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A benefit-cost analysis of a state freeway service patrol

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Title:
A benefit-cost analysis of a state freeway service patrol a Florida case study
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Book
Language:
English
Creator:
Singh, Harkanwal Nain
Publisher:
University of South Florida
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Tampa, Fla
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Subjects / Keywords:
Road rangers program
Traffic delays
Roadway capacity
Incidents
FSPE delay model
Freeway incident management
Dissertations, Academic -- Civil Engineering -- Masters -- USF
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bibliography   ( marcgt )
theses   ( marcgt )
non-fiction   ( marcgt )

Notes

Abstract:
ABSTRACT: The Road Ranger program is a freeway service patrol (FSP) designed to assist disabled vehicles along congested freeway segments and relieve peak period non-recurring congestion through quick detection, verification and removal of freeway incidents in Florida. It consists of approximately 88 vehicles in fleet and provides free service to about 918 centerline miles. The program is funded by the Florida Department of Transportation (FDOT) and its partners, and is bid out to private contractors. The objective of this study is to examine and evaluate the benefits of the Road Ranger service against their operating costs in five of the seven FDOT Districts and Florida Turnpike Enterprise. The five Districts were chosen due to the availability of Road Ranger program data and activity logs for analysis.The Road Ranger program provides direct benefits to the general public in terms of reduced delay, fuel consumption, air pollution and improved safety and security. The benefits would ^be expected to be more significant during the peak period when demand reaches or exceeds capacity than in the off-peak and the mid-day period where capacity may not be as significant an issue. The costs considered in this analysis include costs of administration, operation, maintenance, employee salaries, and overhead costs.Incident data were obtained from the daily logs maintained by the Road Ranger service provider containing important information about the time, duration, location, and type of service provided. Other data collected for this study include average daily traffic volume, geometric characteristics of the freeways, unit cost of Road Ranger service, etc.The Freeway Service Patrol Evaluation (FSPE) model developed by the University of California-Berkley was calibrated and used to estimate the benefit-cost ratio for the Road Ranger program. The estimated benefit/cost ratios based on delay and fuel savings indicate that the Road Ranger program produces significant benefits i n all the five Districts and Turnpike. The range of benefit-cost ratio of the Road Ranger program in different districts is from 2.3:1 to 41.5:1. The benefit -cost ratio of the entire Road Ranger program is estimated to be in excess of 25:1.
Thesis:
Thesis (M.A.)--University of South Florida, 2006.
Bibliography:
Includes bibliographical references.
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Mode of access: World Wide Web.
Statement of Responsibility:
by Harkanwal Nain Singh.
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Title from PDF of title page.
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Document formatted into pages; contains 93 pages.

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University of South Florida Library
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University of South Florida
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Resource Identifier:
aleph - 001793926
oclc - 145558319
usfldc doi - E14-SFE0001526
usfldc handle - e14.1526
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SFS0025844:00001


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A Benefit-Cost Analysis of a State Freew ay Service Patrol: A Florida Case Study by Harkanwal Nain Singh 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 Pendyala, Ph.D. Larry Hagen, P.E., P.T.O.E. Huaguo Zhou, Ph.D. Jian Lu, Ph.D. Date of Approval: March 29, 2006 Keywords: Road Rangers Program, Traffic Delays, Roadway Capacity, Incidents, FSPE Delay Model, Freeway Incident Management Copyright 2006, Harkanwal Nain Singh

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ACKNOWLEDGEMENTS I express my sincere gratitude to my te achers, Larry Hagen, Dr. Huaguo Zhou and Dr. Ram M. Pendyala. It has been has been a wonderful experience to work with them. I thank them for the invaluable ideas, advice and availability that made working on my thesis an enjoyable undertaking. The constant support, active encouragement, inspiration and an excellent and flexible academic atmos phere they provided throughout the masters program has given me a great opportunity to le arn and experience res earch. Thanks to Dr. Jian J. Lu for serving in my master’s thes is committee. Interaction with my colleagues and friends at CUTR on many occasions, especi ally has been very valuable. I also thank the Department of Civil and Environmental Engineering for providi ng excellent facilities and research atmosphere.

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i TABLE OF CONTENTS LIST OF TABLES.............................................................................................................iii LIST OF FIGURES...........................................................................................................vi ABSTRACT......................................................................................................................v ii CHAPTER 1 INTRODUCTION........................................................................................1 1.2 Florida Road Ranger Program...................................................................................2 1.3 Objectives of the Study..............................................................................................3 1.4 Organization of Thesis...............................................................................................3 CHAPTER 2 LITERATURE REVIEW.............................................................................4 2.1 Detection and Response Time...................................................................................4 2.2 Restoration Time........................................................................................................5 2.3 Capacity Reduction....................................................................................................5 2.4 Type of Incidents.......................................................................................................7 2.5 Delay Calculation.......................................................................................................7 2.6 Costs of Freeway Service Patrol................................................................................9 2.7 Benefit-Cost Ratio...................................................................................................10 CHAPTER 3 METHODOLOGY.....................................................................................12 CHAPTER 4 DATA COLLECTION AND PROCESSING............................................16 4.1 Beat/Service Description.........................................................................................16 4.2 Beat Design Characteristics.....................................................................................17 4.3 Traffic Data..............................................................................................................1 7 4.4 Incident Data............................................................................................................18 4.5 Limitations of the Incident Data..............................................................................20 CHAPTER 5 INCIDENT DATA ANALYSIS.................................................................22 5.1 Incident Frequency and Characteristics...................................................................22 5.2 Incident Duration.....................................................................................................31 5.3 Lateral Distribution of Incidents..............................................................................34 CHAPTER 6 BENEFIT AND COST ANAL YSIS..........................................................36

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ii 6.1 Delay and Fuel Savings...........................................................................................36 6.2 Costs...................................................................................................................... ...38 6.3 Benefit and Cost Ratio.............................................................................................38 CHAPTER 7 SENSITIVITY ANALYSIS.......................................................................40 7.1 Introduction..............................................................................................................4 0 7.2 Mean Response Time Without Road Ranger Service..............................................41 7.3 Capacity................................................................................................................... 44 7.4 Number of Incidents................................................................................................45 7.5 Average Annual Daily Traffic.................................................................................46 7.6 Value of Travel Time (Dollars Per Vehicle-hour)...................................................47 7.7 Patrolling Truck Speed............................................................................................48 7.8 Summary..................................................................................................................49 CHAPTER 8 CONCLUSIONS........................................................................................51 REFERENCES.................................................................................................................55 APPENDICES..................................................................................................................57 Appendix A: Traffic Data..............................................................................................58 Appendix B: Benefit/Cost Ra tio In Each District.........................................................67 Appendix C: Savings In Vehicle Emissions In Each District.......................................80 Appendix D: FSPE Model Excel Sheets.......................................................................92

