.64 1.73 2 miles to 3 miles 1.51 1.56 1.54 1.83 1.66 1.75 3 miles to 4 miles 1.59 1.61 1.60 1.89 1.59 1.74 4 miles to 5 miles 1.42 1.58 1.49 1.90 1.91 1.90 5 miles to 10 miles 1.38 1.48 1.43 1.88 1.67 1.81 10 miles to 25 miles 1.22 1.51 1.35 1.81 1.97 1.85 More than 25 miles 1.39 1.74 1.50 1.68 1.94 1.78 Weighted Average 1.37 1.54 1.45 1.80 1.79 1.80 In an urban area with MSA of 1,000,000 2,999,999 1 mile or Less 1.39 1.49 1.45 1.61 1.47 1.54 1 mile to 2 miles 1.35 1.44 1.40 1.61 1.67 1.64 2 miles to 3 miles 1.43 1.50 1.46 1.70 1.63 1.67 3 miles to 4 miles 1.40 1.47 1.44 1.91 1.69 1.81 4 miles to 5 miles 1.36 1.55 1.45 1.70 1.85 1.77 5 miles to 10 miles 1.38 1.41 1.40 1.78 1.80 1.79 10 miles to 25 miles 1.33 1.35 1.34 2.02 1.83 1.95 More than 25 miles 1.42 1.60 1.46 1.93 1.73 1.87 Weighted Average 1.38 1.44 1.41 1.86 1.77 1.82 In an urban area with MSA of 3 million or more 1 mile or Less 1.44 1.62 1.54 1.69 1.65 1.67 1 mile to 2 miles 1.40 1.54 1.48 1.75 1.70 1.73 2 miles to 3 miles 1.45 1.51 1.48 1.92 1.60 1.77 3 miles to 4 miles 1.48 1.52 1.50 2.00 1.72 1.89 4 miles to 5 miles 1.55 1.48 1.52 2.04 1.61 1.86 5 miles to 10 miles 1.37 1.51 1.44 2.03 1.81 1.94 10 miles to 25 miles 1.35 1.38 1.36 1.92 1.93 1.93 More than 25 miles 1.41 1.55 1.45 2.12 2.36 2.20 Weighted Average 1.39 1.50 1.44 2.03 1.97 2.01 In an urban area but not in a MSA 1 mile or Less 1.33 1.50 1.42 1.61 1.73 1.67 1 mile to 2 miles 1.37 1.44 1.41 1.65 1.72 1.68 2 miles to 3 miles 1.36 1.44 1.40 1.82 2.00 1.89 3 miles to 4 miles 1.37 1.44 1.40 1.93 2.01 1.96 4 miles to 5 miles 1.36 1.65 1.49 2.00 1.61 1.86 5 miles to 10 miles 1.39 1.45 1.42 2.06 1.97 2.03 10 miles to 25 miles 1.46 1.36 1.42 2.09 2.24 2.14 More than 25 miles 1.56 1.42 1.51 2.16 2.63 2.35 Weighted Average 1.47 1.44 1.46 2.06 2.27 2.14

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109 CHAPTER 8 DIURNAL DISTRIBUTION OF TRIPS 8.1 Introduction All the trip characteristics such as trip frequencies, trip leng ths, vehicle occupancy can vary greatly with time of the day for diffe rent market segments. Such a variation can be expected because of change in purpose for which the trips are made with time and various other reasons such as number of persons accompanied on the trip, mode usage, trip length. Such a behavior can help in understanding what travel demand management strategies should be formulated so as to lower relieve the co ngestion occurring during peak hours and preventing the air quality degrad ation too at peak times too. This section describes how the trip characteristics vary by time of day. 8.2 Distribution of Person Trips by Mode Table 8.1 and 8.2 gives the comparison of weekdays versus weekend distribution of trips on different modes with time of day in different urban size areas. Figure 8.1 shows that on weekday trips with only one occupant share the maximum percent of about 8% in the morning as compared to the 6.7% as HOV between 7:00 am to 7:59 am. After morning peak, the share of auto decreases but shows some incr ease during lunch hours from noon to 12:59 pm. In evenings, most of the SOV trips (about 8%) maintain the share

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110 Table 8.1 Percent Person Trips by Mode, Time of Day and Urban Size on Weekdays Trip Start Time SOV HOV Bus and Light Rail Metro, Subway and Heavy Rail Commuter Rail Walk Bicycle Total In an urban area with MSA of 250,000 499,999 Midnight 0.46 0.33 N/A N/A N/A 0.23 N/A 0.36 1:00 AM 0.05 0.19 N/A N/A N/A N/A N/A 0.12 2:00 AM 0.10 0.21 N/A N/A N/A 0.21 N/A 0.16 3:00 AM 0.08 0.03 N/A N/A N/A 0.13 N/A 0.05 4:00 AM 0.70 0.09 N/A N/A N/A N/A 0.66 0.34 5:00 AM 1.39 0.34 N/A N/A N/A 1.53 4.57 0.91 6:00 AM 4.33 1.47 N/A N/A N/A 1.88 1.69 2.83 7:00 AM 8.00 6.84 N/A N/A N/A 5.67 5.40 7.58 8:00 AM 6.90 4.57 N/A N/A N/A 4.19 9.79 5.71 9:00 AM 5.80 3.79 N/A N/A N/A 3.96 6.45 4.60 10:00 AM 6.21 4.54 N/A N/A N/A 5.07 0.30 5.18 11:00 AM 7.40 5.26 N/A N/A N/A 5.45 3.85 6.13 Noon 7.92 6.47 N/A N/A N/A 5.78 1.14 6.92 1:00 PM 6.67 5.81 N/A N/A N/A 4.56 6.49 6.15 2:00 PM 6.45 6.43 N/A N/A N/A 7.07 7.95 6.76 3:00 PM 7.16 8.61 N/A N/A N/A 10.11 16.97 8.42 4:00 PM 7.98 7.52 N/A N/A N/A 7.74 13.83 7.62 5:00 PM 7.47 8.27 N/A N/A N/A 7.97 10.28 7.82 6:00 PM 4.58 9.12 N/A N/A N/A 7.82 7.71 6.85 7:00 PM 3.25 7.04 N/A N/A N/A 9.21 N/A 5.42 8:00 PM 2.63 5.50 N/A N/A N/A 6.87 1.46 4.30 9:00 PM 2.05 4.39 N/A N/A N/A 2.18 1.46 3.05 10:00 PM 1.48 1.82 N/A N/A N/A 0.84 N/A 1.56 11:00 PM 0.95 1.34 N/A N/A N/A 1.53 N/A 1.14 Total 100 100 N/A N/A N/A 100 100 100 N/A implies insufficient data

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111 Table 8.1 Continued Trip Start Time SOV HOV Bus and Light Rail Metro, Subway and Heavy Rail Commuter Rail Walk Bicycle Total In an urban area with MSA of 500,000 999,999 Midnight 0.54 0.30 N/A N/A N/A 0.34 N/A 0.39 1:00 AM 0.22 0.30 N/A N/A N/A 0.08 N/A 0.24 2:00 AM 0.29 0.40 N/A N/A N/A 0.38 N/A 0.34 3:00 AM 0.14 0.11 N/A N/A N/A N/A N/A 0.12 4:00 AM 0.46 0.18 N/A N/A N/A 0.02 N/A 0.32 5:00 AM 1.57 0.83 N/A N/A N/A 0.94 N/A 1.12 6:00 AM 4.60 1.70 N/A N/A N/A 2.15 11.59 3.23 7:00 AM 8.43 7.49 N/A N/A N/A 7.83 3.45 8.13 8:00 AM 6.28 4.68 N/A N/A N/A 5.59 2.72 5.49 9:00 AM 5.41 3.20 N/A N/A N/A 5.13 N/A 4.27 10:00 AM 5.94 4.69 N/A N/A N/A 4.19 N/A 5.09 11:00 AM 6.27 4.64 N/A N/A N/A 7.53 3.83 5.58 Noon 7.79 7.34 N/A N/A N/A 8.45 5.26 7.44 1:00 PM 6.70 4.77 N/A N/A N/A 3.07 2.93 5.42 2:00 PM 6.25 7.24 N/A N/A N/A 6.30 4.81 7.15 3:00 PM 6.99 9.10 N/A N/A N/A 9.65 12.17 8.36 4:00 PM 8.48 8.36 N/A N/A N/A 6.97 13.66 8.36 5:00 PM 7.83 7.71 N/A N/A N/A 5.68 0.95 7.38 6:00 PM 5.44 9.20 N/A N/A N/A 9.79 12.61 7.44 7:00 PM 3.65 6.86 N/A N/A N/A 4.65 13.82 5.20 8:00 PM 2.54 5.06 N/A N/A N/A 5.06 9.28 3.90 9:00 PM 1.87 3.29 N/A N/A N/A 3.05 N/A 2.59 10:00 PM 1.47 2.07 N/A N/A N/A 1.89 N/A 1.72 11:00 PM 0.84 0.50 N/A N/A N/A 1.29 2.93 0.70 Total 100 100 N/A N/A N/A 100 100 100 N/A implies insufficient data

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112 Table 8.1 Continued Trip Start Time SOV HOV Bus and Light Rail Metro, Subway and Heavy Rail Commuter Rail Walk Bicycle Total In an urban area with MSA of 1,000,000 2,999,999 Midnight 0.43 0.25 N/A N/A N/A 0.95 N/A 0.38 1:00 AM 0.23 0.19 N/A N/A N/A 0.20 N/A 0.21 2:00 AM 0.18 0.21 N/A N/A N/A 0.14 N/A 0.18 3:00 AM 0.17 0.08 N/A N/A N/A 0.03 N/A 0.11 4:00 AM 0.47 0.23 N/A N/A N/A 0.10 N/A 0.33 5:00 AM 1.79 0.43 N/A N/A N/A 0.37 1.58 1.03 6:00 AM 4.71 2.55 N/A N/A N/A 2.53 N/A 3.62 7:00 AM 7.65 6.21 N/A N/A N/A 5.88 3.71 7.11 8:00 AM 5.98 5.50 N/A N/A N/A 5.47 7.43 5.99 9:00 AM 4.86 3.71 N/A N/A N/A 2.51 1.66 4.09 10:00 AM 5.22 4.94 N/A N/A N/A 3.85 1.73 4.88 11:00 AM 6.53 5.93 N/A N/A N/A 5.78 3.17 6.05 Noon 7.26 6.65 N/A N/A N/A 7.13 3.04 6.87 1:00 PM 6.15 5.69 N/A N/A N/A 6.49 1.87 5.86 2:00 PM 6.07 6.78 N/A N/A N/A 7.13 5.43 6.76 3:00 PM 7.42 8.64 N/A N/A N/A 10.22 10.38 8.50 4:00 PM 8.72 7.92 N/A N/A N/A 7.63 17.12 8.18 5:00 PM 8.85 9.16 N/A N/A N/A 8.06 15.75 8.86 6:00 PM 6.10 7.55 N/A N/A N/A 7.61 9.53 6.74 7:00 PM 3.94 6.33 N/A N/A N/A 7.62 7.49 5.24 8:00 PM 2.64 5.27 N/A N/A N/A 3.97 6.39 3.83 9:00 PM 2.23 3.52 N/A N/A N/A 3.42 2.08 2.83 10:00 PM 1.51 1.45 N/A N/A N/A 1.93 1.64 1.51 11:00 PM 0.90 0.79 N/A N/A N/A 0.98 N/A 0.83 Total 100 100 N/A N/A N/A 100 100 100 N/A implies insufficient data

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113 Table 8.1 Continued Trip Start Time SOV HOV Bus and Light Rail Metro, Subway and Heavy Rail Commuter Rail Walk Bicycle Total In an urban area with MSA of 3 million or more w/o heavy transit Midnight 0.55 0.41 N/A N/A N/A 0.13 N/A 0.44 1:00 AM 0.25 0.18 N/A N/A N/A N/A N/A 0.19 2:00 AM 0.10 0.14 N/A N/A N/A 0.23 N/A 0.13 3:00 AM 0.09 0.04 N/A N/A N/A N/A 0.62 0.07 4:00 AM 0.71 0.15 N/A N/A N/A 0.07 0.21 0.36 5:00 AM 2.10 0.45 N/A N/A N/A 0.44 1.84 1.17 6:00 AM 4.44 1.92 N/A N/A N/A 1.98 3.05 3.17 7:00 AM 7.80 5.65 N/A N/A N/A 5.55 3.51 6.91 8:00 AM 6.70 6.32 N/A N/A N/A 7.30 1.73 6.67 9:00 AM 6.17 4.14 N/A N/A N/A 3.63 8.83 4.89 10:00 AM 5.41 5.12 N/A N/A N/A 5.79 2.23 5.18 11:00 AM 5.90 6.85 N/A N/A N/A 5.73 3.50 6.22 Noon 6.39 5.90 N/A N/A N/A 6.88 4.39 6.09 1:00 PM 6.74 5.89 N/A N/A N/A 5.04 4.02 6.03 2:00 PM 6.68 7.18 N/A N/A N/A 9.10 5.68 7.38 3:00 PM 6.73 9.40 N/A N/A N/A 9.71 18.26 8.69 4:00 PM 7.88 7.33 N/A N/A N/A 7.00 11.75 7.48 5:00 PM 8.36 8.42 N/A N/A N/A 7.22 8.69 8.19 6:00 PM 6.20 7.50 N/A N/A N/A 7.45 9.38 6.81 7:00 PM 4.05 6.45 N/A N/A N/A 7.47 7.36 5.37 8:00 PM 2.78 4.12 N/A N/A N/A 4.81 2.78 3.47 9:00 PM 1.86 3.47 N/A N/A N/A 2.96 1.52 2.63 10:00 PM 1.21 1.82 N/A N/A N/A 1.00 0.67 1.48 11:00 PM 0.90 1.16 N/A N/A N/A 0.51 N/A 0.98 Total 100 100 N/A N/A N/A 100 100 100 N/A implies insufficient data

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114 Table 8.1 Continued Trip Start Time SOV HOV Bus and Light Rail Metro, Subway and Heavy Rail Commuter Rail Walk Bicycle Total In an urban area with MSA of 3 million or more w/ heavy transit Midnight 0.47 0.59 N/A 0.14 N/A 0.25 N/A 0.44 1:00 AM 0.16 0.13 N/A 0.09 N/A 0.20 1.79 0.17 2:00 AM 0.08 0.06 0.19 N/A N/A 0.08 N/A 0.07 3:00 AM 0.03 N/A N/A 0.60 N/A N/A N/A 0.04 4:00 AM 0.56 0.47 0.42 0.76 N/A N/A N/A 0.41 5:00 AM 1.84 0.70 2.45 1.23 3.12 0.11 0.14 1.08 6:00 AM 4.11 1.59 3.42 3.00 11.93 1.31 2.00 2.66 7:00 AM 7.78 7.85 9.76 9.75 20.97 4.08 4.42 7.74 8:00 AM 7.48 6.22 9.99 10.79 10.30 6.68 2.14 7.09 9:00 AM 5.38 3.13 8.15 8.11 0.37 4.46 3.04 4.37 10:00 AM 5.52 4.59 6.40 4.33 1.06 4.04 2.85 4.79 11:00 AM 6.07 5.66 5.50 4.73 2.79 4.67 2.68 5.52 Noon 6.93 5.23 5.04 3.85 3.77 8.69 5.91 6.29 1:00 PM 6.45 5.53 4.92 2.60 2.93 8.03 6.91 6.11 2:00 PM 6.21 6.25 7.08 8.91 1.74 9.66 7.80 7.21 3:00 PM 7.46 8.16 8.88 5.24 5.59 8.68 9.71 8.14 4:00 PM 7.62 6.88 8.40 7.52 8.54 7.12 14.89 7.20 5:00 PM 7.79 9.46 6.79 9.27 15.39 7.77 16.18 8.42 6:00 PM 6.18 8.18 5.41 9.00 6.90 7.13 6.82 7.04 7:00 PM 4.06 7.04 1.65 4.21 1.94 7.34 7.06 5.64 8:00 PM 2.83 5.38 2.43 1.16 N/A 4.34 1.98 3.97 9:00 PM 2.51 3.74 1.68 2.13 1.04 2.60 2.16 2.89 10:00 PM 1.41 2.38 0.85 1.76 N/A 1.99 1.52 1.85 11:00 PM 1.07 0.77 0.59 0.82 1.61 0.77 N/A 0.86 Total 100 100 100 100 100 100 100 100 N/A implies insufficient data

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115 Table 8.1 Continued Trip Start Time SOV HOV Bus and Light Rail Metro, Subway and Heavy Rail Commuter Rail Walk Bicycle Total In an urban area but not in a MSA Midnight 0.37 0.39 N/A N/A N/A 0.30 N/A 0.36 1:00 AM 0.15 0.26 N/A N/A N/A 0.21 N/A 0.21 2:00 AM 0.09 0.17 N/A N/A N/A 0.02 N/A 0.12 3:00 AM 0.14 0.05 N/A N/A N/A N/A N/A 0.09 4:00 AM 0.69 0.20 N/A N/A N/A 0.06 N/A 0.40 5:00 AM 1.50 0.82 N/A N/A N/A 0.57 N/A 1.07 6:00 AM 4.24 1.48 N/A N/A N/A 1.82 0.85 2.90 7:00 AM 7.98 6.52 N/A N/A N/A 6.97 6.26 7.69 8:00 AM 6.08 5.08 N/A N/A N/A 6.94 N/A 5.76 9:00 AM 6.36 4.08 N/A N/A N/A 3.67 9.27 5.02 10:00 AM 6.29 5.14 N/A N/A N/A 5.17 4.94 5.52 11:00 AM 7.17 6.40 N/A N/A N/A 7.52 5.96 6.66 Noon 8.27 6.20 N/A N/A N/A 6.75 7.14 7.00 1:00 PM 6.87 5.47 N/A N/A N/A 6.64 7.69 6.13 2:00 PM 6.05 7.40 N/A N/A N/A 5.05 5.27 6.94 3:00 PM 7.02 8.70 N/A N/A N/A 10.57 9.84 8.64 4:00 PM 7.70 8.49 N/A N/A N/A 6.15 10.17 7.75 5:00 PM 7.76 9.13 N/A N/A N/A 7.61 10.86 8.17 6:00 PM 5.10 7.10 N/A N/A N/A 6.73 13.72 6.10 7:00 PM 3.39 6.04 N/A N/A N/A 6.25 4.27 4.70 8:00 PM 2.87 5.36 N/A N/A N/A 7.09 1.74 4.23 9:00 PM 1.99 3.65 N/A N/A N/A 2.42 1.89 2.75 10:00 PM 1.16 0.81 N/A N/A N/A 1.10 0.13 0.98 11:00 PM 0.74 1.05 N/A N/A N/A 0.40 N/A 0.82 Total 100 100 N/A N/A N/A 100 100 100 N/A implies insufficient data

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116 Table 8.2 Percent Person Trips by Mode, Time of Day and Urban Size on Weekends Trip Start Time SOV HOV Bus and Light Rail Metro, Subway and Heavy Rail Commuter Rail Walk Bicycle Total In an urban area with MSA of less than 250,000 Midnight 0.39 0.32 N/A N/A N/A 0.36 N/A 0.34 1:00 AM 0.64 N/A N/A N/A N/A N/A N/A 0.19 2:00 AM 0.51 0.04 N/A N/A N/A N/A N/A 0.17 3:00 AM 0.05 N/A N/A N/A N/A N/A N/A 0.02 4:00 AM 0.34 N/A N/A N/A N/A N/A N/A 0.10 5:00 AM 0.33 0.76 N/A N/A N/A N/A N/A 0.57 6:00 AM 2.06 0.27 N/A N/A N/A 1.46 N/A 0.87 7:00 AM 5.52 1.35 N/A N/A N/A 5.02 4.95 2.84 8:00 AM 5.44 4.75 N/A N/A N/A 5.93 N/A 5.00 9:00 AM 6.74 7.43 N/A N/A N/A 4.66 N/A 6.91 10:00 AM 6.83 7.12 N/A N/A N/A 5.15 7.64 6.86 11:00 AM 9.39 9.96 N/A N/A N/A 6.79 2.90 9.44 Noon 7.94 8.87 N/A N/A N/A 0.38 14.63 8.05 1:00 PM 7.19 8.84 N/A N/A N/A 6.02 20.05 8.35 2:00 PM 7.43 7.69 N/A N/A N/A 5.37 7.34 7.48 3:00 PM 9.97 5.28 N/A N/A N/A 9.56 N/A 6.87 4:00 PM 5.84 6.87 N/A N/A N/A 14.71 11.61 7.21 5:00 PM 5.77 8.18 N/A N/A N/A 5.38 9.40 7.25 6:00 PM 3.50 5.80 N/A N/A N/A 8.00 17.86 5.59 7:00 PM 5.26 5.35 N/A N/A N/A 4.47 3.63 5.26 8:00 PM 2.56 5.05 N/A N/A N/A 8.44 N/A 4.47 9:00 PM 3.07 3.23 N/A N/A N/A 7.25 N/A 3.40 10:00 PM 1.68 1.93 N/A N/A N/A 1.08 N/A 1.76 11:00 PM 1.55 0.92 N/ A N/A N/A N/A N/A 1.02 Total 100 100 N/A N/A N/A 100 100 100 N/A implies insufficient data

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117 Table 8.2 Continued Trip Start Time SOV HOV Bus and Light Rail Metro, Subway and Heavy Rail Commuter Rail Walk Bicycle Total In an urban area with MSA of 250,000 499,999 Midnight 0.76 0.36 N/A N/A N/A 1.46 N/A 0.54 1:00 AM 0.26 0.13 N/A N/A N/A N/A N/A 0.15 2:00 AM 0.28 0.06 N/A N/A N/A N/A N/A 0.11 3:00 AM 0.21 0.21 N/A N/A N/A N/A N/A 0.19 4:00 AM 0.55 0.02 N/A N/A N/A N/A N/A 0.15 5:00 AM 0.58 0.09 N/A N/A N/A 0.60 N/A 0.25 6:00 AM 1.56 0.34 N/A N/A N/A 0.33 N/A 0.65 7:00 AM 3.44 1.14 N/A N/A N/A 3.68 N/A 1.91 8:00 AM 6.60 3.41 N/A N/A N/A 3.01 N/A 4.18 9:00 AM 7.62 4.74 N/A N/A N/A 4.11 4.88 5.42 10:00 AM 7.03 6.61 N/A N/A N/A 6.73 5.14 6.75 11:00 AM 6.80 9.77 N/A N/A N/A 13.24 6.84 9.18 Noon 7.71 9.41 N/A N/A N/A 7.94 11.43 8.86 1:00 PM 8.21 7.25 N/A N/A N/A 9.76 7.13 7.60 2:00 PM 7.93 7.74 N/A N/A N/A 11.41 23.03 8.16 3:00 PM 8.14 6.33 N/A N/A N/A 8.56 18.98 7.02 4:00 PM 8.26 7.65 N/A N/A N/A 6.63 6.38 7.88 5:00 PM 5.75 8.54 N/A N/A N/A 5.03 7.43 7.55 6:00 PM 5.30 7.87 N/A N/A N/A 3.15 5.48 7.05 7:00 PM 4.02 6.16 N/A N/A N/A 5.06 N/A 5.41 8:00 PM 3.47 5.20 N/A N/A N/A 2.34 N/A 4.48 9:00 PM 3.07 3.87 N/A N/A N/A 1.95 3.28 3.47 10:00 PM 1.67 2.19 N/A N/A N/A 3.80 N/A 2.13 11:00 PM 0.79 0.96 N/A N/A N/A 1.22 N/A 0.91 Total 100 100 N/A N/A N/A 100 100 100 N/A implies insufficient data

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118 Table 8.2 Continued Trip Start Time SOV HOV Bus and Light Rail Metro, Subway and Heavy Rail Commuter Rail Walk Bicycle Total In an urban area with MSA of 500,000 999,999 Midnight 0.57 0.28 N/A N/A N/A N/A N/A 0.34 1:00 AM 0.46 0.25 N/A N/A N/A N/A N/A 0.29 2:00 AM 0.09 0.20 N/A N/A N/A N/A N/A 0.16 3:00 AM 0.72 0.08 N/A N/A N/A N/A N/A 0.25 4:00 AM 0.92 N/A N/A N/A N/A N/A N/A 0.25 5:00 AM 0.74 0.22 N/A N/A N/A 0.22 N/A 0.36 6:00 AM 2.03 0.24 N/A N/A N/A 1.34 1.85 0.79 7:00 AM 3.81 0.95 N/A N/A N/A 5.67 N/A 1.98 8:00 AM 5.51 2.94 N/A N/A N/A 6.60 N/A 3.85 9:00 AM 6.46 6.52 N/A N/A N/A 3.66 N/A 6.30 10:00 AM 7.76 8.11 N/A N/A N/A 4.17 25.47 7.91 11:00 AM 7.25 8.09 N/A N/A N/A 6.34 8.58 7.88 Noon 8.82 10.36 N/A N/A N/A 4.82 28.43 9.72 1:00 PM 7.39 8.61 N/A N/A N/A 4.76 10.54 8.17 2:00 PM 8.22 8.69 N/A N/A N/A 9.21 N/A 8.54 3:00 PM 6.42 7.00 N/A N/A N/A 2.72 6.05 6.60 4:00 PM 8.01 6.65 N/A N/A N/A 8.67 12.45 7.15 5:00 PM 7.33 7.62 N/A N/A N/A 5.63 2.18 7.42 6:00 PM 4.84 6.89 N/A N/A N/A 13.44 N/A 6.61 7:00 PM 4.54 6.62 N/A N/A N/A 10.11 4.45 6.19 8:00 PM 3.00 4.25 N/A N/A N/A 5.09 N/A 3.90 9:00 PM 1.76 2.89 N/A N/A N/A 2.17 N/A 2.49 10:00 PM 2.05 1.43 N/A N/A N/A 3.46 N/A 1.68 11:00 PM 1.28 1.09 N/A N/A N/A 1.92 N/A 1.17 Total 100 100 N/A N/A N/A 100 100 100 N/A implies insufficient data

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119 Table 8.2 Continued Trip Start Time SOV HOV Bus and Light Rail Metro, Subway and Heavy Rail Commuter Rail Walk Bicycle Total In an urban area with MSA of 1,000,000 2,999,999 Midnight 0.60 0.46 N/A N/A N/A 0.24 1.87 0.51 1:00 AM 0.51 0.16 N/A N/A N/A 0.57 N/A 0.29 2:00 AM 0.38 0.23 N/A N/A N/A 0.24 N/A 0.27 3:00 AM 0.18 0.17 N/A N/A N/A 0.13 N/A 0.16 4:00 AM 0.72 0.19 N/A N/A N/A 0.10 N/A 0.33 5:00 AM 1.04 0.25 N/A N/A N/A 0.32 N/A 0.50 6:00 AM 1.90 0.38 N/A N/A N/A 1.04 1.43 0.88 7:00 AM 3.59 1.91 N/A N/A N/A 3.82 1.63 2.54 8:00 AM 4.85 3.55 N/A N/A N/A 5.23 1.56 4.09 9:00 AM 6.27 5.39 N/A N/A N/A 4.53 1.14 5.57 10:00 AM 8.43 7.38 N/A N/A N/A 9.06 4.50 7.79 11:00 AM 8.40 7.52 N/A N/A N/A 6.10 3.25 7.62 Noon 8.31 9.25 N/A N/A N/A 9.85 8.63 8.98 1:00 PM 7.64 8.53 N/A N/A N/A 6.20 6.99 8.17 2:00 PM 7.33 8.65 N/A N/A N/A 11.90 16.00 8.49 3:00 PM 7.42 7.69 N/A N/A N/A 5.42 8.90 7.45 4:00 PM 8.30 7.58 N/A N/A N/A 8.46 12.12 7.86 5:00 PM 6.90 7.04 N/A N/A N/A 6.13 11.34 6.95 6:00 PM 4.86 7.45 N/A N/A N/A 6.98 9.67 6.69 7:00 PM 3.82 4.47 N/A N/A N/A 5.04 5.76 4.31 8:00 PM 2.58 4.30 N/A N/A N/A 2.29 5.22 3.64 9:00 PM 2.82 4.00 N/A N/A N/A 3.78 N/A 3.65 10:00 PM 2.09 1.81 N/A N/A N/A 2.26 N/A 1.90 11:00 PM 1.08 1.63 N/A N/A N/A 0.32 N/A 1.34 Total 100 100 N/A N/A N/A 100 100 100 N/A implies insufficient data