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iii LIST OF TABLES Table 1.1 Number of Assists by Road Rangers in Year 2000-2003....................................3 Table 2.1 Remaining Freeway Cap acity (%) Recommended by HCM...............................7 Table 2.2 Results of Service Pa trol Benefit-Cost Studies..................................................11 Table 4.1 Traffic Profiles (Time of the Day Distribution of Traffic) of Various Districts in Florida..............................................................................................18 Table 4.2 Percentage of Incident Occurrence by Lateral Location...................................19 Table 5.1 Number of Incident and In cident Rates in Each District...................................22 Table 5.2 Percentage Distribution of Inci dents by Type in Various Districts...................23 Table 5.3 Incident Rates on the Freeways in District 6.....................................................27 Table 5.4 Incident Duration by Type in Minutes in Each District.....................................31 Table 5.5 Average Duration in Minutes by Type of Incident in District 6........................33 Table 5.6 Lateral Distribution (%) of Incidents in District 6.............................................35 Table 6.1 Benefit-Cost Ratio of Road Ranger Program in Each District..........................37 Table A.1 Traffic Profiles of Various Districts in Florida.................................................58 Table A.2 Freeway and Traffic Ch aracteristics in District 2.............................................59 Table A.3 Freeway and Traffic Ch aracteristics in District 4.............................................60 Table A.4 Freeway and Traffic Ch aracteristics in District 5.............................................61 Table A.5 Freeway and Traffic Ch aracteristics in District 6.............................................62 Table A.6 Freeway and Traffic Characteristics in Turnpike.............................................64 Table A.7 Freeway and Traffic Characteristics in Turnpike.............................................65 Table B.1 Road Ranger Benefits in District 2 (Jan-Sep)...................................................67 Table B.2 Monthly Road Ranger Benefits in District 2 on I-10 (Jan-Sep)........................67 Table B.3 Monthly Road Ranger Benefits in District 2 on I-295 (Jan-Sep)......................67 Table B.4 Monthly Road Ranger Benefits in District 2 on I-95 (Jan-Sep)........................68 Table B.5 Monthly Road Ranger Benefits in Di strict 2 on Turner Butler Road (Jan-Sep)68 Table B.6 Road Ranger Benefits in Districts 4, 5 a nd District 7.......................................68 Table B.7 Average Monthly Road Ra nger Benefits in District 6......................................69 Table B.8 Monthly Road Ranger Be nefits on I-75 in District 6........................................69

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iv Table B.9 Monthly Road Ranger Be nefits on I-95 in District 6........................................70 Table B.10 Monthly Road Ranger Benefits on I-395 in District 6....................................70 Table B.11 Monthly Road Ranger Benefits on I-195 in District 6....................................71 Table B.12 Monthly Road Ranger Benefits on SR-836 in District 6................................71 Table B.13 Monthly Road Ranger Benefits on SR-112 in District 6................................72 Table B.14 Monthly Road Ranger Benefits on SR-826 in District 6................................72 Table B.15 Monthly Road Ranger Benefits on SR-874 in District 6................................73 Table B.16 Monthly Road Ranger Benefits on SR-878 in District 6................................73 Table B.17 Overall Annual Benefit of Road Ranger Program in Turnpike Region..........74 Table B.18 Monthly Road Ranger Benefits in Zone 1......................................................74 Table B.19 Monthly Road Ranger Benefits in Zone 2......................................................75 Table B.20 Monthly Road Ranger Benefits in Zone 3......................................................75 Table B.21 Monthly Road Ranger Benefits in Zone 4......................................................76 Table B.22 Monthly Road Ranger Benefits in Zone 5......................................................76 Table B.23 Monthly Road Ranger Benefits in Zone 6......................................................77 Table B.24 Monthly Road Ranger Benefits in Zone 7......................................................77 Table B.25 Monthly Road Ranger Benefits in Zone 8......................................................78 Table B.26 Monthly Road Ranger Benefits in Zone 12....................................................78 Table B.27 Monthly Road Ranger Benefits in Zone 13....................................................79 Table C.1 Savings in Vehicular Emissi ons in District 2 on I-10 (Jan-Sep).......................80 Table C.2 Savings in Vehicular Emissi ons in District 2 on I-295 (Jan-Sep).....................80 Table C.3 Savings in Vehicular Emissi ons in District 2 on I-95 (Jan-Sep).......................81 Table C.4 Savings in Vehicular Emissions in District 2 on Turner Butler Road (JanSep)..................................................................................................................81 Table C.5 Savings in Vehicular Em issions in District 4, 5 and 7......................................82 Table C.6 Savings in Vehicular Em issions on I-75 in District 6.......................................82 Table C.7 Savings in Vehicular Em issions on I-95 in District 6.......................................82 Table C.8 Savings in Vehicular Em issions on I-395 in District 6.....................................83 Table C.9 Savings in Vehicular Em issions on I-195 in District 6.....................................83 Table C.10 Savings in Vehicular Em issions on SR-836 in District 6...............................84 Table C.11 Savings in Vehicular Em issions on SR-112 in District 6...............................84 Table C.12 Savings in Vehicular Em issions on SR-826 in District 6...............................85

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v Table C.13 Savings in Vehicular Em issions on SR-874 in District 6...............................85 Table C.14 Savings in Vehicular Em issions on SR-878 in District 6...............................86 Table C.15 Savings in Vehicular Emissions in Zone 1 in Florida’s Turnpike..................86 Table C.16 Savings in Vehicular Emissions in Zone 2 in Florida’s Turnpike..................87 Table C.17 Savings in Vehicular Emissions in Zone 3 in Florida’s Turnpike..................87 Table C.18 Savings in Vehicular Emissions in Zone 4 in Florida’s Turnpike..................88 Table C.19 Savings in Vehicular Emissions in Zone 5 in Florida’s Turnpike..................88 Table C.20 Savings in Vehicular Emissions in Zone 6 in Florida’s Turnpike..................89 Table C.21 Savings in Vehicular Emissions in Zone 7 in Florida’s Turnpike..................89 Table C.22 Savings in Vehicular Emissions in Zone 8 in Florida’s Turnpike..................90 Table C.23 Savings in Vehicular Emissions in Zone 12 in Florida’s Turnpike................90 Table C.24 Savings in Vehicular Emissions in Zone 13 in Florida’s Turnpike................91

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vi LIST OF FIGURES Figure 5.1 Monthly Distribution of Incidents in District 2................................................24 Figure 5.2 Number of Incidents by Type in District 4.......................................................25 Figure 5.3 Monthly Distribu tion of Incident Number in District 5...................................26 Figure 5.4 Percentage Distribution of In cidents by Type in District 6..............................27 Figure 5.5 Number of Incidents by Type on I-275 in District 7.......................................28 Figure 5.6 Number of Incidents by Type in Turnpike Region..........................................30 Figure 5.7 Monthly Distribution of Incidents on Turnpike...............................................30 Figure 5.8 Incident Duration in Minutes by Type of Incident in District 4.......................32 Figure 5.9 Incident Durations in Mi nutes on I-275 in District 7.......................................34 Figure 7.1 Change in Benefit-Cost Ratio With Mean Response Time Without the Service on a 5 mile Section With Di fferent Number of Service Trucks.........43 Figure 7.2 Change in Benefit-Cost Ratio With Mean Response Time Without the Service on a 15 mile Section With Di fferent Number of Service Trucks.......43 Figure 7.3 Change in Benefit-Cost Ratio With Mean Response Time Without the Service on a 10 mile Section With Two Service Trucks.................................44 Figure 7.4 Change in Benefit-Cost Ratio With Freeway Capacity....................................45 Figure 7.5 Change in Benefit-Cost Ratio With Number of Incidents Per Month on the Beat Segment.............................................................................................46 Figure 7.6 Change in Benefit-Cost Ratio With AADT Volumes......................................47 Figure 7.7 Change in Benefit-Cost Ratio With Value of Travel Time..............................48 Figure 7.8 Change in Benefit-Cost Ratio With Patrolling Truck Speed...........................49 Figure D.1 FSPE Model MS-Excel Input Sheet................................................................92 Figure D.2 FSPE Model Output in MS-Excel...................................................................93

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vii A BENEFIT-COST ANALYSIS OF A STATE FREEWAY SERVICE PATR OL: A FLORIDA CASE STUDY Harkanwal Nain Singh ABSTRACT The Road Ranger program is a freeway service patrol (FSP) designed to assist disabled vehicles along congested freeway segments and relieve peak period non-recurring congestion through quick detection, verifica tion and removal of freeway incidents in Florida. It consists of approximately 88 ve hicles in fleet and provides free service to about 918 centerline miles. The program is funded by the Florida Department of Transportation (FDOT) and its partners, and is bid out to privat e contractors. The objective of this study is to examine and ev aluate the benefits of the Road Ranger service against their operating costs in five of the seven FDOT Districts and Florida Turnpike Enterprise. The five Districts were chosen due to the availability of Road Ranger program data and activ ity logs for analysis. The Road Ranger program provides direct bene fits to the general public in terms of reduced delay, fuel consumption, air polluti on and improved safety and security. The benefits would be expected to be more significant during the peak period when demand reaches or exceeds capacity than in the o ff-peak and the mid-da y period where capacity may not be as significant an issue. The costs considered in this analysis include costs of administration, operation, maintenance, em ployee salaries, and overhead costs. Incident data were obtained from the daily logs maintained by the Road Ranger service provider containing important information a bout the time, durati on, location, and type of service provided. Other data collected fo r this study include av erage daily traffic volume, geometric characteristics of the fr eeways, unit cost of Road Ranger service, etc.

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viii The Freeway Service Patrol Evaluation (FSPE ) model developed by the University of California-Berkley was calibrated and used to estimate the benefit-cost ratio for the Road Ranger program. The estimated benefi t/cost ratios based on delay and fuel savings indicate that the Road Ranger program produces significant benefits in all the five Districts and Turnpike. The range of be nefit-cost ratio of the Road Ranger program in different districts is from 2.3:1 to 41.5:1. The benefit -cos t ratio of the entire Road Ranger program is estimated to be in excess of 25:1.

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1 CHAPTER 1 INTRODUCTION 1.1 Background Highway congestion represents a daily prob lem for commuters and commercial carriers on many freeways across the countr y. It costs travelers more than $40 billion annually in our nation’s 50 largest cities (1) Incidents are the unplanned random events occurring on freeways, resulting in a reduction in the capacity of the freeway system due to either lane blockage or rubbernecking. It has been found th at the actual reduction in the capacity is much more than that one would anticipate. For example, a closure of one-lane on a threelane freeway causes more than 50% reducti on in capacity instead of 33%. Even an incident on the shoulder causes a reduction in capacity or flow because curiosity leads to driver distraction and a reduc tion in speeds. A recent study (2) has evaluated the rubbernecking impacts of accidents on traffic in the opposite direction based on archived traffic and accident data. In order to reduce non-recurring delays cau sed by incidents, many states run freeway service patrols. The first se rvice patrol known is the Chic ago Emergency Traffic Patrol (ETP), which began in 1960. Since then, ove r 50 freeway service patrols have been established in United States, most of which were implemented after 1990 (3). Most state DOTs operate their freeway service patrol eith er with their own st aff or on a contract basis. Freeway service patrol programs from Michigan and Texas obtained partial funds from their respective DOT and local businesses (4) The patrol vehicles rove around the freeways and provide a low tech incident detection, response, and removal system. The number of patrol vehicles and their timing depend upon the frequency of incidents, traffic on freeway, and the budget. It is very important to have a cost-effective freeway service patrol system to ensure the amount of savings due to reductions in delay, fu el, and emissions are more than the operational and

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2 administrative cost of the freeway service pa trol program. To quan tify the necessity of such a program, a detailed benefitcost analysis is necessary. 1.2 Florida Road Ranger Program To reduce the impacts of the incidents occurr ing on freeways, the Florida Department of Transportation (FDOT) has been running a fr eeway service patrol called the Road Rangers since December 1999. The program was initially used for the management of traffic incidents in the construction zones. This program has expanded to respond to all type of incidents, and has become one of the most effective elements of the Department's incident management program (5). The Road Ranger mission is to provide free highway assistance services during incidents to redu ce delay and improve safety for the motoring public. It consists of about 88 vehicles in fleet and provi des free servic e to about 918 centerlines miles (5). The Road Ranger Service Patrol is funded by the FDOT and its partners and is bid out to private contract ors. The Road Rangers are roving vehicles which patrol congested areas and high-incident locations of the urban freeways and are equipped, as a minimum, with the following eq uipment to assist as needed: cell phones, first aid kits, 2 ton jacks, fire extinguishers, flashing arrow board, reflective cones, booster cables, wood blocks, 5 gallon of sand, au to fluids, flares, ra diator water, and a public address system (5) Although each contractor has a di fferent make of vehicle, the vehicles are typically white in color with th e Road Rangers logo affixed to the rear and sides of the vehicle. Currentl y, all the seven Districts and Florida Turnpike provide the Road Ranger services except District 3. The hours of operation for District 1, 4, 5, 6 and 7 are 24 hours a day and 7 days a week; District 2 operates from 5:30 am to 7:30 pm each day; Florida Turnpike operat es from 6:00 am to 10:00 am & from 4:00 pm to 8:00 pm and 365 days a year. The number of assists provided by the Road Ranger program since its inception is li sted in Table 1.1

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3 Table 1.1 Number of Assists by Road Rangers in Year 2000-2003 Year No. of Assists 2003 316,883 2002 279,525 2001 198,372 2000 112,000 1.3 Objectives of the Study The objective of this study is to examine and evaluate the benefits of the Road Ranger service patrol against their ope rating costs in Florida. The five Districts and Turnpike were chosen due to the availability of Ro ad Ranger program data and activity logs for analysis. The year of analys is for the present study is 2004. This project was funded by the FDOT. 1.4 Organization of Thesis The rest of the thesis is organized as follo ws. The thesis is divided into 8 chapters. Chapter 2 covers the literature review of the similar studies conducted in the past. Chapter 3 describes the methodology adopted fo r the present service patrol evaluation. Chapter 4 presents the data and parameter requirements and data sources. Chapter 5 presents the details of incident data analysis for District 2, Di strict 7, District 4, District 5 and Florida’s Turnpike. Chapter 6 summarizes the estimates of benefits of the Road Ranger program and also the B-C ratio. Chapte r 7 shows the results of the sensitivity analysis performed to measur e the effect of various input variables on the model output. Finally, chapter 8 includes the summary of findings and conclusions. Chapter 8 is followed by the list of references and appendix tables.

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4 CHAPTER 2 LITERATURE REVIEW The major benefits of a freeway service patr ol program include: delay savings, reduced fuel consumption and emissions, improved tr affic flow, reduced pot ential for secondary incidents, reduced stress, and an increase d sense of security. Past studies have concentrated on the methodologies to quantify the delay savings and fuel consumption. These two aspects make up the majority of tota l benefits in terms of dollar value. Few studies were found to deal with the reduction in secondary incidents and other benefits that are difficult to quantify. Over the last decade, various methodologies have been used to calculate delays caused by incidents and savings in delay due to servic e patrols. There are certain challenges in estimating such benefits, mainly due to the measurement and co llection of certain important variables such as incident dete ction and response times (with and without freeway service patrols), reduction in roadway capacities, travel time value, and method for calculating delay. Therefore, researcher s often calculated benefit-cost ratio by assuming suitable values based on experience. The benefits of delay savings for a freeway se rvice patrol are often determined based on the detection and response times, amount of cap acity reduction, type of incident, time of day, traffic volumes, etc. However, it is impract ical to collect all of the data necessary for the precise measurement of these delay savi ngs. Some reasonable assumptions must be made. 2.1 Detection and Response Time The main objective of a freeway service patrol is to reduce the response time of incidents and provide assistance for their quick clea rance. A study in Colo rado reported, based on actual observations, that the re sponse and clearance times were reduced by an average of