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120 Table 8.2 Continued Trip Start Time SOV HOV Bus and Light Rail Metro, Subway and Heavy Rail Commuter Rail Walk Bicycle Total In an urban area with MSA of 3 million or more w/o heavy transit Midnight 0.79 0.34 N/A N/A N/A 0.09 N/A 0.42 1:00 AM 0.35 0.26 N/A N/A N/A 0.58 N/A 0.34 2:00 AM 0.16 0.24 N/A N/A N/A N/A 2.09 0.21 3:00 AM 0.12 0.07 N/A N/A N/A N/A N/A 0.07 4:00 AM 0.33 0.09 N/A N/A N/A 0.33 N/A 0.17 5:00 AM 0.60 0.05 N/A N/A N/A 0.34 N/A 0.22 6:00 AM 1.51 0.76 N/A N/A N/A 1.28 N/A 1.04 7:00 AM 3.64 1.06 N/A N/A N/A 3.00 1.97 1.86 8:00 AM 5.94 2.65 N/A N/A N/A 2.30 9.88 3.52 9:00 AM 6.89 6.70 N/A N/A N/A 4.07 1.62 6.50 10:00 AM 9.09 8.59 N/A N/A N/A 5.28 6.67 8.35 11:00 AM 7.88 8.67 N/A N/A N/A 5.08 8.47 8.20 Noon 9.10 9.80 N/A N/A N/A 9.07 2.02 9.46 1:00 PM 7.50 7.83 N/A N/A N/A 10.03 9.79 7.94 2:00 PM 7.29 8.42 N/A N/A N/A 7.94 11.28 8.19 3:00 PM 8.19 8.12 N/A N/A N/A 5.87 17.75 7.94 4:00 PM 7.16 8.01 N/A N/A N/A 11.43 5.93 8.03 5:00 PM 5.29 6.14 N/A N/A N/A 5.33 10.20 5.90 6:00 PM 5.90 6.54 N/A N/A N/A 9.20 3.43 6.62 7:00 PM 4.38 5.39 N/A N/A N/A 3.82 3.45 5.06 8:00 PM 3.27 4.53 N/A N/A N/A 4.58 5.44 4.18 9:00 PM 1.72 3.17 N/A N/A N/A 5.12 N/A 2.94 10:00 PM 1.83 1.48 N/A N/A N/A 4.14 N/A 1.77 11:00 PM 1.08 1.09 N/A N/A N/A 1.11 N/A 1.06 Total 100 100 N/A N/A N/A 100 100 100 N/A implies insufficient data

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121 Table 8.2 Continued Trip Start Time SOV HOV Bus and Light Rail Metro, Subway and Heavy Rail Commuter Rail Walk Bicycle Total In an urban area with MSA of 3 million or more w/ heavy transit Midnight 0.66 0.95 0.23 0.93 N/A 1.03 N/A 0.91 1:00 AM 0.44 0.43 N/A N/A N/A 0.45 N/A 0.45 2:00 AM 0.25 0.12 N/A 1.16 N/A 0.14 N/A 0.18 3:00 AM 0.17 0.02 N/A N/A N/A N/A 0.09 4:00 AM 0.53 0.09 0.58 N/A N/A 0.18 N/A 0.21 5:00 AM 0.54 0.28 1.22 N/A N/A 0.52 N/A 0.48 6:00 AM 2.97 0.59 1.79 5.17 20.57 0.55 N/A 1.28 7:00 AM 4.16 1.65 2.76 2.18 N/A 1.11 3.80 2.23 8:00 AM 5.99 3.27 5.06 4.80 23.29 4.26 2.05 4.09 9:00 AM 6.85 4.23 4.25 6.13 N/A 3.57 0.73 4.74 10:00 AM 8.41 7.79 5.20 3.95 3.72 6.98 8.22 7.69 11:00 AM 9.42 7.71 6.18 7.51 N/A 8.82 4.82 8.10 Noon 8.23 7.76 15.50 5.31 N/A 10.94 9.84 8.44 1:00 PM 8.36 7.70 10.36 4.00 11.47 8.96 9.52 8.05 2:00 PM 8.16 9.79 4.68 4.26 14.16 7.80 10.10 8.90 3:00 PM 6.15 8.67 11.65 12.12 23.29 6.82 8.49 7.94 4:00 PM 6.62 6.61 5.34 11.52 3.49 9.67 12.40 7.02 5:00 PM 5.62 6.70 10.47 5.35 N/A 7.31 12.94 6.70 6:00 PM 4.74 8.01 6.49 12.23 N/A 6.06 9.32 7.02 7:00 PM 3.52 6.52 2.40 5.88 N/A 4.98 1.68 5.40 8:00 PM 2.85 4.10 1.25 0.43 N/A 4.67 6.08 3.74 9:00 PM 2.47 3.74 1.69 2.44 N/A 2.18 N/A 3.11 10:00 PM 1.66 1.99 2.30 1.81 N/A 2.04 N/A 1.99 11:00 PM 1.24 1.27 0.60 2.82 N/A 0.94 N/A 1.23 Total 100 100 100 100 100 100 100 100 N/A implies insufficient data

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122 Table 8.2 Continued Trip Start Time SOV HOV Bus and Light Rail Metro, Subway and Heavy Rail Commuter Rail Walk Bicycle Total In an urban area but not in a MSA Midnight 0.70 0.20 N/A N/A N/A 1.18 N/A 0.41 1:00 AM 0.04 0.19 N/A N/A N/A N/A N/A 0.13 2:00 AM 0.17 0.08 N/A N/A N/A 0.27 N/A 0.14 3:00 AM N/A 0.03 N/A N/A N/A N/A N/A 0.02 4:00 AM 0.21 0.14 N/A N/A N/A N/A N/A 0.14 5:00 AM 1.31 0.27 N/A N/A N/A 0.72 N/A 0.57 6:00 AM 1.99 0.68 N/A N/A N/A 2.54 N/A 1.17 7:00 AM 3.71 1.88 N/A N/A N/A 4.10 4.78 2.54 8:00 AM 5.45 2.82 N/A N/A N/A 4.10 N/A 3.57 9:00 AM 7.08 6.31 N/A N/A N/A 5.16 3.88 6.35 10:00 AM 9.32 8.35 N/A N/A N/A 3.06 N/A 8.11 11:00 AM 9.23 7.47 N/A N/A N/A 6.91 4.35 7.77 Noon 8.91 10.27 N/A N/A N/A 9.20 8.38 9.84 1:00 PM 8.54 9.41 N/A N/A N/A 9.26 10.66 9.14 2:00 PM 8.33 8.48 N/A N/A N/A 4.26 5.85 8.28 3:00 PM 5.87 7.05 N/A N/A N/A 6.11 1.81 6.73 4:00 PM 7.22 7.12 N/A N/A N/A 7.77 6.53 7.19 5:00 PM 5.45 7.11 N/A N/A N/A 8.52 34.72 6.94 6:00 PM 4.51 6.95 N/A N/A N/A 7.21 7.61 6.32 7:00 PM 4.74 6.09 N/A N/A N/A 6.55 5.37 5.73 8:00 PM 2.42 4.54 N/A N/A N/A 6.43 6.05 4.13 9:00 PM 2.03 2.22 N/A N/A N/A 4.10 N/A 2.34 10:00 PM 1.69 1.36 N/A N/A N/A 1.81 N/A 1.46 11:00 PM 1.06 1.01 N/A N/A N/A 0.75 N/A 1.00 Total 100 100 N/A N/A N/A 100 100 100 N/A implies insufficient data

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123Figure 8.1 Distribution of Auto Person Trips by Trip Start Times 0.001.002.003.004.005.006.007.008.009.0010.00Midnight 12:59 am1:00 1:59 am2:00 2:59 am3:00 3:59 am4:00 4:59 am5:00 5:59 am6:00 6:59 am7:00 7:59 am8:00 8:59 am9:00 9:59 am10:00 10:59 am11:00 11:59 amNoon 12:59 pm1:00 1:59 pm2:00 2:59 pm3:00 3:59 pm4:00 4:59 pm5:00 5:59 pm6:00 6:59 pm7:00 7:59 pm8:00 8:59 pm9:00 9:59 pm10:00 10:59 pm11:00 11:59 pmTrip Start TimePercent Trips SOV on weekdays SOV on weekends HOV on weekdays HOV on weekends Figure 8.2 Distribution of Non-Motorized Person Trips by Trip Start Times 0.002.004.006.008.0010.0012.0014.0016.00Midnight 12:59 am1:00 1:59 am2:00 2:59 am3:00 3:59 am4:00 4:59 am5:00 5:59 am6:00 6:59 am7:00 7:59 am8:00 8:59 am9:00 9:59 am10:00 10:59 am11:00 11:59 amNoon 12:59 pm1:00 1:59 pm2:00 2:59 pm3:00 3:59 pm4:00 4:59 pm5:00 5:59 pm6:00 6:59 pm7:00 7:59 pm8:00 8:59 pm9:00 9:59 pm10:00 10:59 pm11:00 11:59 pmTrip Start TimePercent Trips Walk on weekdays Walk on weekends Bicycle on weekdays Bicycle on weekends

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124 from 4:00 pm until after 6:00 pm when the share declines. HOV on the other hand peaks earlier at 3:00 pm to 3:59 pm and is genera lly more than the SOV trips in the evenings. On weekends, the SOV trip reaches their peak level only after 10:00 am whereas HOV trips reach their peak level at noon and decreases after that. Share of HOV trips are more in the afternoon as compared to that in the morning. Figure 8.2 shows on weekdays where only 28% of the bicycle trips are made between noon to 4 pm, almost 41% are made on weekends between the four hours. However, another 26% of them are made from 4 pm to 6 pm as compared to the weekends where their share is only 22.4%. Share of walk tr ips are generally the same on weekdays and weekends. Figure 8.3 shows the distribution of pers on trips made on transit on weekdays and weekends by their trip start time in an urba n area of a population of 3 million and above and with heavy transit. While trips made on bus and light rail shows peaks at 7:00 am to 7:59 am and 3:00 pm to 3:59 pm on weekdays on weekends they peak between noon to 1:59 pm. Trips made on metro, subway and heav y rail are more on weekdays from 7:00 am to 8:59 am in morning and 4:00 pm to 7: 00 pm in evening whereas on weekends their major share lies only in eveni ngs from 3:00 pm to 6:59 pm. 8.3 Distribution of Vehicle Trips by Purpose Table 8.3 through 8.8 gives a weekday versus weekend comparison of share of vehicle trips made for each purpose by trip st art time for different urban area size. Each

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125table is reproduced graphically shown in Figures 8.4 to 8.15 following the tables. Home based other trips starts from 7:00 am in the morning and in the evening shows increases only in evening at 5:00 pm to 7:00 pm on weekdays. On weekends, they start increasing early in the morning and stabilize by 9:00 am. It peaks around noon on weekends and decreases afterwards. Non-home based trips peaks at lunch hours around noon. Figure 8.3 Distribution of Transit Person Trips by Trip Start Times 0.002.004.006.008.0010.0012.0014.00Midnight 12:59 am1:00 1:59 am2:00 2:59 am3:00 3:59 am4:00 4:59 am5:00 5:59 am6:00 6:59 am7:00 7:59 am8:00 8:59 am9:00 9:59 am10:00 10:59 am11:00 11:59 amNoon 12:59 pm1:00 1:59 pm2:00 2:59 pm3:00 3:59 pm4:00 4:59 pm5:00 5:59 pm6:00 6:59 pm7:00 7:59 pm8:00 8:59 pm9:00 9:59 pm10:00 10:59 pm11:00 11:59 pmTrip Start TimePercent Trips Bus and Light Rail on weekdays Bus and Light Rail on weekends Metro, Subway and Heavy Rail on weekdays Metro, Subway and Heavy Rail on weekends 8.4 Gender Differences Table 8.9 gives the distribution of person trips by gender and trip start time for various urban area sizes. Figures 8.16 and 8.17 give comparison of person trips by gender on weekdays and weekends. On weekdays, females have highest person trips from 7:00

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126 am to 8:59 am (about 14%) in morning a nd 3:00 pm to 5:59 pm (about 25%) in the evenings but on weekends peak occurs between noon to 2:59 pm (about 26.5%). The increase in female person trips starts from 10:00 am on the morning itself as opposed to the two peaks one in morning and the other in evening. Males show similar trends for peaks as females. Males start making their tr ips early in morning at 4:00 am on weekdays as opposed to the 5:00 am on weekends.