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5 10.5 minutes for in-lane incidents, and an aver age of 8.6 minutes for incidents occurring outside the traveled way (6) Another study in Houston re ported an average incident duration reduction of 16.5 minutes base d on before-and-after incident data (7). A recent research by the Institute of Transportation St udies at University of California, Berkley recommended the use of 30 minutes mean re sponse time without freeway service patrol. This study also suggested calculation of res ponse time with freeway service patrol based on patrol size, beat characteristics, patrol vehicle speeds and time of day (peak, off-peak and mid-day) (8). It is very important to have appropr iate values of inci dent duration with and without the freeway service pa trol, in order to get an accura te estimate of its benefits. 2.2 Restoration Time Restoration time is the time required for traf fic to restore to its original form after clearing the incident. This time is from the mo ment when queues begin to dissipate to the moment when traffic gets back to its original pre-incident flow ra te. The restoration time can be very long for severe incidents, with long durations and heavy traffic volumes. The duration of an incident has a significant im pact on the recovery time. Freeway service patrols mostly handle minor accidents. A ma jority of these incidents occur on the shoulders or medians. In these cases, there is actually no lane blockage or traffic backup on the freeway main lanes. Therefore, the di fference in restoration time with or without freeway service patrols was not considered in the benefit analysis in past studies. 2.3 Capacity Reduction Many past analyses have focused on estimati ng the capacity reduction due to an incident. The factors determining the percentage of capacity reduction include: location of the incident (in lane, shoulder, or median), num ber of lanes on freeway, and number of lanes blocked. Some key findings incl ude: 1) the actual reduction in capacity of the freeway is much more than just blockage of lane; 2) the loss in capacity is likely to be greater than simply the proportion of original capacity that is physically blocked; 3) the effect of an incident on capacity depends on the proportion of the traveled roadway that is blocked by the stopped vehicles, as well as the number of lanes on the road way at that point (Highway Capacity Manual) ; 4) in case of multiple incidents at the same time, the

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6 capacity reduction used for the analysis shou ld be the incident which has the maximum impact on the capacity. Cuciti and Janson (6) made assumptions on roadway cap acity reduction fo r evaluation of freeway service patrols in Colorado, in terms of number of lanes lost, at the following incident locations: right or left shoulder, 0.7; left or right lane, 1.7; middle lane, 2.3; off road, 0.3. A study by Hawkins (7) measured the extent of roadway capacity reduction during incident occurrence th rough field studies in Hous ton. Hawkins estimated, for a three lane freeway segment, a 29 percent re duction in roadway capacity for a stalled vehicle located on the shoulder and roadway cap acity reduction of 52 percent for a stall or a crash blocking one lane. Similarly for a 4-lane freeway segment, Hawkins reported a 43 percent reduction in roadway capacity fo r a stalled vehicle blocking one lane, a capacity reduction of 82 per cent for blocking 3 lanes and 12. 5 percent decrease for a stall blocking a shoulder. Goolsby (9) made the first efforts in calculating the effective capacity during the incidents for certain lane and shoulder blocka ges. It was concluded that “the effective capacity loss due to incidents is more than th e effective loss due to removing a single lane on a four lane roadway”. Goolsby used de tailed incident logs coupled with video surveillance. By comparing the volumes under normal and incident conditions, he was able to predict the capacity reductions during incident conditions. Smith (10) performed a similar study, with much more detailed da ta using loop detectors and comparing the volumes under normal and incident conditions. Highway Capacity Manual (HCM ) also gives a capacity redu ction table for various types of incident blockages, as s hown in Table 2.1. But in order to use th ese tables, lateral location of the incident is required. A Freew ay Service Patrol Evaluation (FSPE) model recently developed by University of California, Berkley (8) adopted the percent of capacity remaining due to an inci dent as provided by the HCM.

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7 Table 2.1 Remaining Freeway Capacity (%) Recommended by HCM No. of Freeway Lanes/Direction Incident Type Location 2 3 4 5+ Rt Shdr 81.00 83.00 85.00 87.00 Median 81.00 83.00 85.00 87.00 Accident 1-Lane 35.00 49.00 58.00 65.00 Rt Shdr 95.00 98.00 98.00 98.00 Median 95.00 98.00 98.00 98.00 Breakdown 1-Lane 35.00 49.00 58.00 65.00 Rt Shdr 95.00 98.00 98.00 98.00 Median 95.00 98.00 98.00 98.00 Debris 1-Lane 35.00 49.00 58.00 65.00 2.4 Type of Incidents Incidents include crashes and a vast array of sm all events: stalls, flat tires, spills, debris on the road, and even highway maintenance wo rk that diverts drivers’ attention and disrupts the normal flow of traffic. The incide nt location is very important to estimate the capacity reduction on the freeway. A recent st udy by University of California-Berkley (8) defined nine types of incident based on the in cident type and location to estimate the benefits of a freeway service patrol progr am. These types included: accident (right shoulder, in lane, left shoulder), breakdown (ri ght shoulder, in lane, left shoulder), and debris (right shoulder, in lane, left shoulde r). The average time spent by a service patrol vehicle in each incident category is quite different. A clear clas sification by type of incident is very helpful to correctly estim ate the average incident duration and roadway capacity reduction. 2.5 Delay Calculation Delay saving is a major portion of the benef its of a freeway servi ce patrol program. The difference in delay between with and without fr eeway service patrol is the net benefit of the program. Two studies were conducted to estimate the delay due to incidents on I-880 in San Francisco by Skarbardonis (11) and Garib (12) Loop detectors were used to measure the speed of vehicles and probe ve hicles were used to detect incidents.

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8 Skarbardonis (11) developed a general equation which calculated delay as a function of traffic volume, time of congestion, length of impacted freeway segment, average travel speed, and travel speed during an incident. Garib (12) conducted a regression analys is of I-880 incident data to develop two models to predict incident-induced delay. The first model used four variables that included number of lanes involved, number of vehicl es involved, incident duration and traffic demand upstream of the incident. The second model excluded traffic demand upstream. Another method of calculating incident i nduced delay is queuing theory. Morales (13) developed a cumulative volume approach to calculate the delays on freeways. In his approach, two cumulative volume curves for a rrival and departure were plotted against the time axis. The area between the two curves represented the extra delay due to an incident. Lindley (14) performed a study on recurrent and nonrecurrent dela y using traffic counts from 37 cities across the nation. Sullivan (15) also used queuing theory to estimate incident-related delay. His de lay model included 4 sub-mode ls: an incident rate submodel, an incident severity sub-model, an incident duration sub-model, and delay submodel. He obtained capacity reductions from previous studies and classified incidents into seven category types. Each incident type was then matc hed to incident duration to formulate weighted average delay. Al-Deek (16) developed a method which was primarily an improvement to Morales’ me thod. Vehicle speeds were incorporated in conjunction with traffic volumes to develop a delay formula. Historical speed data were used to distinguish between incident and nonincident congestion. However, this method requires a one-minute time interval which may result in formation of “noisy” data, while larger time intervals may not allow for accura te estimation of queue boundaries. In this method, individual slices are summed up to calc ulate the total delay fo r a given segment. Pierce and Sun (17) used a video reidentification met hod to estimate the delay due to incidents. A cubic polynomial model was developed to desc ribe the travel time versus elapsed time during the incident duration. Delays were calcul ated by taking the difference between actual and the normal travel times. This method is very time consuming and labor intensive.