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127 Table 8.3 Percent of Vehicle Trips by Trip Purpose in an Urban MSA Size Less Than 250,000 Urban MSA Size of Less than 250,000 HBW HBOther NHB All Purposes Hour Beginning Weekdays WeekendsWeekdaysWeekendsW eekdaysWeekends Weekdays Weekends Midnight 0.27% 2.19%0.24%0.09%0.12%0.16% 0.20% 0.30% 1:00 AM 0.14% 0.00%0.05%0.56%0.17%0.00% 0.10% 0.35% 2:00 AM 0.15% 0.00%0.43%0.44%0.27%0.00% 0.32% 0.28% 3:00 AM 0.19% 0.31%0.05%0.00%0.03%0.00% 0.07% 0.03% 4:00 AM 0.89% 1.17%0.33%0.00%0.31%0.26% 0.45% 0.18% 5:00 AM 4.43% 2.25%0.85%0.08%0.81%0.20% 1.55% 0.31% 6:00 AM 9.93% 7.04%1.56%0.90%1.01%0.21% 3.07% 1.27% 7:00 AM 15.11% 9.48%6.45%3.45%5.14%3.15% 7.74% 3.92% 8:00 AM 6.45% 8.46%5.15%4.95%5.16%4.00% 5.44% 5.05% 9:00 AM 1.38% 4.49%5.10%7.81%6.32%7.19% 4.76% 7.30% 10:00 AM 2.36% 2.91%5.61%8.13%7.62%5.00% 5.65% 6.81% 11:00 AM 4.92% 5.62%6.11%9.92%10.51%10.93% 7.33% 9.92% Noon 5.15% 6.63%5.87%8.13%10.91%11.09% 7.39% 8.79% 1:00 PM 4.41% 0.27%5.71%9.28%7.97%7.00% 6.20% 7.76% 2:00 PM 4.32% 4.16%7.43%7.00%8.39%9.53% 7.12% 7.50% 3:00 PM 6.56% 12.50%7.71%7.19%7.00%6.83% 7.24% 7.56% 4:00 PM 10.01% 4.89%7.63%6.64%7.84%7.94% 8.17% 6.82% 5:00 PM 10.27% 9.08%8.89%6.94%7.86%5.64% 8.82% 6.75% 6:00 PM 3.69% 3.01%7.92%4.08%4.44%6.24% 5.92% 4.58% 7:00 PM 1.88% 4.26%6.14%4.66%3.73%6.69% 4.49% 5.18% 8:00 PM 1.89% 0.38%5.42%4.17%2.06%3.00% 3.60% 3.47% 9:00 PM 1.72% 2.23%2.74%3.26%1.12%3.05% 2.00% 3.09% 10:00 PM 1.80% 4.36%1.35%1.46%1.01%1.51% 1.33% 1.74% 11:00 PM 2.07% 4.33%1.25%0.87%0.20%0.39% 1.07% 1.05%

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Figure 8.4 Percent of Weekday Vehicle Trips by Hour by Trip Purpose in an Urban MSA Size Less Than 250,000 0%5%10%15%20%Midnight1:00 AM2:00 AM3:00 AM4:00 AM5:00 AM6:00 AM7:00 AM8:00 AM9:00 AM10:00 AM11:00 AMNoon1:00 PM2:00 PM3:00 PM4:00 PM5:00 PM6:00 PM7:00 PM8:00 PM9:00 PM10:00 PM11:00 PMBeginning HourPercent of Total Vehicle Trips HBW HBOther NHB

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Figure 8.5 Percent of Weekend Vehicle Trips by Hour by Trip Purpose in an Urban MSA Size Less Than 250,000 0%5%10%15%20%Midnight1:00 AM2:00 AM3:00 AM4:00 AM5:00 AM6:00 AM7:00 AM8:00 AM9:00 AM10:00 AM11:00 AMNoon1:00 PM2:00 PM3:00 PM4:00 PM5:00 PM6:00 PM7:00 PM8:00 PM9:00 PM10:00 PM11:00 PMBeginning HourPercent of Total Vehicle Trips HBW HBOther NHB

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130 Table 8.4 Percent of Vehicle Trips by Trip Purpose in an Urban MSA Size of 250,000 499,999 Urban MSA Size from 250,000 499,999 HBW HBOther NHB All Purposes Hour Beginning Weekdays WeekendsWeekdaysWeekendsW eekdaysWeekends Weekdays Weekends Midnight 1.21% 3.32%0.15%0.54%0.14%0.31% 0.36% 0.70% 1:00 AM 0.20% 0.00%0.05%0.31%0.06%0.37% 0.09% 0.31% 2:00 AM 0.34% 0.00%0.18%0.14%0.13%0.22% 0.19% 0.15% 3:00 AM 0.17% 2.59%0.06%0.00%0.03%0.00% 0.07% 0.21% 4:00 AM 1.69% 2.99%0.21%0.08%0.13%0.09% 0.50% 0.32% 5:00 AM 3.67% 3.40%0.54%0.17%0.21%0.05% 1.06% 0.39% 6:00 AM 10.02% 4.80%1.96%0.98%1.39%0.14% 3.42% 1.03% 7:00 AM 14.68% 8.99%6.46%2.45%4.53%0.25% 7.53% 2.32% 8:00 AM 7.47% 9.82%5.70%4.80%6.50%3.41% 6.32% 4.79% 9:00 AM 2.97% 7.09%5.52%6.97%6.10%4.01% 5.20% 6.09% 10:00 AM 1.62% 4.51%5.95%7.34%7.61%5.92% 5.63% 6.69% 11:00 AM 3.29% 3.10%6.77%8.53%9.39%8.51% 6.93% 8.09% Noon 5.66% 4.99%5.99%8.59%12.06%9.25% 7.94% 8.50% 1:00 PM 3.58% 3.10%6.01%7.99%9.40%8.26% 6.64% 7.68% 2:00 PM 5.32% 3.95%6.41%7.58%8.31%10.19% 6.82% 8.07% 3:00 PM 6.67% 6.66%8.14%6.43%7.27%9.86% 7.54% 7.47% 4:00 PM 8.57% 8.89%6.97%7.26%8.02%10.08% 7.63% 8.23% 5:00 PM 9.97% 2.65%7.22%8.61%6.75%7.41% 7.61% 7.78% 6:00 PM 3.98% 7.41%7.26%5.99%4.37%6.88% 5.63% 6.37% 7:00 PM 2.33% 2.43%5.61%4.88%3.07%5.53% 4.09% 4.88% 8:00 PM 1.63% 1.64%4.95%4.47%2.55%4.63% 3.48% 4.29% 9:00 PM 1.62% 4.30%4.24%3.35%1.15%2.58% 2.67% 3.19% 10:00 PM 2.56% 2.64%2.06%1.80%0.24%0.94% 1.55% 1.61% 11:00 PM 0.78% 0.73%1.60%0.75%0.62%1.10% 1.11% 0.85%

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Figure 8.6 Percent of Weekday Vehicle Trips by Hour by Trip Purpose in an Urban MSA Size of 250,000 499,999 0%5%10%15%20%Midnight1:00 AM2:00 AM3:00 AM4:00 AM5:00 AM6:00 AM7:00 AM8:00 AM9:00 AM10:00 AM11:00 AMNoon1:00 PM2:00 PM3:00 PM4:00 PM5:00 PM6:00 PM7:00 PM8:00 PM9:00 PM10:00 PM11:00 PMBeginning HourPercent of Total Vehicle Trips HBW HBOther NHB

PAGE 146

Figure 8.7 Percent of Weekend Vehicle Trips by Hour by Trip Purpose in an Urban MSA Size of 250,000 499,999 0%5%10%15%20%Midnight1:00 AM2:00 AM3:00 AM4:00 AM5:00 AM6:00 AM7:00 AM8:00 AM9:00 AM10:00 AM11:00 AMNoon1:00 PM2:00 PM3:00 PM4:00 PM5:00 PM6:00 PM7:00 PM8:00 PM9:00 PM10:00 PM11:00 PMBeginning HourPercent of Total Vehicle Trips HBW HBOther NHB

PAGE 147

133 Table 8.5 Percent of Vehicle Trips by Trip Purpose in an Urban MSA Size of 500,000 999,999 Urban MSA Size from 500,000 999,999 HBW HBOther NHB All Purposes Hour Beginning Weekdays WeekendsWeekdaysWeekendsW eekdaysWeekends Weekdays Weekends Midnight 0.57% 0.43%0.58%0.54%0.07%0.20% 0.44% 0.43% 1:00 AM 0.39% 0.00%0.18%0.53%0.02%0.17% 0.17% 0.39% 2:00 AM 0.23% 0.00%0.44%0.17%0.06%0.29% 0.27% 0.19% 3:00 AM 0.28% 1.99%0.11%0.38%0.02%0.17% 0.11% 0.43% 4:00 AM 0.96% 3.18%0.15%0.05%0.35%0.12% 0.39% 0.49% 5:00 AM 4.55% 2.70%0.63%0.47%0.66%0.06% 1.39% 0.55% 6:00 AM 10.13% 4.31%2.39%0.82%1.81%0.80% 3.68% 1.07% 7:00 AM 14.20% 11.60%7.08%2.34%5.84%1.00% 8.10% 2.64% 8:00 AM 8.42% 7.60%5.07%4.62%5.19%2.11% 5.74% 4.12% 9:00 AM 2.91% 4.45%5.18%7.18%4.70%5.07% 4.60% 6.37% 10:00 AM 1.58% 4.60%6.00%7.93%6.79%8.34% 5.42% 7.78% 11:00 AM 2.53% 2.03%4.86%7.29%9.27%11.16% 5.87% 7.98% Noon 3.73% 2.66%6.47%9.61%11.93%12.35% 7.75% 9.85% 1:00 PM 3.68% 6.76%5.95%7.44%7.82%10.64% 6.12% 8.27% 2:00 PM 4.36% 9.74%6.56%8.17%7.88%10.14% 6.56% 8.82% 3:00 PM 7.25% 8.58%8.07%7.07%7.19%6.88% 7.60% 7.11% 4:00 PM 8.77% 4.02%7.91%7.08%9.44%7.52% 8.57% 6.96% 5:00 PM 9.79% 3.46%7.95%7.90%6.31%7.33% 7.78% 7.40% 6:00 PM 5.28% 7.35%7.69%5.41%6.13%5.04% 6.69% 5.44% 7:00 PM 2.71% 2.24%6.39%5.53%3.16%3.78% 4.57% 4.79% 8:00 PM 1.68% 4.08%4.45%3.67%2.71%3.30% 3.37% 3.59% 9:00 PM 2.18% 2.86%3.20%2.70%1.58%1.14% 2.45% 2.27% 10:00 PM 2.25% 3.83%2.02%1.58%0.80%0.95% 1.65% 1.56% 11:00 PM 1.57% 1.52%0.70%1.53%0.27%1.44% 0.72% 1.50%

PAGE 148

Figure 8.8 Percent of Weekday Vehicle Trips by Hour by Trip Purpose in an Urban MSA Size of 500,000 999,999 0%5%10%15%20%Midnight1:00 AM2:00 AM3:00 AM4:00 AM5:00 AM6:00 AM7:00 AM8:00 AM9:00 AM10:00 AM11:00 AMNoon1:00 PM2:00 PM3:00 PM4:00 PM5:00 PM6:00 PM7:00 PM8:00 PM9:00 PM10:00 PM11:00 PMBeginning HourPercent of Total Vehicle Trips HBW HBOther NHB

PAGE 149

Figure 8.9 Percent of Weekend Vehicle Trips by Hour by Trip Purpose in an Urban MSA Size of 500,000 999,999 0%5%10%15%20%Midnight1:00 AM2:00 AM3:00 AM4:00 AM5:00 AM6:00 AM7:00 AM8:00 AM9:00 AM10:00 AM11:00 AMNoon1:00 PM2:00 PM3:00 PM4:00 PM5:00 PM6:00 PM7:00 PM8:00 PM9:00 PM10:00 PM11:00 PMBeginning HourPercent of Total Vehicle Trips HBW HBOther NHB

PAGE 150

136 Table 8.6 Percent of Vehicle Trips by Trip Purpose in an Urban MSA Size of 1,000,000 2,999,999 Urban MSA Size of 1,000,000 2,999,999 HBW HBOther NHB All Purposes Hour Beginning Weekdays Weekends WeekdaysWeekends WeekdaysWeekendsWeekdays Weekends Midnight 0.60% 1.07% 0.37%0.50%0.18%0.42%0.36% 0.52% 1:00 AM 0.42% 1.11% 0.23%0.34%0.09%0.33%0.22% 0.40% 2:00 AM 0.26% 0.43% 0.23%0.35%0.01%0.22%0.16% 0.31% 3:00 AM 0.28% 0.65% 0.10%0.16%0.20%0.31%0.17% 0.24% 4:00 AM 0.89% 2.08% 0.21%0.21%0.33%0.71%0.43% 0.50% 5:00 AM 4.37% 4.11% 0.63%0.37%0.61%0.42%1.43% 0.68% 6:00 AM 11.21% 4.60% 2.57%1.03%1.68%0.81%4.16% 1.23% 7:00 AM 15.25% 8.22% 5.65%2.41%4.16%1.88%7.23% 2.72% 8:00 AM 7.18% 8.58% 5.47%4.16%5.38%3.22%5.82% 4.21% 9:00 AM 2.73% 4.49% 4.96%6.32%5.23%4.98%4.56% 5.81% 10:00 AM 1.93% 4.62% 5.37%7.78%7.21%8.56%5.22% 7.76% 11:00 AM 2.39% 4.15% 6.03%8.80%9.79%8.13%6.44% 8.25% Noon 4.34% 5.82% 5.78%8.17%11.13%11.33%7.20% 8.92% 1:00 PM 3.83% 4.90% 5.57%7.60%8.28%10.70%6.05% 8.35% 2:00 PM 4.38% 4.84% 6.10%7.47%7.91%10.20%6.32% 8.08% 3:00 PM 7.25% 5.19% 7.12%8.13%8.96%7.99%7.72% 7.85% 4:00 PM 9.35% 8.13% 8.39%7.55%8.19%8.61%8.51% 7.91% 5:00 PM 10.65% 6.25% 8.76%7.08%7.88%6.38%8.87% 6.81% 6:00 PM 4.95% 4.48% 8.52%6.12%4.64%5.75%6.51% 5.87% 7:00 PM 1.83% 4.31% 6.45%4.37%3.53%3.07%4.51% 3.98% 8:00 PM 1.38% 2.20% 4.99%3.68%2.09%2.14%3.28% 3.10% 9:00 PM 1.52% 1.92% 3.60%3.86%1.64%2.06%2.52% 3.17% 10:00 PM 1.51% 4.99% 2.04%2.04%0.42%1.33%1.42% 2.04% 11:00 PM 1.51% 2.86% 0.85%1.51%0.47%0.44%0.87% 1.29%

PAGE 151

Figure 8.10 Percent of Weekday Vehicle Trips by Hour by Trip Purpose in an Urban MSA Size of 1,000,000 2,999,999 0%5%10%15%20%Midnight1:00 AM2:00 AM3:00 AM4:00 AM5:00 AM6:00 AM7:00 AM8:00 AM9:00 AM10:00 AM11:00 AMNoon1:00 PM2:00 PM3:00 PM4:00 PM5:00 PM6:00 PM7:00 PM8:00 PM9:00 PM10:00 PM11:00 PMBeginning HourPercent of Total Vehicle Trips HBW HBOther NHB