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9 Many service patrol agencies have used the deterministic queuing model to evaluate the benefit-cost ratio of their program. Colorado, Michigan and New York have previously evaluated their program s with queuing type models. In ad dition to queuing and real time traffic data based approaches, computer si mulation is another effective approach in modeling traffic delays due to incidents. By changing the incident durations with and without freeway service patrol, the dela y savings can be calculated. A Houston (7) study used FREQ10PC, a deterministic and macrosc opic model to find incident related delays. FREWAY3, CORSIM and XXEXQ are other simula tion models that have been used for measuring nonrecurrent delays. University of California-Berkley developed a freeway service patrol evaluation ( FSPE) model to estimate the benefit-cost ratio for the California Service Patrol (CSP). The model handles multiple time periods with different number of FSP tow trucks per time period. The FSPE model was extensively tested and applied to all existing FSP b eats in California. The FSPE model is implemented in a Microsoft Excel workbook using Visual Basic for Applications (VBA) routines in the workbook itself and in a Microsoft Excel add-in file. This method uses a deterministic queuing model and few assumptions about re sponse time reductions to evaluate delay savings. The model is also equipped with the latest emission sub-model to calculate savings on emissions. The model specification or parameters can be changed to suit local conditions. 2.6 Costs of Freeway Service Patrol Most state Departments of Transportation f und and operate the freeway service patrol, either on their own or on a contract basis. In some cases, local and state police or metropolitan transportation authorities fund the patrolling services. The source of funding comes from fuel taxes, Department of Motor Vehicles fees, and/or a percentage of state or local sales taxes. In case of funding from the federal government, the dollars frequently come from congesti on mitigation and air quality (CMAQ) funds, construction funds, or highway safety funds. In some cases, the funding is sponsored exclusively by private agencies. An example of this is the Samaritan patrol program. The Samaritan patrols operate in 11 northeastern United States metropolitan areas. The patrols

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10 are operated by Samaritan, Inc. and funde d by large corporations such as CVS pharmacies, First Union Bank, and Bank of Bo ston. Some privately operated programs get their funds from turnpike authorities, which use collected tolls to support the program. The main cost components of a service pa trol program are capital, administrative and operating costs. The annual co st of a freeway service patr ol depends upon the number of center-line miles covered, hours of operation, a nd number of vehicles maintained. Metro freeway service patrol in Los Angeles, which maintains a fleet of 150 vehicles and covers about 650 center line miles, costs about $20 million annually (3). Chicago, Washington D.C., Oakland, Orange county (C A) are other places which ma intain a fleet of over 50 vehicles and provide 24 hour service. These pr ograms cost a few million dollars annually. There are places which have freeway servi ce patrols operating only during the peak hours. These systems typically maintain a low fleet of vehi cles and cost just a few hundred thousand dollars annually (3). 2.7 Benefit-Cost Ratio Past studies carried out for various freeway service patrols showed greater benefit value than cost. The benefit-cost ratio ranges from low 2:1 to high 36:1 (4 ). Table 2.2 table shows the reported benefit-cost ra tio of several existing programs (3)

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11 Table 2.2 Results of Service Patrol Benefit-Cost Studies Patrol Location Patrol Name Year Performed Results Charlotte, NC Incident Management Assistance Patrol 1993 3:1 to 7:1 Chicago, IL Emergency Traffic Patrol 1990 17:1 Dallas, TX Courtesy Patrol 1995 3.3:1 to 36.2:1 Denver, CO Mile High Courtesy Patrol 1996 20:1 to 23:1 Detroit, MI Freeway Courtesy Patrol 1995 14:1 Fresno, CA Freeway Service Patrol 1995 12.5:1 Houston, TX Motorist Assistance Program 1994 6.6:1 to 23.3:1 Los Angeles, CA Metro Freeway Service Patrol 1993 11:1 Minneapolis, MN Highway Helper 1995 5:1 New York, NY Highway Emergency Local Patrol 1995 23.5:1 Norfolk, VA Safety Service Patrol 1995 2:1 to 2.5:1 Oakland, CA Freeway Service Patrol 1991 3.5:1 Orange Co., CA Freeway Service Patrol 1995 3:1 Riverside Co., CA Freeway Service Patrol 1995 3:1 Sacramento, CA Freeway Se rvice Patrol 1995 5.5:1

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12 CHAPTER 3 METHODOLOGY There have been many previous studies on th e evaluation of the freeway service patrol programs. The methodologies have been focuse d on how to estimate the benefits of delay and fuel savings by a freeway service patrols. Most of these studies rely on extensive field data to estimate the delay caused by incidents, which is very time and labor consuming. Also most of these delay models are region specific and need additional efforts for the calibration and data collecti on before it can be applied to other regions. Few past studies have focused on developing a complete evaluation tool for estimating the benefit and cost ratio of a freeway patrol program. The Freeway Service Patrol Evaluation (FSPE) Version 12.1 tool developed by University of California at Berkeley is one such tool that was developed to evaluate freeway services patrol. The FSPE model uses Microsoft Excel workbooks for all inputs and outputs. The MS Excel interface makes the model user-friendly, convenient, and simple in terms of entering the data and obtaining the results. The inputs are used by FSPE’s internal Visual Basic for Applications (VBA) progr am to estimate the hourly traffic flows that are then used to estimat e the incident induced vehicular delays and delay reductions due to Freeway Service Pa trol (FSP) service. The model uses a deterministic queuing model for the purpose of calculating delay. The delay model uses VBA code implemented as built -in modules (directly contai ned in the workbook’s sheets) to accommodate the more de tailed queuing model. The m odel estimated delay saving benefits based on the beat’s geometric and tr affic characteristics, and the frequency and type of FSP-assisted incidents. For measur ing fuel and emission savings, it uses the Emissions Factor (EMFAC) mode l with the latest mobile source emission rates published by California Air Resource Board (CARB). Th e inputs required by the model mainly include the beat characteristics, traffic volum es, and incidents. The model distributes the various incident types over the study segm ent during the service period proportional to

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13 the Vehicle Miles Traveled (VMT) in that se gment during different periods of the day. It uses traffic profiles of the study area a nd AADT volumes on the study segments to calculate VMT during different times of the day and assigns incidents accordingly. It calculates the benefits for one average day using the input information and multiplies it by number of days of service to give the total benefit. The model uses the capacity reduction factors given by HCM 2000 to calculate the delay caused by incidents and uses a deterministic queuing model. The differenc e in delay with and without the patrol service would be the vehiclehours saved and the net benefit of the service patrol. The model recommends 30 minutes response and de tection time without the service patrol. Response time with service patrol is calcula ted using the beat length, truck speed, and number of trucks patrolling at time of evaluation on the study beat. To apply the FSPE model to evaluate the Fl orida Road Ranger Program, the model has to be calibrated to suit Florida tr affic and roadway conditions. The California freeway service pa trol is provided in peak pe riods, and there is no service during the non-peak periods. Hence, the model input fo r hours of operation doesn’t account for non-peak hours. Since most of th e Florida Road Ranger programs provide 24 hour service, the model has to be calibrated to evaluate and account for non-peak hours. The FSPE model calculates the benefits by considering average daily traffic and distributing incidents on the selected beat segment proportio nal to the VMT traveled. An important feature of the model is that it di stributes incidents based on the VMT traveled, which is estimated by Average Annual Daily Tr affic volume data and traffic profiles. In this way, the model output is not affected by how the hours of operation ar e distributed over AM peak, mid-day and PM-peak periods. The model is formulated for California Freeway Service Patrol, which is a peak period service. So, if an incident is entered for 11:45 PM and its average duration is 45 minutes then the program enters into the next day and gives erratic results. This is because the program has not been developed in a manner to evaluate complete 24 hours. So, wh ile performing delay benefit estimation for Florida Service Patrols, the total time of evaluation was kept from midnight to 11:15 PM, so that the incident will not go into the next day.