PAGE 152

Figure 8.11 Percent of Weekend Vehicle Trips by Hour by Trip Purpose in an Urban MSA Size of 1,000,000 2,999,999 0%5%10%15%20%Midnight1:00 AM2:00 AM3:00 AM4:00 AM5:00 AM6:00 AM7:00 AM8:00 AM9:00 AM10:00 AM11:00 AMNoon1:00 PM2:00 PM3:00 PM4:00 PM5:00 PM6:00 PM7:00 PM8:00 PM9:00 PM10:00 PM11:00 PMBeginning HourPercent of Total Vehicle Trips HBW HBOther NHB

PAGE 153

139 Table 8.7 Percent of Vehicle Trips by Trip Purpose in an Urban MSA Size of 3 Million or More Urban MSA Size of 3 million or more HBW HBOther NHB All Purposes Hour Beginning Weekdays WeekendsWeekdaysWeekendsW eekdaysWeekends Weekdays Weekends Midnight 0.90% 2.57%0.59%0.69%0.12%0.42% 0.51% 0.73% 1:00 AM 0.25% 1.53%0.22%0.31%0.13%0.25% 0.20% 0.37% 2:00 AM 0.19% 0.66%0.08%0.23%0.03%0.07% 0.09% 0.21% 3:00 AM 0.11% 0.46%0.06%0.07%0.00%0.15% 0.05% 0.12% 4:00 AM 1.05% 0.94%0.19%0.12%0.45%0.44% 0.49% 0.28% 5:00 AM 4.44% 2.31%0.89%0.24%0.62%0.09% 1.54% 0.35% 6:00 AM 9.91% 7.98%2.09%1.10%1.50%0.77% 3.53% 1.49% 7:00 AM 14.11% 9.02%6.10%2.51%4.70%1.76% 7.31% 2.73% 8:00 AM 9.59% 7.58%6.37%4.66%5.75%3.31% 6.83% 4.48% 9:00 AM 3.98% 5.84%5.31%6.59%6.00%5.42% 5.26% 6.22% 10:00 AM 1.81% 2.56%5.86%9.00%7.15%9.19% 5.44% 8.62% 11:00 AM 2.05% 4.62%6.01%8.30%9.18%10.28% 6.21% 8.62% Noon 3.28% 3.22%5.15%8.39%10.76%10.43% 6.55% 8.62% 1:00 PM 3.04% 5.40%5.67%7.48%9.59%9.47% 6.38% 7.90% 2:00 PM 4.06% 7.18%6.58%7.21%8.26%10.74% 6.59% 8.21% 3:00 PM 7.05% 5.22%7.10%7.69%8.41%8.50% 7.50% 7.75% 4:00 PM 8.73% 6.13%7.16%7.41%7.31%6.72% 7.53% 7.12% 5:00 PM 10.98% 7.84%7.74%5.92%7.26%6.16% 8.25% 6.11% 6:00 PM 6.09% 5.01%8.03%6.43%4.56%5.62% 6.51% 6.09% 7:00 PM 2.42% 2.97%6.93%5.48%3.29%3.32% 4.83% 4.69% 8:00 PM 1.39% 2.73%5.00%3.91%2.07%2.72% 3.32% 3.49% 9:00 PM 1.75% 1.88%3.61%3.24%1.43%2.38% 2.53% 2.90% 10:00 PM 1.58% 3.39%1.92%1.82%1.01%1.20% 1.56% 1.76% 11:00 PM 1.22% 2.97%1.33%1.21%0.41%0.58% 1.02% 1.15%

PAGE 154

Figure 8.12 Percent of Weekday Vehicle Trips by Hour by Trip Purpose in an Urban MSA Size of 3 Million or More 0%5%10%15%20%Midnight1:00 AM2:00 AM3:00 AM4:00 AM5:00 AM6:00 AM7:00 AM8:00 AM9:00 AM10:00 AM11:00 AMNoon1:00 PM2:00 PM3:00 PM4:00 PM5:00 PM6:00 PM7:00 PM8:00 PM9:00 PM10:00 PM11:00 PMBeginning HourPercent of Total Vehicle Trips HBW HBOther NHB

PAGE 155

Figure 8.13 Percent of Weekend Vehicle Trips by Hour by Trip Purpose in an Urban MSA Size of 3 Million or More 0%5%10%15%20%Midnight1:00 AM2:00 AM3:00 AM4:00 AM5:00 AM6:00 AM7:00 AM8:00 AM9:00 AM10:00 AM11:00 AMNoon1:00 PM2:00 PM3:00 PM4:00 PM5:00 PM6:00 PM7:00 PM8:00 PM9:00 PM10:00 PM11:00 PMBeginning HourPercent of Total Vehicle Trips HBW HBOther NHB

PAGE 156

142 Table 8.8 Percent of Vehicle Trips by Trip Purpose in an Urban Area but Not in an MSA In an urban area but not in an MSA HBW HBOther NHB All Purposes Hour Beginning Weekdays Weekends WeekdaysWeekends WeekdaysWeekendsWeekdays Weekends Midnight 1.06% 1.96% 0.21%0.32%0.05%0.22%0.33% 0.43% 1:00 AM 0.15% 0.00% 0.23%0.28%0.00%0.00%0.14% 0.17% 2:00 AM 0.22% 0.61% 0.17%0.10%0.01%0.00%0.13% 0.11% 3:00 AM 0.18% 0.00% 0.08%0.00%0.14%0.00%0.12% 0.00% 4:00 AM 1.36% 1.12% 0.22%0.11%0.35%0.05%0.51% 0.18% 5:00 AM 3.61% 5.81% 0.66%0.41%0.69%0.47%1.29% 0.87% 6:00 AM 9.68% 7.36% 1.80%0.91%2.02%0.60%3.51% 1.34% 7:00 AM 14.36% 5.44% 6.28%2.64%4.82%1.97%7.46% 2.67% 8:00 AM 5.87% 9.22% 5.89%4.13%5.27%2.52%5.69% 4.08% 9:00 AM 2.74% 1.53% 6.61%7.07%6.39%7.23%5.75% 6.69% 10:00 AM 1.60% 6.40% 6.67%9.48%7.69%8.49%5.95% 8.93% 11:00 AM 3.12% 4.42% 6.84%8.04%9.89%10.75%7.05% 8.53% Noon 6.92% 6.72% 6.04%9.11%11.46%10.87%7.98% 9.42% 1:00 PM 5.44% 5.38% 6.26%8.11%8.04%11.54%6.65% 8.88% 2:00 PM 3.05% 8.62% 6.35%8.21%8.22%8.50%6.27% 8.32% 3:00 PM 6.77% 6.19% 7.13%6.44%8.34%7.20%7.43% 6.64% 4:00 PM 9.38% 5.11% 7.33%7.48%8.18%7.74%8.02% 7.40% 5:00 PM 10.79% 3.47% 7.86%7.03%6.82%5.45%8.12% 6.27% 6:00 PM 4.67% 4.42% 7.37%5.93%4.18%5.30%5.78% 5.62% 7:00 PM 2.76% 4.44% 5.76%5.37%2.65%5.18%4.16% 5.24% 8:00 PM 1.49% 1.86% 4.76%3.93%2.56%2.83%3.37% 3.43% 9:00 PM 2.09% 1.92% 3.38%2.54%1.15%1.84%2.41% 2.28% 10:00 PM 1.40% 4.37% 1.44%1.34%0.44%0.87%1.11% 1.45% 11:00 PM 1.26% 3.64% 0.65%1.03%0.62%0.37%0.76% 1.05%

PAGE 157

Figure 8.14 Percent of Weekday Vehicle Trips by Hour by Trip Purpose in an Urban Area but Not in an MSA 0%5%10%15%20%Midnight1:00 AM2:00 AM3:00 AM4:00 AM5:00 AM6:00 AM7:00 AM8:00 AM9:00 AM10:00 AM11:00 AMNoon1:00 PM2:00 PM3:00 PM4:00 PM5:00 PM6:00 PM7:00 PM8:00 PM9:00 PM10:00 PM11:00 PMBeginning HourPercent of Total Vehicle Trips HBW HBOther NHB

PAGE 158

Figure 8.15 Percent of Weekend Vehicle Trips by Hour by Trip Purpose in an Urban Area but Not in an MSA 0%5%10%15%20%Midnight1:00 AM2:00 AM3:00 AM4:00 AM5:00 AM6:00 AM7:00 AM8:00 AM9:00 AM10:00 AM11:00 AMNoon1:00 PM2:00 PM3:00 PM4:00 PM5:00 PM6:00 PM7:00 PM8:00 PM9:00 PM10:00 PM11:00 PMBeginning HourPercent of Total Vehicle Trips HBW HBOther NHB

PAGE 159

145 Table 8.9 Percent of Person Trips by Gender and Start Time Weekdays Weekends Trip Start Time Male Female All Male Female All In an urban area with MSA of less than 250,000 Midnight 0.29 0.12 0.20 0.41 0.27 0.34 1:00 AM 0.16 0.05 0.10 0.32 0.06 0.19 2:00 AM 0.27 0.17 0.22 0.34 N/A 0.17 3:00 AM 0.09 N/A 0.04 N/A 0.03 0.02 4:00 AM 0.56 0.17 0.35 0.20 N/A 0.10 5:00 AM 1.73 0.85 1.27 0.61 0.52 0.57 6:00 AM 3.44 1.78 2.56 0.94 0.79 0.87 7:00 AM 7.94 8.17 8.06 3.38 2.30 2.84 8:00 AM 4.92 5.23 5.09 5.62 4.38 5.00 9:00 AM 3.70 4.60 4.18 7.32 6.50 6.91 10:00 AM 5.41 5.82 5.62 6.55 7.18 6.86 11:00 AM 5.95 7.08 6.55 9.53 9.36 9.44 Noon 7.17 6.97 7.06 8.31 7.80 8.05 1:00 PM 6.00 6.05 6.03 7.41 9.29 8.35 2:00 PM 7.13 8.01 7.59 7.48 7.48 7.48 3:00 PM 7.74 8.70 8.25 6.02 7.70 6.87 4:00 PM 7.14 8.28 7.74 6.61 7.80 7.21 5:00 PM 8.85 7.90 8.35 7.33 7.17 7.25 6:00 PM 6.34 6.50 6.42 5.80 5.39 5.59 7:00 PM 5.78 5.71 5.74 4.80 5.71 5.26 8:00 PM 4.14 3.93 4.03 4.22 4.71 4.47 9:00 PM 2.40 1.80 2.08 3.40 3.39 3.40 10:00 PM 1.94 1.39 1.65 2.28 1.25 1.76 11:00 PM 0.92 0.71 0.81 1.14 0.90 1.02 Total 100% 100% 100% 100% 100% 100% N/A implies insufficient data

PAGE 160

146 Table 8.9 Continued Weekdays Weekends Trip Start Time Male Female All Male Female All In an urban area with MSA of 250,000 499,999 Midnight 0.46 0.28 0.36 0.71 0.36 0.54 1:00 AM 0.12 0.11 0.12 0.27 0.03 0.15 2:00 AM 0.19 0.14 0.16 N/A 0.22 0.11 3:00 AM 0.06 0.05 0.05 0.09 0.29 0.19 4:00 AM 0.46 0.24 0.34 0.28 0.03 0.15 5:00 AM 1.40 0.45 0.91 0.28 0.23 0.25 6:00 AM 3.62 2.11 2.83 0.67 0.63 0.65 7:00 AM 7.14 7.96 7.57 2.21 1.61 1.91 8:00 AM 5.52 5.88 5.71 4.81 3.53 4.18 9:00 AM 4.57 4.64 4.60 5.81 5.03 5.42 10:00 AM 5.14 5.22 5.18 6.63 6.86 6.74 11:00 AM 5.70 6.52 6.13 9.24 9.10 9.17 Noon 7.00 6.87 6.93 8.90 8.84 8.87 1:00 PM 5.71 6.54 6.15 7.69 7.50 7.60 2:00 PM 6.74 6.77 6.76 8.23 8.14 8.18 3:00 PM 8.33 8.50 8.42 6.39 7.66 7.02 4:00 PM 7.12 8.06 7.61 7.93 7.83 7.88 5:00 PM 7.50 8.11 7.82 7.39 7.71 7.55 6:00 PM 6.97 6.73 6.85 6.63 7.47 7.04 7:00 PM 5.98 4.91 5.42 5.06 5.75 5.40 8:00 PM 4.39 4.23 4.30 4.46 4.49 4.48 9:00 PM 2.89 3.20 3.05 3.56 3.39 3.47 10:00 PM 1.61 1.52 1.56 1.93 2.32 2.12 11:00 PM 1.39 0.95 1.16 0.84 0.99 0.91 Total 100% 100% 100% 100% 100% 100% N/A implies insufficient data

PAGE 161

147 Table 8.9 Continued Weekdays Weekends Trip Start Time Male Female All Male Female All In an urban area with MSA of 500,000 999,999 Midnight 0.21 0.55 0.39 0.29 0.38 0.34 1:00 AM 0.27 0.22 0.24 0.36 0.23 0.29 2:00 AM 0.40 0.29 0.34 0.23 0.09 0.16 3:00 AM 0.15 0.09 0.12 0.38 0.14 0.25 4:00 AM 0.41 0.24 0.32 0.54 N/A 0.25 5:00 AM 1.36 0.90 1.12 0.48 0.26 0.36 6:00 AM 3.92 2.64 3.23 0.97 0.64 0.79 7:00 AM 7.68 8.52 8.13 2.53 1.49 1.98 8:00 AM 5.42 5.56 5.49 3.90 3.81 3.85 9:00 AM 4.37 4.17 4.27 5.75 6.78 6.30 10:00 AM 4.82 5.33 5.09 9.06 6.89 7.90 11:00 AM 5.72 5.47 5.58 7.40 8.29 7.87 Noon 7.75 7.17 7.44 10.25 9.25 9.72 1:00 PM 4.98 5.80 5.42 7.60 8.66 8.17 2:00 PM 6.88 7.40 7.16 8.11 8.91 8.54 3:00 PM 8.01 8.67 8.36 6.07 7.05 6.59 4:00 PM 7.65 8.98 8.36 6.84 7.42 7.15 5:00 PM 7.41 7.35 7.38 7.03 7.78 7.43 6:00 PM 7.70 7.22 7.44 6.85 6.43 6.63 7:00 PM 5.44 4.99 5.20 6.51 5.90 6.19 8:00 PM 4.19 3.65 3.90 3.74 4.04 3.90 9:00 PM 2.52 2.67 2.60 2.24 2.71 2.49 10:00 PM 1.80 1.66 1.72 1.51 1.84 1.68 11:00 PM 0.97 0.47 0.70 1.35 1.01 1.17 Total 100% 100% 100% 100% 100% 100% N/A implies insufficient data