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14 Model parameters are the default values used to estimate hourly traffic volumes, delay, and fuel consumption savings. The model provi des default values for various parameters in the PARAMS worksheet. These default valu es can be changed to replicate the local conditions. Below are listed seve ral of the parameters used in the model to estimate B-C ratio. 1. The freeway capacity for mixed use lanes is taken from the Highway Capacity Manual ( HCM ). According to the HCM, the spee d of passenger cars at flow rates that represent capacity is about 55 mph, a nd the flow rate corresponding to this speed could be approximated as about 2250 pcphpl. Howeve r, for actual analysis a lower capacity of 2100 pcphpl is used cons idering the high percentage of older driver population. 2. The reduction values in HCM will be used to estimate the remaining capacity on freeway due to various incidents. 3. Reduction in response times is the difference between response time without Road Ranger service and the headway of patrol ling vehicles. It has been found that without patrol service detection/respons e times are generally approximately 30 minutes. The headway of patrolling vehicle was computed by using the beat length divided by the number of patrolling vehicl es and the speed of patrolling vehicles. Average speed of patrolling vehicles is assumed to be approximately 30 mph. 4. The average fuel costs per gallon in Florida are: $ 1.52 in 2002, $ 1.63 in 2003, and $ 1.96 in 2004, respectively (18) 5. According to Texas Transportation Inst itute (TTI) Urban M obility Report 2005, travel time value for each person hour of travel is $13.45 in 2004, and for trucks is $71.05. Assuming average vehicle occupa ncy of 1.5 (NHTS Survey 2001), and percentage of trucks in total traffic as 5% the travel time value for present analysis is taken as $ 22.71. Travel Time Value = $13.45*1.5*0.95 + $71.05*0.05=$22.71

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15 Finally, the traffic volumes, road way geometry, and traffic prof iles for each district were collected and input to FSPE models. The calib rated FSPE models for each district were then applied to perform the benefit-cost an alysis of Road Ranger program in each FDOT district and the Turnpike.

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16 CHAPTER 4 DATA COLLECTION AND PROCESSING In this study, the FSPE model was calibrated to fit Florida roadway, traffic and Road Ranger service conditions. The calibrated FSPE model will be used to perform the benefit-cost analysis of th e Road Ranger program in FDOT districts and the Florida Turnpike. The data required for evaluating the Florida Road Ranger program using the FSPE model can be classified into 4 chief categories: 1. Beat/Service description 2. Beat design characteristics 3. Traffic data 4. Incident data 4.1 Beat/Service Description The service description includes only information such as district name, beat name, date, and name of analyst. Beat characteristics in clude information related to the Road Ranger program on the beat that is being evalua ted such as hours of operation, number of patrolling vehicles, number of service days per year, cost of each ve hicle ($/truck-hr), and total number of assists per year. Costs of tr uck include the cost paid by FDOT to the private contractor per truck hour for running the Road Ranger prog ram. All the data regarding cost and operation of the Road Ranger program were obtained from respective Road Ranger District managers or the contract or providing the service. Each district in which the Road Ranger program is operational has its own contractor and also maintains the Road Ranger logs recording informati on about the type, time and duration of the incident assisted. As each district has its own contractor, the cost of program varies from district to district. The cost of the truck per hour is about in th e range of $27.00 to $41.00.

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17 4.2 Beat Design Characteristics Each study beat is divided in to various segments for each travel direction. Each segment is similar in geometric design, capacity (numbe r of lanes) and traffic volumes. Data are entered for each travel direction on a segm ent, including: length (miles), number of mixed flow lanes, HOV lane (i f any), and presence of shoulders. All the data regarding beat design characteristics can be obtained from Florida Traffic Information CD (FTI, 2003). 4.3 Traffic Data For each segment of the study beat, the Averag e Annual Daily Traffic and Directionality factors (AM, Mid-day and PM peak periods) are required for analysis. Traffic data are obtained from FTI CD. Also the program require s traffic profiles for various districts in order to calculate the hourly traffic volumes for each beat se gment. Traffic profiles are estimated using the Florida Traffic Info rmation CD (2003). The FSPE model requires traffic profiles for the entire district to calcu late the hourly distribution of traffic for each segment of the beat being evaluated. Traffic profile is the percentage distribution of traffic volumes during the day. Each hour in a day corresponds to a percentage value, which represents the percent of total daily volume that flows during that hour. To estimate the traffic profiles for each district 24 hour traffic count s along (and around) freeways being evaluated are determined. Thes e traffic volume values are then used to calculate the percentage of traffic during a particular hour of day, for each of the 24 hours. It should be noted that hourly traffic counts from all the site s on the service roads in a district are used to calcul ate percentage of traffic. Tabl e 4.1 shows the traffic profiles of all the districts and Turnpike in Florida. Traffic data used for this study are contained in Appendix A.

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18 Table 4.1 Traffic Profiles (Time of the Day Distribution of Traffic) of Various Districts in Florida Hourly Interval District 1 District 2 District 4 District 5 District 6 District 7 Turnpike Midnite-1 0.87 0.94 1.09 1.01 1.29 1.18 1.07 1-2 0.56 0.57 0.67 0.64 0.79 0.77 0.67 2-3 0.43 0.57 0.57 0.51 0.54 0.62 0.54 3-4 0.40 0.46 0.59 0.57 0.55 0.65 0.54 4-5 0.74 0.62 0.90 0.88 0.84 0.97 0.82 5-6 1.86 1.53 2.14 2.33 1.93 2.19 2.00 6-7 4.77 4.53 5.52 5.34 4.75 5.20 5.02 7-8 7.38 7.39 7.70 7.07 6.60 6.72 7.14 8-9 6.92 7.09 7.39 6.71 6.42 6.32 6.81 9-10 5.67 5.33 5.55 5.88 5.58 5.58 5.60 10-11 5.73 5.20 5.00 5.28 5.23 5.56 5.33 11-Noon 5.60 5.75 4.94 5.61 5.43 5.72 5.51 Noon-1 5.59 6.29 4.99 5.53 5.54 5.68 5.61 1-2 5.84 6.08 5.16 5.67 5.61 5.53 5.65 2-3 6.05 6.10 5.66 5.79 5.32 5.54 5.74 3-4 7.25 6.53 6.40 6.35 6.79 6.03 6.56 4-5 7.62 7.56 7.48 6.47 6.85 6.81 7.13 5-6 8.39 8.10 8.11 7.36 7.37 7.26 7.76 6-7 5.81 5.66 6.57 5.91 6.26 5.89 6.02 7-8 3.87 4.01 4.39 4.27 4.76 4.40 4.28 8-9 2.97 3.14 2.98 3.32 3.57 3.32 3.22 9-10 2.47 2.75 2.54 3.22 3.42 3.28 2.95 10-11 1.95 2.17 2.19 2.44 2.69 2.59 2.34 11-Midnite 1.26 1.62 1.48 1.83 1.89 2.16 1.71 4.4 Incident Data The incident data required for the FSPE m odel include typically the total number of assists during the evaluation pe riod, type of incident, and m ean duration (in minutes) of incident. Herein the mean duration of a particul ar incident type is the actual time spent by the Road Ranger team at the site of an incident. It does not include response and detection time of the incident. The FSPE mode l has divided all the incidents into nine categories depending upon the lateral location of incidents. The model considers three types of incidents: accident, breakdown and debris. For each category, there is a subcategory for location of incident. For inst ance, if the incident has occurred on right shoulder, left shoulder, or bl ocked a lane. The incident loca tion will directly affect the

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19 capacity reduction on the freeway as taken from the HCM. The HCM suggests that the reduction in freeway capacity is same for incidents occurring on the left or right shoulders. The incident related information is obtai ned from Road Ranger l ogs. After reviewing Road Ranger logs, it was found that the incident s were classified into ten main categories. They are: accidents, flat tires, fuel, cell phones, jump start, debris, minor repairs, overheated, abandoned and tow to shoulder. In order to use the FSPE tool, these ten categories needed to be regroupe d into the same three catego ries as the FSPE model. The accident and debris from Road Ranger logs ar e defined the same as in the FSPE model. All the others, such as flat tires, fuel, cell phones, jump start, minor repairs, overheated and abandoned vehicles, are considered in the breakdown category. However the Road Ranger logs do not have any information regard ing the lateral location of incidents. The model however requires the late ral location for each incident type. Empirically, it has been found that about 35 per cent of the accidents occur in the lane. Breakdowns mostly occur on right shoulder while 82 percent of debris is in the lane inci dents. It should be noted that the incidents blocking more than one lane are very rare and hence are ignored during the present study. Tabl e 4.1 gives an approximate percentage for lateral occurrences of three incident types. In absen ce of sufficient data from the Road Ranger logs, these percentages are used to evaluate the freeway patrol program. Table 4.2 Percentage of Incident Occurrence by Lateral Location Incident % Incidents Type/Location Accident Right Shoulder 55.9% Lt Shldr (Median) 9.4% 1-Lane 34.6% Breakdown Right Shoulder 89.6% Lt Shldr (Median) 5.3% 1-Lane 5.0% Debris Right Shoulder 14.2% Lt Shldr (Median) 3.3% 1-Lane 82.4%

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20 4.5 Limitations of the Incident Data The present study obtained all the incident re lated data from the Road Ranger incident logs. This data typically included: type of incident, duration, location, time and date of the incident. The accuracy and consistency of the data is ve ry important factor in the delay estimation process. Any discrepancies a nd inconsistencies in the data can influence the results of the study. During the present st udy many inconsistencies in the data were observed in terms of type of data collected and the data recording process. No District (except for District 6) provided any informati on related to the lane blockage due to the incident, which is an important parameter in determining the decrease in capacity of the roadway section. In numerous cases the data was entered as text; such type of data entries can be understood onl y when read in person an d through computer queries. However, in dealing with large data sets like incident logs, th e data should be entered in a format easily queried and searched through computer software. In many occasions the type of incident was written down as text in single column instead of having different columns for each type and assigning a dummy variable. It was also found that there was no uniformity in entering the te xt description e.g. an incide nt caused due to “break down” can be written as: Brk down, Break Down, breakdown, vehiclebreak down etc. Use of different abbreviations and text descriptions slows down the process of data processing and querying. Also, there is no standardization about the classification of incidents across the Districts. Similarly, the location of the incidents is described based on the nearest interchange which again had different text de scriptions for the incidents occurring at the same location. Noting the incidents based on th e mile point, makes location more precise and easy to locate or geocode. The incident time and duration information is absent in some Districts. In that case the duration values for these dist ricts had to be assumed as an average of other districts. This can have so me impact on the benefit-cost ratio estimation process. Duration of incident is an important value in delay calculations. All incident logs provide information only about the time of arri val at the scene of incident and departing time. The difference of these two times is the clearance time of the incident during which the Road Rangers were present a nd not the total duration of the incident. Also lots of data entries regarding the time were found to be ab surd and incorrect. During data analysis a

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21 large number of incidents with zero and negati ve durations were dete cted. It is necessary to have consistent and error free data for effective evaluation and analysis.

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22 CHAPTER 5 INCIDENT DATA ANALYSIS 5.1 Incident Frequency and Characteristics The incident data were obtained from review ing Road Ranger logs in each district. The incident data formats are different in diffe rent districts. Since some districts have different service period, inci dent rate was defined as the average number of incidents served or assisted per hour of the service pe riod. Incident rates do not represent the actual number of incidents occurring. This is because the entire incident da ta is extracted from the Road Ranger logs, which implies the data only include the incidents that have been assisted by the Road Rangers during the se rvice period. Table 5.1 shows the number of incident and incident rates in each district per month. Table 5.1 Number of Incident and In cident Rates in Each District District Service Period (Hours per day) Coverage Area (miles) No. of Incidents Per Month Incident Rate (Incidents Per Service Hour) 2 14 102 1103 2.5 4 24 111 3638 4.9 5 24 74.5 2704 3.6 6 24 85 7273 9.8 7 24 34.5 2573 3.5 Turnpike 8 332 4468 18.0 Florida 20 739 21759 7.1 Table 5.2 shows the percentage of incidents by type in variou s districts and the Turnpike. It is noted that approximately 81% of all th e incidents are the brea kdown type incidents. Flat tires are the most frequently occurring in cident (average 23% of all incidents) in the

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23 breakdown category. Accidents an d debris account for a very small portion of the total incidents. Table 5.2 Percentage Distribution of Inci dents by Type in Various Districts Percentage Distribution of Incidents by Type in Various Districts and Turnpike Breakdown District Flat Tire Fuel Cell Phone Jump Start Minor Repairs Over heat Abandoned Tow to Shoulder Call Wrecker Breakdown Accident Debris 2 32 17 1 5 8 N/A 21 6 N/A 91 4 4 4 34 12 2 4 7 7 14 4 N/A 85 8 7 5 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 6 21 10 4 4 7 8 25 5 N/A 84 13 4 7 28 11 4 4 6 7 26 5 N/A 91 9 0 Turn-pike 15 8 0 2 10 N/A 17 0 6 59 6 35 Average Florida 23 10 3 6 9 5 19 4 1 81 9 10 The District 2 Road Ranger program is not a 24 hour service and is operational on 4 highways, I-95, I-10, I-295 and the Turner Bu tler road. The hours of operation are 5:30 AM through 7:30 PM. All the incident data is taken from Road Ranger logs and hence the records show the incident s occurring during the 14 hour period of service and for 9 months (Jan-Sep). All the inci dents reported in the logs are classified into the following 9 main categories: accident, debris, cell phone, jump start, tow-transport, minor repairs, fuel, abandoned and flat tires. The Road Ranger logs contained information about the break (restroom or fuel) taken by the driver and about weather related delays. All those cases were deleted for the present analysis as they don’t contribute to any benefit. As the FSPE model recognizes only 3 main types of incidents i.e. accident, debris and breakdowns, all the categories name ly, flat tires, fuel, minor repairs, tow-transport etc. were clubbed together as break downs for the purpose of calculating the benefit-cost ratio. It was found that during most months I-295 recorded the maximum number of incidents about 340 incidents per month, whic h makes it almost 24 assists every hour. Interestingly, I-295 has low AADT volumes co mpared to other road s but has th e highest

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24 incident rate. This might also be due to the fact that I-295 has the highe st coverage (34.35 miles) followed by I-95 (31.76 miles), I-10 ( 20.33 miles) and the Turner Butler (12.31 miles). The monthly distribution of incidents in District 2 are shown in figure 5.1. For all interstates (I-95, I-295 and I-10) the incident rate is higher during the summer months (April-August). The number of incidents fo r January, February and September are considerably low compared to other months It was also found th at May recorded less incidents when compared to other summer months. However on Turner Butler the number of incidents remained same thr oughout the study period (Jan-Sep) with an average of 103 incidents each month except for March and May where number of incidents bumped up. Of all the incidents during a 9 month period in Dist rict 2, flat tires are the most frequent ones. Almost 22-35 % of all the incidents are flat tires. Flat tire, fuel and abandoned vehicles alone comprise of about 60-70 % of the total incidents across all the months and on a ll the roads in District 2. A ccidents and debris, though low in number cause more delay and capacity re duction. Also, the probability of an accident or debris blocking a lane is higher than that for breakdown type of incidents. Figure 5.1 Monthly Distribution of Incidents in District 2 0 50 100 150 200 250 300 350 400 450 January February March April May JuneJuly AugustSeptember I-10 I-95 I-295 Turner Butler Road