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148 Table 8.9 Continued Weekdays Weekends Trip Start Time Male Female All Male Female All In an urban area with MSA of 1,000,000 2,999,999 Midnight 0.47 0.29 0.38 0.49 0.53 0.51 1:00 AM 0.23 0.19 0.21 0.45 0.14 0.29 2:00 AM 0.22 0.14 0.18 0.33 0.21 0.27 3:00 AM 0.16 0.06 0.11 0.16 0.17 0.16 4:00 AM 0.48 0.20 0.34 0.49 0.18 0.33 5:00 AM 1.49 0.60 1.03 0.63 0.36 0.50 6:00 AM 4.40 2.89 3.62 1.16 0.61 0.88 7:00 AM 6.84 7.38 7.12 3.00 2.09 2.54 8:00 AM 5.53 6.43 5.99 4.78 3.43 4.09 9:00 AM 4.14 4.04 4.09 5.74 5.41 5.57 10:00 AM 4.73 5.01 4.88 7.39 8.18 7.79 11:00 AM 5.76 6.32 6.05 7.71 7.54 7.62 Noon 6.59 7.12 6.87 8.80 9.15 8.98 1:00 PM 5.71 6.00 5.86 7.77 8.56 8.17 2:00 PM 6.54 6.96 6.76 8.39 8.57 8.48 3:00 PM 8.45 8.55 8.50 7.13 7.76 7.45 4:00 PM 7.96 8.39 8.19 7.23 8.47 7.86 5:00 PM 8.82 8.89 8.86 6.88 7.02 6.95 6:00 PM 6.94 6.56 6.74 6.45 6.92 6.69 7:00 PM 5.24 5.24 5.24 4.57 4.05 4.31 8:00 PM 3.91 3.79 3.85 3.62 3.67 3.64 9:00 PM 2.68 2.96 2.82 3.53 3.78 3.66 10:00 PM 1.65 1.37 1.51 1.85 1.95 1.90 11:00 PM 1.06 0.61 0.83 1.43 1.25 1.34 Total 100% 100% 100% 100% 100% 100%

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149 Table 8.9 Continued Weekdays Weekends Trip Start Time Male Female All Male Female All In an urban area with MSA of 3 million or more w/o heavy transit Midnight 0.58 0.32 0.44 0.48 0.36 0.42 1:00 AM 0.23 0.16 0.19 0.49 0.18 0.34 2:00 AM 0.14 0.12 0.13 0.26 0.15 0.21 3:00 AM 0.07 0.08 0.07 0.10 0.04 0.07 4:00 AM 0.60 0.14 0.36 0.27 0.06 0.17 5:00 AM 1.70 0.68 1.17 0.34 0.10 0.22 6:00 AM 3.97 2.45 3.18 1.19 0.88 1.04 7:00 AM 7.20 6.65 6.91 2.30 1.43 1.86 8:00 AM 6.60 6.72 6.66 3.73 3.30 3.52 9:00 AM 4.64 5.12 4.89 6.19 6.81 6.50 10:00 AM 4.91 5.42 5.18 8.34 8.37 8.35 11:00 AM 5.93 6.48 6.22 8.12 8.29 8.20 Noon 5.91 6.26 6.09 8.95 9.97 9.46 1:00 PM 5.83 6.20 6.02 7.71 8.16 7.93 2:00 PM 7.15 7.59 7.38 8.27 8.12 8.20 3:00 PM 8.23 9.11 8.69 7.94 7.97 7.95 4:00 PM 7.24 7.71 7.48 7.55 8.49 8.02 5:00 PM 8.16 8.22 8.19 5.71 6.10 5.91 6:00 PM 6.64 6.97 6.81 6.53 6.71 6.62 7:00 PM 5.50 5.26 5.37 4.96 5.16 5.06 8:00 PM 3.51 3.44 3.47 4.38 3.98 4.18 9:00 PM 2.62 2.62 2.62 3.08 2.79 2.94 10:00 PM 1.60 1.37 1.48 1.95 1.59 1.77 11:00 PM 1.04 0.92 0.97 1.15 0.97 1.06 Total 100% 100% 100% 100% 100% 100%

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150 Table 8.9 Continued Weekdays Weekends Trip Start Time Male Female All Male Female All In an urban area with MSA of 3 million or more w/ heavy transit Midnight 0.45 0.42 0.44 1.32 0.51 0.91 1:00 AM 0.17 0.17 0.17 0.43 0.47 0.45 2:00 AM 0.09 0.05 0.07 0.28 0.08 0.18 3:00 AM 0.05 0.02 0.04 0.18 N/A 0.09 4:00 AM 0.69 0.16 0.41 0.27 0.15 0.21 5:00 AM 1.51 0.69 1.08 0.73 0.25 0.48 6:00 AM 3.39 1.99 2.66 1.49 1.07 1.28 7:00 AM 8.01 7.46 7.73 2.55 1.92 2.23 8:00 AM 6.37 7.74 7.08 4.43 3.76 4.09 9:00 AM 4.19 4.53 4.37 4.71 4.77 4.74 10:00 AM 4.43 5.11 4.79 7.30 8.07 7.69 11:00 AM 4.50 6.48 5.53 8.89 7.34 8.10 Noon 6.22 6.34 6.28 7.41 9.43 8.43 1:00 PM 5.61 6.57 6.10 7.99 8.10 8.05 2:00 PM 6.68 7.68 7.20 8.46 9.32 8.90 3:00 PM 7.60 8.68 8.16 7.48 8.38 7.94 4:00 PM 7.16 7.31 7.24 6.26 7.75 7.01 5:00 PM 8.70 8.15 8.41 6.45 6.95 6.70 6:00 PM 7.27 6.82 7.04 6.60 7.42 7.01 7:00 PM 5.98 5.33 5.64 5.56 5.24 5.40 8:00 PM 4.53 3.45 3.97 4.28 3.22 3.74 9:00 PM 3.13 2.65 2.88 3.37 2.84 3.11 10:00 PM 2.14 1.59 1.85 2.33 1.66 1.99 11:00 PM 1.13 0.60 0.86 1.20 1.30 1.25 Total 100% 100% 100% 100% 100% 100% N/A implies insufficient data

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151 Table 8.9 Continued Weekdays Weekends Trip Start Time Male Female All Male Female All In an urban area but not in a MSA Midnight 0.48 0.27 0.37 0.61 0.21 0.41 1:00 AM 0.24 0.19 0.21 0.05 0.21 0.13 2:00 AM 0.15 0.10 0.12 0.17 0.11 0.14 3:00 AM 0.13 0.05 0.09 0.03 N/A 0.02 4:00 AM 0.60 0.21 0.40 0.15 0.13 0.14 5:00 AM 1.29 0.86 1.07 0.79 0.35 0.57 6:00 AM 3.38 2.43 2.90 1.75 0.60 1.17 7:00 AM 7.75 7.64 7.69 2.94 2.15 2.54 8:00 AM 5.73 5.78 5.76 4.12 3.03 3.57 9:00 AM 5.17 4.88 5.02 5.83 6.85 6.34 10:00 AM 5.16 5.85 5.52 8.49 7.73 8.11 11:00 AM 6.02 7.25 6.65 8.35 7.20 7.77 Noon 7.33 6.68 7.00 8.33 11.32 9.84 1:00 PM 6.09 6.17 6.13 8.35 9.91 9.13 2:00 PM 6.58 7.26 6.93 8.50 8.12 8.31 3:00 PM 8.14 9.11 8.64 6.38 7.07 6.73 4:00 PM 7.57 7.92 7.75 6.67 7.69 7.19 5:00 PM 8.17 8.17 8.17 7.14 6.73 6.93 6:00 PM 6.13 6.06 6.09 6.69 5.95 6.32 7:00 PM 4.53 4.88 4.71 6.09 5.37 5.73 8:00 PM 4.20 4.26 4.23 3.79 4.47 4.13 9:00 PM 2.90 2.60 2.75 1.99 2.68 2.34 10:00 PM 1.33 0.64 0.97 1.52 1.39 1.45 11:00 PM 0.91 0.75 0.83 1.27 0.73 1.00 Total 100% 100% 100% 100% 100% 100% N/A implies insufficient data

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152Figure 8.16 Distribution of Person Trips by Gender and Trip Start Time on Weekdays 0.001.002.003.004.005.006.007.008.009.0010.00Midnight 12:59 am1:00 1:59 am2:00 2:59 am3:00 3:59 am4:00 4:59 am5:00 5:59 am6:00 6:59 am7:00 7:59 am8:00 8:59 am9:00 9:59 am10:00 10:59 am11:00 11:59 amNoon 12:59 pm1:00 1:59 pm2:00 2:59 pm3:00 3:59 pm4:00 4:59 pm5:00 5:59 pm6:00 6:59 pm7:00 7:59 pm8:00 8:59 pm9:00 9:59 pm10:00 10:59 pm11:00 11:59 pmTrip Start TimePercent Trips Male Female Figure 8.17 Distribution of Person Trips by Gender and Trip Start Time on Weekends 0.001.002.003.004.005.006.007.008.009.0010.00Midnight 12:59 am1:00 1:59 am2:00 2:59 am3:00 3:59 am4:00 4:59 am5:00 5:59 am6:00 6:59 am7:00 7:59 am8:00 8:59 am9:00 9:59 am10:00 10:59 am11:00 11:59 amNoon 12:59 pm1:00 1:59 pm2:00 2:59 pm3:00 3:59 pm4:00 4:59 pm5:00 5:59 pm6:00 6:59 pm7:00 7:59 pm8:00 8:59 pm9:00 9:59 pm10:00 10:59 pm11:00 11:59 pmTrip Start TimePercent Trips Male Female

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153 8.5 Occupancies by Purpose and Trip Start Time Table 8.10 gives the comparison of occ upancies on weekdays and weekends by trip purpose and trip start time. Shopping trips that had averag e occupancies of 1.58 on weekdays reach maximum value of 2.04 at 9: 00 pm to 9:59 pm on weekdays as opposed to the 2.71 reached earlier at 6:00 pm to 6: 59 pm but on weekends. Social recreational trips which had maximum occupancy of 2.11 on weekdays at 11:00 pm -11:59 pm had a higher 2.29 occupancy much earlier at 1: 00 pm to 1:59 pm in afternoon. Figure 8.18 shows the change in occupancies that occurred on weekends from weekdays in all urban areas. Home based shopping trips show the ma ximum increase in occupancies in night at 10:00 pm to 10:59 pm followed by 6:00 pm to 6:59 pm in evening. Except early in morning and late at night, a ll the non-home based trips show an increase in occupancy by almost 0.66. Social recreational trips and other home based tr ips show an increase of 0.40 with maximum increase being 0.71 at 1:00 pm to 1:59 pm and 0.73 at noon to 12:59 pm respectively.

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154 Table 8.10 Average Occupancy Rate by Time of Day and Purpose Trip Start Time HBW HBShop HBSoc HBOther NHB Total Weekdays Midnight 1.03 1.38 2.25 1.20 1.53 1.33 1:00 AM 1.14 1.18 2.48 1.19 1.62 1.41 2:00 AM 1.05 1.55 2.06 1.75 2.77 1.73 3:00 AM 1.01 1.17 1.12 1.41 2.46 1.47 4:00 AM 1.29 1.26 1.03 1.24 1.19 1.24 5:00 AM 1.09 1.01 1.10 1.63 1.31 1.17 6:00 AM 1.10 1.37 1.13 1.69 1.43 1.22 7:00 AM 1.08 1.25 1.20 1.78 1.25 1.25 8:00 AM 1.08 1.29 1.43 1.62 1.40 1.32 9:00 AM 1.06 1.40 1.60 1.45 1.35 1.33 10:00 AM 1.11 1.74 1.73 1.47 1.46 1.48 11:00 AM 1.07 1.60 1.76 1.47 1.47 1.46 Noon 1.07 1.61 1.73 1.61 1.49 1.48 1:00 PM 1.04 1.52 1.58 1.56 1.46 1.44 2:00 PM 1.10 1.63 1.94 1.66 1.55 1.52 3:00 PM 1.13 1.66 1.85 1.69 1.60 1.49 4:00 PM 1.16 1.52 1.87 1.63 1.47 1.42 5:00 PM 1.12 1.55 1.94 1.76 1.53 1.45 6:00 PM 1.07 1.50 1.81 1.62 1.77 1.51 7:00 PM 1.17 1.69 1.69 1.73 1.71 1.61 8:00 PM 1.05 1.56 2.10 1.67 1.84 1.69 9:00 PM 1.04 2.04 1.82 1.70 1.98 1.65 10:00 PM 1.05 1.73 1.83 1.47 2.09 1.49 11:00 PM 1.06 1.34 2.11 1.63 2.07 1.62 Total 1.10 1.58 1.79 1.62 1.51 1.43

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155 Table 8.10 Continued Trip Start Time HBW HBShop HBSoc HBOther NHB Total Weekends Midnight 1.34 1.71 2.34 1.68 1.75 1.75 1:00 AM 1.00 2.00 1.99 1.34 2.40 1.62 2:00 AM 1.00 N/A 2.13 1.87 2.26 1.84 3:00 AM 1.04 1.00 1.74 1.00 1.86 1.35 4:00 AM 1.00 1.00 1.25 1.42 1.29 1.24 5:00 AM 1.07 1.05 1.17 1.65 1.11 1.24 6:00 AM 1.02 1.99 2.13 2.39 1.46 1.59 7:00 AM 1.05 1.41 1.63 1.58 1.75 1.45 8:00 AM 1.15 1.99 1.95 1.81 1.80 1.73 9:00 AM 1.11 1.76 2.00 1.85 2.03 1.84 10:00 AM 1.07 1.84 2.14 1.92 2.15 1.95 11:00 AM 1.07 1.95 2.17 1.73 2.09 1.94 Noon 1.15 1.92 2.19 2.34 2.07 2.09 1:00 PM 1.09 1.65 2.29 1.99 2.19 1.99 2:00 PM 1.11 2.01 2.23 2.00 2.14 2.01 3:00 PM 1.04 2.33 2.24 1.78 2.23 2.03 4:00 PM 1.32 1.93 2.07 1.90 2.14 1.95 5:00 PM 1.16 1.92 2.30 1.88 2.09 1.95 6:00 PM 1.10 2.71 2.22 2.09 2.24 2.16 7:00 PM 1.24 2.06 2.24 2.06 2.42 2.11 8:00 PM 1.06 2.16 2.23 2.17 2.38 2.17 9:00 PM 1.04 2.14 2.22 2.28 2.27 2.15 10:00 PM 1.19 3.80 1.91 1.94 1.98 1.95 11:00 PM 1.27 1.61 2.18 1.90 2.33 1.89 Total 1.12 2.00 2.16 1.95 2.12 1.96

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Figure 8.18 Change in Occupancies by Trip Purpose and Trip Start Time -0.50-0.250.000.250.500.751.001.251.501.752.002.255:00 5:59 am6:00 6:59 am7:00 7:59 am8:00 8:59 am9:00 9:59 am10:00 10:59 am11:00 11:59 amNoon 12:59 pm1:00 1:59 pm2:00 2:59 pm3:00 3:59 pm4:00 4:59 pm5:00 5:59 pm6:00 6:59 pm7:00 7:59 pm8:00 8:59 pm9:00 9:59 pm10:00 10:59 pm11:00 11:59 pmTrip Start TimeChange in Occupancy HBW HBShop HBSoc HBOther NHB

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157 CHAPTER 9 MODELLING OF ACTIVITY AND TRAVEL BEHAVIOR 9.1 Introduction This section looks into th e effect of the socio-dem ographics onto activity and travel behavior. Not only is the effect of so cio-demographics seen, but also an attempt has been made to explore what kind of tr adeoffs does occur between the activity and travel behavior. The section begins with model specification, followed by some data cleaning process that was requi red and finally the structural equation modeling for both weekdays and weekends. 9.2 Model Specification The objective of this part of the report is to develop a model that could help explore relationships among the socio-demogra phics, activity particip ation and the travel behavior. Based on literature and travel behavior theory, a possible structural equation model is postulated as shown in Figure 9.1. Th is framework is inte nded to capture how derived is the demand for travel for different ac tivities. The activity be havior or rather participation is defined by the time spent by the individual perfor ming that activity and travel behavior is essentially the time spent in driving (or being driven) for that activity. The socio-demographic characteristics of the individual are treated as exogenous

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variables whereas the activity participation and travel behavior is treated as the endogenous variables. The model is intended to capture how the socio-demographics can affect the travel behavior directly and indirectly through different activities in which the individual is engaged. The effects among the activities are hypothesized based on importance of each activity and the obligation level. In, other words we assume that people would give propriety in allocating the time to the subsistence activity first, maintenance activity second, followed by recreational and social activities. In addition, higher level travel times are supposed to directly affect the lower level activities. Figure 9.1 Activities Participation Model ACTIVITY PARTICIPATION SOCIO-DEMOGRAPHICS TRAVEL BEHAVIOR Subsistence Activity Duration 158 Person Characteristics (Age, Gender, Worker, Education ) Household Characteristics (Income, Household Size, Number of Children ) Maintenance Activity Duration Recreational Activity Duration Travel Time for Subsistence Travel Time for Maintenance Travel Time for Recreational Travel Time for Social Social Activity Duration

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159 That is, travel time for subsistence activity affects the maintenance, recreational and social activities. The simultaneous relationshi ps are estimated by the use of structural equations model. 9.3 Data Preparation The original sample sizes capturing the trip information and person level information of only urban households and the trips of 75 miles or less in length were used. A trip tour starting from home and ending at home wa s considered as a complete tour while other tours that included beginni ng of a trip from a non home based location and or/and ending at home based location on any day was considered belonging to an incomplete trip chain. Thus, only those pers ons trip information was selected who had complete tour information. The trip file, that contained the origin a nd destination of each trip, had almost 36 classifica tions of valid trip purposes Many classification schemes exist in literature. Conventi onal method is to group into two categories work and nonwork. In this report, modern consumer theory of classification into four types of out-ofhome activities Subsistence, Maintenance, Recreational and Social was followed in the analysis. Table 9.1 shows how the various activity classifica tions were composed from the NHTS purposes. The various activity type s and the corresponding tr avel required (in minutes) was aggregated for the person for the entire day and linked with other sociodemographics characteristics of the person. Essentially age, gender, worker status, education level, household income, number of persons in the household and the number of children in the household was supposed sufficient to represent the persons characteristics. Finally only those persons were selected who were 16 years or above to

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160 give more meaning of subsis tence activity to the indivi duals. The final sample thus contained 18,460 persons who traveled on w eekdays and 6,143 persons who traveled on weekends. Table 9.2 gives the person characteristics of all such persons. Table 9.1 Activity Categorization Original 2001 NHTS Trip Purposes Activity Categories Go to work Return to work Attend business meeting/trip Other work related School activity Go to school as a student SUBSISTENCE Shopping/errands Meals Get/eat meal Coffee/ice cream/snacks Buy goods: groceries/clothing/hardware store Buy services: video rentals/ dry cleaner/post office/car service/bank Buy gas Family personal business/obligations Use professional servic es: attorney/accountant Use personal services: grooming/haircut/nails Pet care: walk the dog/vet visits Attend meeting: PTA/home owners association/local government Go to library: school related Medical or dental services OS Day care Transport someone Pickup someone Rake and Wait Drop someone off MAINTENANCE Go to gym/exercise/play sports Rest or relaxation/vacation Social/recreational RECREATIONAL Go to religious activity Visit friends/relatives Go out/hang out: entertainment/theater/sports event/go to bar Visit public place: historic site/museum/park/library Attend funeral or wedding Social event Other reason SOCIAL

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161 Table 9.2 Characteristics of Persons Aged 16 Years and Above in Urban Areas Characteristic Weekday Weekend Sample Size 18,460 6,143 Population 82,161,864 30,612,254 Age(in years) 42.67 43.16 16-24 15.06% 15.43% 25-39 32.38% 30.14% 40-64 39.74% 41.10% 65-74 7.57% 7.95% 75-84 4.47% 4.76% 85+ 0.77% 0.61% Gender Male 48.44% 48.84% Female 51.56% 51.16% Worker 70.65% 70.44% Driver 93.60% 92.70% Educational Level Low 35.80% 37.90% Medium 30.10% 29.60% High 34.10% 32.60% Daily Activity Durations (minutes) All Non-Zero All Non-Zero Subsistence 288.77 466.98 70.70 367.38 Maintenance 63.95 88.78 87.58 111.71 Recreational 14.91 103.61 19.21 125.50 Social 32.29 151.51 93.36 192.55 Daily Travel Durations (minutes) All Non-Zero All Non-Zero Subsistence 20.03 32.36 4.76 24.71 Maintenance 25.60 35.04 28.57 36.12 Recreational 3.53 23.83 4.55 28.86 Social 5.24 24.40 13.49 27.72 Refer Table 3.3 for details on categorization of educational level of the respondent.

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162 9.4 Theory of Structural Equations Modeling A structural equation model (SEM) is us ed to capture the causal influences (regression effects) of the exogenous variab les on the endogenous variables. It has several advantages over othe r linear-in-paramet ers statistical methods. Golob (2003) summarized how the flexibility of this linear in parameter multivariate statistical modeling technique has been used in various transportation applic ations. The standard form of a structural equation model (w ithout latent variables) is given as: Y = B. Y + .X + e where Y is a column vector of p endogenous variables, X is a column vector of q exogenous variables. B is the pp matrix of parameters between the endogenous variables, is the pq matrix of parameters from th e exogenous variables to the endogenous variables, = E[ e.e T ] is the variance-covariance matrix of the p error terms and is the qq covariance matrix of X The equation can be rewritten as Y = [I B ] -1 [ .X + e ] where I denotes the identity matrix of rank p. For identification, it is assumed that B is chosen such that [I-B] is non-singular. This type of st ructural equations systems are estimated generally using the method of mome nts (also called varian ce analysis methods or covariance (structure) anal ysis). It follows the idea th at the matrix of population covariance matrix of observed variables (in our case all the exogenous and endogenous variables since there is no latent variable) given by S matches as close as possible to the covariance matrix, ( ) of the variables implied by the model system in terms of model parameters ( With multiple endogenous variables in the SEM, several methods such as normal theory Maximum Likelihood (ML), unweighted least squares (ULS), generalized

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163 weighted least squares (GWLS) and asympt otically distributionfree weighted least squares (ADF) developed generally involve mini mization of a scalar fitting function that makes this possible. The sele ction of an appropriate es timation method depends on the assumptions made on probability distribution, th e scale properties of the variables, the complexity of the model and the sample size. ML method is used most often in transportation research because of being robust against violations of multivariate normality for sample sizes. Missing, non-normal, truncated and censored data biases the estimation results obtained fr om the ML method. To minimize the biases, ADF method is used that yield consistent and asymptotically efficient estimators. The fitting function that is minimized in the ADF method of estimati on of structural parameters is given by F ADF = [s ( ) ] T W -1 [s ( ) ] where s is a vector of censored correlation co efficients for all pairs of endogenous and exogenous variables i.e. a vector of ( p+q)(p+q+1) elements of S ( ) is a vector of model-implied correlations for the same variable pairs i.e. a vector of ( p+q)(p+q+1) elements of ( ) and W is a positive definite weight matrix whose best choice is a consistent estimator of the asymptotic c ovariance. Browne (1984) demonstrated that under very generalized conditions, W = ( w ij, kl w ij .w kl )/N is a consistent estimator, where w ij, kl denotes the fourth ordered moments of the variables around their means, w ij and w kl denote covariances, and N th e number of observations. According to Kuppam and Pendyala (2001), mo del coefficients through the ML and the ADF estimation are same if the endogenous variables are continuous, however the later lacks in obtaining the intercepts. The estimati on of the models in this report has been

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164 done via ADF method using AMOS software (A rbuckle, 2000), howev er the intercepts are produced that were a result of ML method. The model fit is assessed by various measures. The 2 test statistic is used to test the null hypothesis that the theoretical model fits the data. If the model provides a good fit, then the obtained 2 value should be small and the p value associated with the 2 should be relatively large (i .e. greater than 0.05). Although 2 is a useful index, it is generally accepted that it should be interpre ted with caution and supplemented with other goodness of fit indices. The 2 test can be influenced with factors other than the validity of the theoretical model: factors such as sample size, departures form multivariate normality, and the complexity of the model. Some researcher s use the criteria that the ratio of the 2 value to its degrees of freedom should be less than 2.00. Since for large samples, Hoelters Critical N (CN) is used that gives the sample size for which the 2 would correspond to p=0.05. As a rule of thumb, mode l having CN value greater than 200 is assumed acceptable. Comparative Fit Inde x (CFI) has been proposed as alternative to the 2 test. It ranges from 0 to 1 but values over 0.90 are said to be indicative of an acceptable fit. Goodness of fit measure based on 2 value for a single model such as the root mean square error of approximation (R MSEA) describing the discrepancy per degree of freedom is also used. For a good model, value of RMSEA less than 0.05 is suggested. Goodness of fit measures based on the dire ct comparison of the sample and modelimplied variance covariance matrices incl ude the Goodness-of-Fit Index (GFI) and the Adjusted Goodness-of-Index (AGFI), adjusted fo r the degrees of freedom in the model.

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9.5 Model Estimation Results Structural Equations Modeling gives an insight into three types of relationships between the variables the total, the direct and the indirect effect. The total effects of the endogenous variables on each other are given by T xx = [I B] -1 I and the total effects of the exogenous variables on the endogenous variables are given by T xy = [I B] -1 The total effect of one variable on another is the sum of the direct effect and the indirect effect that can occur with another variable(s) in between. Direct and indirect effect has significance in the sense that in one way it may lead to an increase whereas in another way it may lead to a decrease (if the signs of both the effects are opposite). Figure 9.2 illustrates the concept of the direct and indirect effect. In the figure, variable A effects C directly and indirectly through another variable B. Model estimation results are produced separately for weekdays and weekends. Figure 9.2 Illustration of Direct, Indirect and Total Effects B 165 A C 1 2 d Direct Effect = Regression Coefficient (d) Indirect Effect = 1 2 Total Effect (t) = d + 1 2

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166 9.5.1 Weekdays The estimation results for weekdays describing the effect of socio-demographics on activity durations and travel times are shown in Table 9.3 whereas Table 9.4 shows the interactions between the activity durations and travel times. Various goodness-of-fit measures are reproduced in the Table 9.3. The 2 goodness of fit shows that null hypothesis about sample moments being e qual to the implied moments cannot be rejected. All measures of goodness of fit su ch as good of fit index (GFI), Adjusted goodness of fit index (AGFI), and root mean square error of approximation (RMSEA) are all acceptable by model fit criter ia according to Golob (2003). Table 9.3 Effect of Socio-Demographics on Activity and Travel Time on Weekdays Endogenous Variable Intercept Effect Age Age 2 Male High Educ. Worker Status High Income HH Size No. of Children 153.58 Total 4.26 -0.09 73.83 -12.98 159.92 20.68 0.00 -16.32 Direct 4.26 -0.09 73.83 -12.98 159.92 20.68 -16.32 Subsistence Activity Duration Indirect 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 81.15 Total 0.72 0.00 -18.03 1.78 21.90 1.35 -3.13 6.17 Direct 1.30 -0.01 -7.92 4.18 -3.13 3.94 Maintenance Activity Duration Indirect -0.58 0.01 -10.11 1.78 -21.90 -2.83 0.00 2.23 25.95 Total -0.21 0.00 3.26 5.51 -5 .13 4.93 -1.09 1.49 Direct 5.19 5.09 5.83 -1.27 1.19 Recreational Activity Duration Indirect -0.21 0.00 -1.93 0.42 -5.13 -0.89 0.17 0.31 101.98 Total -1.82 0.02 -4.59 0.55 -6 .99 -2.32 0.45 -0.78 Direct -1.38 0.01 4.15 -1.38 Social Activity Duration Indirect -0.45 0.01 -4.59 0.55 -11.14 -2.32 0.45 0.60 -4.43 Total 0.59 -0.01 8.68 -0.63 10.40 2.83 0.04 -0.75 Direct 0.39 0.00 5.40 3.37 2.00 Travel time for Subsistence Indirect 0.20 0.00 3.28 -0.63 7.04 0.83 0.04 -0.75 12.24 Total 0.51 0.00 -4.10 0.44 -6 .44 1.01 -1.46 3.73 Direct 0.44 0.00 1.21 -0.99 2.45 Travel time for Maintenance Indirect 0.07 0.00 -4.10 0.44 -6 .44 -0.20 -0.47 1.29 0.69 Total 0.04 0.00 0.22 1.27 -1 .00 1.10 -0.26 0.21 Direct 0.08 0.00 0.57 0.57 -0.14 Travel time for Recreational Indirect -0.04 0.00 0.22 0.70 -1 .00 0.53 -0.12 0.21 1.70 Total -0.20 0.00 -0.71 0.10 -1.18 0.09 -0.11 0.02 Direct 0.36 -0.13 Travel time for Social Indirect -0.20 0.00 -0.71 0.10 -1.18 -0.27 0.02 0.02 N = 18460; 2 = 39 with df = 31; p-val = 0.153; GFI = 1.00; AGFI = 1. 00; RMSEA = 0.004; CFI = 1.00; CN = 21290. All variables are significant at 95% level of confidence

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167 The model results in Table 9.3 shows that males spend almost 74 minutes on an average more as compared to females. Females on the other hand spend more time on out of home maintenance and social activities. Th is agree with the earlier literature that suggested the household obligations are been more attached to females than males. Tradeoff between various activities and the trav el times can clearly be seen in Table 9.4 An increase in one activity leads to a decrease in duration of any ot her activity down the activities hierarchy. An hour of subsistence activity reduces maintenance, recreational and social activities by 8.5 min, 2 min a nd 4.2 minutes respectively. An hour of maintenance activity reduces the social activity by almost 9.6 minutes. Persons belonging to higher income households (those with $55K or more) spend more time on work and work related activities on weekdays possibly because of more work obligations to be met. However they have spend more time on recreation and maintenance activities too implying more complex trip chaining behavior by these households. Although most of the direct effects are reinforced by the indirect effects but there are few cases where the indirect effect tend to offset the direct effect. Consider the effect of male on the recreational activity du ration. Males spend more time on r ecreational activities. However, spending more time on subsistence activities leads to spending lesser times on all other activities. Further by spending less time on maintenance activiti es will lead to spending more time on other recreational ac tivity. Thus, the indi rect effect is the sum of the above two indirect effects which comes out to be favoring less time on recreational activities possibly because of too much time spent on s ubsistence activity leaving them with not quite enough time to be spent on recreational ones. Similar kind of tradeoff occurs with the effect of worker status on social activity duration.

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168 Table 9.4 Effect of Activity Particip ation on Travel Time on Weekdays Endogenous Variable Effect Type Subs. Activity Duration Maint. Activity Duration Recr. Activity Duration Social Activity Duration Travel Time for Subs. Travel Time for Maint. Travel Time for Recr. Total Direct Subsistence Activity Duration Indirect Total -0.14 Direct -0.14 Maintenance Activity Duration Indirect 0.00 Total -0.03 -0.06 Direct -0.04 -0.06 Recreational Activity Duration Indirect 0.01 0.00 Total -0.07 -0.12 -0.07 Direct -0.09 -0.12 -0.07 Social Activity Duration Indirect 0.02 0.00 0.00 Total 0.04 -0.01 -0.01 -0.02 Direct 0.04 -0.01 -0.01 -0.02 Travel Time for Subs. Activity Indirect 0.00 0.00 0.00 0.00 Total -0.04 0.16 -0.02 -0.01 0.05 Direct -0.02 0.16 -0.02 -0.01 0.05 Travel Time for Maint. Activity Indirect -0.02 0.00 0.00 0.00 0.00 Total -0.01 -0.01 0.12 0.00 -0.01 Direct 0.00 0.00 0.12 -0.01 Travel Time for Recr. Activity Indirect 0.00 -0.01 0.00 0.00 0.00 Total -0.01 -0.01 -0.01 0.11 0.00 0.03 0.03 Direct 0.00 0.00 0.00 0.11 0.03 0.03 Travel Time for Social Activity Indirect -0.01 -0.01 -0.01 0.00 0.00 0.00 0.00 The indirect effects seem to be stronger th an the direct effect. A worker would spend much more time on subsistence activity as co mpared to any other activity. However, an increase in the subsistence activity durati on would lead to decrease in maintenance, recreational and social activiti es duration. The net effect of all possible tradeoffs that would occur through the worker status to th e social activity mediating between other activities comes out to be a d ecrease in social activity pa rticipation. Thus, these total effects give a good picture of what all factors are causing the change in the behavior.

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169 As far as the travel times are concer ned, males are found to travel more for subsistence activity that they have to perf orm and similarly less travel for maintenance activities. Table 9.4 shows intera ctions between the travel ti me and the activity durations. More is the activity duration; more is the travel time that is being devoted to that activity fulfillment. Further more is the travel time for subsistence activity, more is the time spent in traveling for maintenance activity and le ss time for the recreational activity. This can be explained by the fact that recreational activities are not performed possibly due to commuting stress tend to take control wh en the work requires a lot of travel. 9.5.2 Weekends The estimation results for weekends descri bing the effect of socio-demographics on activity durations and travel times are shown in Table 9.5 whereas Table 9.6 shows the interactions between the activity durations and travel times. Various goodness-of-fit measures as produced for the weekends are reproduced in Table 9.5. The 2 goodness of fit shows that null hypothesis about sample moments being eq ual to the implied moments cannot be rejected. All meas ures of goodness of fit such as good of fit index (GFI), Adjusted goodness of fit index (AGFI), and root mean square error of approximation (RMSEA) are all acceptable by model fit criteria according to Golob (2003). The effect of socio-demographics on the activity and travel behavior is almost same with only difference that occur is in the magnitude of the effects. One of the differences that are visible on direct comparison is that workers participate in social activities on weekends as opposed to an av erage non-participation behavi or exhibited on weekdays. Other is the effect of persons belonging to high income households. High income

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170 Table 9.5 Effect of Socio-Demographics on Activity and Travel Time on Weekends Endogenous Variable Intercept Effect Age Age 2 Male High Educ. Worker Status High Income HH Size No. of Children 89.17 Total -1.28 0.00 27.92 -21.84 40.29 -10.35 5.56 -11.87 Direct -1.28 27.92 -21.84 40.29 -10.35 5.56 -11.87 Subsistence Activity Duration Indirect 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 75.18 Total 1.55 -0.02 -13.94 2.89 -5.33 1.37 -0.74 1.57 Direct 1.38 -0.02 -10.24 Maintenance Activity Duration Indirect 0.17 0.00 -3.69 2.89 -5.33 1.37 -0.74 1.57 24.93 Total -0.04 0.00 10.22 6.50 -1.22 3.79 -2.15 3.12 Direct 0.00 10.45 5.84 3.48 -1.98 2.76 Recreational Activity Duration Indirect -0.04 0.00 -0.23 0.66 -1.22 0.31 -0.17 0.36 184.89 Total -2.31 0.02 -4.04 1.80 1.19 -9.55 2.55 1.08 Direct -2.13 0.02 7.24 -10.22 2.88 Social Activity Duration Indirect -0.19 0.01 -4.04 1.80 -6.06 0.67 -0.33 1.08 0.58 Total -0.06 0.00 2.60 -1.06 2.90 -0.47 0.26 -0.57 Direct 1.28 1.00 Travel time for Subsistence Indirect -0.06 0.00 1.32 -1.06 1.90 -0.47 0.26 -0.57 12.98 Total 0.65 -0.01 -1.13 0.69 -1.44 0.51 -0.85 0.38 Direct 0.35 0.00 1.49 -0.63 Travel time for Maintenance Indirect 0.31 0.00 -2.62 0.69 -1.44 0.51 -0.22 0.38 0.90 Total 0.15 0.00 2.25 0.91 -0.35 0.57 -0.68 0.44 Direct 0.13 0.00 1.01 -0.36 Travel time for Recreational Indirect 0.01 0.00 1.24 0.91 -0.35 0.57 -0.32 0.44 6.22 Total -0.21 0.00 -1.37 0.24 -0.95 -0.93 -0.26 0.15 Direct -0.90 -0.90 -0.46 Travel time for Social Indirect -0.21 0.00 -0.48 0.24 -0.05 -0.93 0.21 0.15 N = 6143; 2 = 8 with df = 39; p-val = 0.91; GFI = 1.00; AGFI = 1.00; RMSEA = 0.000; CFI = 1.00; CN = 12041. All variables are significant at 95% level of confidence households are possibly spe nding les time on weekend subsistence activity may be mostly because of a non-working day and subst itution to other activi ties. The lesser they spend their time on the subsistence activity the lesser is the time that is been required for it. Number of children has a positive eff ect on the social activity duration. Where weekdays tend to more of a working day with not much time required by the household members to involve in social activities, weekends may be the chance for whole family to involve in social activities. Si milar to behavior on weekdays, the travel time for a specific

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171 activity type increase only if the activity dur ation increases. An increase in activity duration on particular type lead s to a decrease in duration an d travel time for all other activities. Table 9.6 Effect of Activity Particip ation on Travel Time on Weekends Endogenous Variable Effect Type Subs. Activity Duration Maint. Activity Duration Recr. Activity Duration Social Activity Duration Travel Time for Subs. Travel Time for Maint. Travel Time for Recr. Total Direct Subsistence Activity Duration Indirect Total -0.13 Direct -0.13 Maintenance Activity Duration Indirect 0.00 Total -0.03 -0.06 Direct -0.04 -0.06 Recreational Activity Duration Indirect 0.01 0.00 Total -0.15 -0.28 -0.25 Direct -0.20 -0.29 -0.25 Social Activity Duration Indirect 0.05 0.02 0.00 Total 0.05 0.00 0.00 0.00 Direct 0.05 0.00 0.00 0.00 Travel Time for Subs. Activity Indirect 0.00 0.00 0.00 0.00 Total -0.04 0.16 -0.02 -0.02 0.17 Direct -0.03 0.15 -0.02 -0.02 0.17 Travel Time for Maint. Activity Indirect -0.01 0.01 0.00 0.00 0.00 Total -0.01 -0.01 0.13 -0.01 0.00 0.02 Direct -0.01 -0.01 0.13 -0.01 0.02 Travel Time for Recr. Activity Indirect 0.00 0.00 0.00 0.00 0.00 0.00 Total -0.02 -0.03 -0.03 0.10 0.01 0.06 Direct 0.00 -0.01 -0.01 0.10 0.06 Travel Time for Social Activity Indirect -0.02 -0.02 -0.03 0.00 0.01 0.00

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172 CHAPTER 10 CONCLUSIONS AND FURTHER RESEARCH 10.1 Conclusions The report compared travel behavior ch aracteristics on weekdays and weekends in United States using the recently available 2001 NHTS data. The detailed analysis of various trip characteristics by various so cio-demographic characteristics at the households and the person level provided insi ghts into how and to what extent the difference occurred on w eekdays and weekends. At the household level, a decrease in the person trips was found on weekends as compared to weekdays. All other analysis that was done at person level offered distinctions to be made depending on various person and trip characteristics. Females were found to be more active than males in making more number of trips on weekdays while a reverse trend was obtained on weekends However, their overall mileage traveled was found to be lesser than that of males. Mean trip lengths per person and per vehicle were found to be slightly more on weekends than weekdays. Overall person miles traveled by the person per day on weekends wa s found to be more than weekdays but on the household level, the total vehicles mile s traveled by household on weekdays exceeded that on weekends. Although single occupant au to (SOV) dominated the chosen mode for

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173 making trips, their share re duced on weekends with more persons making trips on a higher occupancy vehicle. Higher occupancy vehicles were preferred for longer trips on weekends as opposed to the SOVs. Vehicle o ccupancies were studied with respect the purpose and the time of the day. The trio role of socio-demographics, activity and travel behavior was captured through a structural equation model framework th at provided insights onto various direct and indirect effects inhibite d in the relationships among th em. Most of the estimated direct effects were found to be in consistent with the past literature. Overall this study which summarizes w eekday and weekend travel behavior analysis can help assist various decision makers and planners in facilitating the good design or planning of transportation systems, devise policies in mitigating congestion and air quality issues. The trip estimates in this report derived from the latest national survey in this report can be used by the urban planners for planning purposes. 10.2 Further Research The report uses only one-day travel data of the individual obtained through the Computer Assisted Telephonic Interview (CATI) process. As described in the literature review, there happens to be a lot of substitu tion of activities that goes on between the inhome and out-home and also on weekdays and w eekends. With availability of sufficient data, one can study the rhythms of travel th at is exhibited by the individual between several days. Further one day data has been s ubjected to various cri ticisms such as people

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174 generally lying or giving fals e information about the destinat ion, travel time, trip purpose and other characteristics such as underreporting of short trips or number of stops in trip chain. This is supposed to be improved by the use of Global Positioning Systems (GPS). Collecting traffic data on weekdays and week ends can lead to comparison of congestion indices over several ar eas that warrant such an analysis.

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