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25 The Road Ranger program in District 4 op erates on I-95 (Broward County and Palm Beach County), I-75 and I-595. Data taken from Road Ranger logs reported a total of 3615 incidents. Out of the total 3615 report ed incidents, 2248 happened on I-95. Service on I-95 is almost 68 miles long and has high tr affic volumes and therefore accounts for most incidents in District 4. Flat tire is the most frequent type of incident followed by fuel (see figure 5.2). On I-95 alone, about 700 flat tire incidents occurred during a single month. I-75 and I-595 have almost the same nu mber of reported inci dents of different types with most incidents of the flat tire and fuel type. On I-95 flat tire, fuel and abandoned vehicles cover about 63% of the total in cidents. Each freeway had about 8% accidents and almost the same percentage of debris. It is observed that flat tire and fuel type incidents are more common th an any other kind of incident. Figure 5.2 Number of Incidents by Type in District 4 The data from District 5 records contain on ly the number of stops for each month. For 2004, the data is available only for months January through August. There is no information regarding the type of incident or duration. Th e only information provided is 0 100 200 300 400 500 600 700 800 Flat TireFuelCell PhoneJump Start Minor Repairs Overhea t AbandonedTow to Shoulder N o ServiceAccidentDebris I-95 I-75 I-595

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26 the total number of stops by month. In 2003, the Road Ranger service made a total of 30,965 stops and already about 24,338 stops from January to August in 2004. Monthly distribution of total incidents in District 5 are shown in figure 5.3. The analysis for B-C ratio requires incident types a nd their duration. For district 5, due to unavailability of data these values were assumed. Th e percentage of breakdowns, debris and accidents were assumed to be 86, 6 and 8% respectively. Th e incident durations used for estimating benefits are the average incident du rations from the other districts. Figure 5.3 Monthly Distribution of Incident Number in District 5 District 6 Road Ranger logs provide comple te information about the incidents on 10 service freeways for one year. The Road Ra nger logs provided the complete incident information on all the patrolled freeways along with the lateral loca tion of each incident. District 6 reported about 96,000 incidents for year 2004. After removing incomplete data and double counted incidents, a total of 88,114 incidents were analyzed in this study. The Road Ranger service in District 6 is a 24 hour service and covers about 89 miles. Table 5.3 shows incident rates on different freeways. Incident rates have be en expressed as the 0 500 1000 1500 2000 2500 3000 3500 4000 JANFEBMA R AP R MAY JUNJUL AUG SEP OCT N OV DEC 2003 2004

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27 Fuel 10% Cell Phone 4% Jump Start 4% Minor Repairs 8% Overhea t 9% Abandoned 20% Tow to Shoulder 5% Accident 13% Debris 4% Flat Tire 23% number of incidents per hour. It can be seen that I-95, SR 836 and SR 826 have the highest incident numbers and corresponding rates. This is because these freeways have high coverage miles and they experience very high traffic volumes. Incident analysis shows that 46% of the incidents attended by the Road Ranger program were flat tire and abandoned vehicles. The percentage of accidents in District 6 was high compared to other districts. Accidents were 13% of the total in cidents. Breakdown type incidents form the highest percentage. Almost 83% of the in cidents were breakdowns. Figure 5.4 shows the distribution of various incidents by their type in District 6. Table 5.3 Incident Rates on the Freeways in District 6 Freeway Study Period Service Period (Hours per day) Coverage Area (miles) No. of Incidents Incident Rate (No. of incidents per hour ) I-75 1 year 24 6.978 4927 0.56 I-95 1 year 24 17.26 18667 2.13 I-395 1 year 24 4.27 1439 0.16 I-195 1 year 24 4.341 1661 0.19 SR 836 1 year 24 11.952 12067 1.37 SR 112 1 year 24 4.112 3839 0.44 SR 878 1 year 24 3.118 1203 0.14 SR 826 1 year 24 24.19 31882 3.63 SR 924 1 year 24 5.378 3310 0.38 SR 874 1 year 24 6.949 9119 1.04 District 6 1 year 24 89 88114 10.03 Figure 5.4 Percentage Distribution of In cidents by Type in District 6

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28 The Road Ranger program in District 7 is a 24 hour service and is operational on I-275, I4 and SR-60. However, due to data unavailab ility, only one stretch of I-275 was analyzed for the month of August. All the data was ta ken from Road Ranger logs and was in MSAccess format. There were many incidents th at were double counted e.g. an incident marked as fuel and flat tire, accident and minor repair or accident and debris. All such double counted incidents were removed and assi gned to either accide nt or debris with priority to accident. Since most accidents i nvolved debris removal, most of them were counted and assigned as accidents only. The incidents which said “no service” were completely removed as these are the cases wh ere Road Ranger patrol s didn’t provide any benefit/help. It was found that on I-275 almo st 53 % of the incidents attended by the Road Ranger patrols were flat tires and abandoned vehicles. Debr is had a very low percentage (about 0.23 %). Interestingly, the nu mber of accidents is quite high on I-275 with almost 186 accidents occurring during th e 1 month period. All other breakdown type incidents are very low in number varying between 9-13 %. Figure 5.5 shows the number of incidents by each type on I-275. Figure 5.5 Number of Incidents by Type on I-275 in District 7 I-275 District 70 100 200 300 400 500 600 700Flat TireFuelCell PhoneJump StartMinor RepairsOverheatAbandonedTow to Shoulder AccidentDebris

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29 Road Rangers cover the entire Turnpike main line (mile point 0 to 309), Turnpike Golden Glades Spur (mile point 0X to 4X) and Sawg rass Expressway. However, service operates only during the peak hours during 6 to 10 in the morning and 4 to 8 in the evening. The entire region is divided into 14 patrol zone s with one truck assigne d to each zone. The zones 1 to 7 lie in southern z one and 8 to 14 in northern zo ne. The data is available for North and South zones; however zone wise da ta is not available. However, since each zone varies with respect to AADT volumes and number of lanes the benefit-cost ratio is calculated for each zone separately. Since zone wise data is not available, so the number of incidents is distributed to each zone according to the VMT traveled in that zone. The VMT in each zone was determined by multiplying AADT into segment length. The data classifies incidents into 11 different categories: ac cident, abandoned vehicle, dead/injured animals, large debris, small debris, fuel, flat tire, jump start, minor repairs, car wrecker and no assistance. All “no assist ance” type incidents are deleted and dead animal, small and large debris are grouped to gether as debris. The 8 hour daily Road Ranger service attended almost 59,622 incide nts through out the ye ar. Surprisingly, unlike other districts, for the turnpike region, debris is the most frequent incident type. Debris account for almost 35% of the total inci dents. Flat tire and abandoned vehicles are next most occurring incidents (see figure 5.6) January and February have low incident rates compared to the other months while N ovember has the highest incident rate (see figure 5.7).

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30 Figure 5.6 Number of Incidents by Type in Turnpike Region Number of Incidents by Type Turnpike0 200 400 600 800 1000 1200 1400 1600 1800 2000 Flat TireFuelJump StartMinor RepairsAbandoned Vehicle Call WreckerAccidentDebris January February March April May June July August September October November December Figure 5.7 Monthly Distribution of Incidents on Turnpike Number of Incidents by Month Turnpike0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% JanuaryFebruaryMarchAprilMayJuneJuly AugustSeptemberOctoberNovemberDecember Debris Accident Call wrecker Abandoned vehicles Minor repairs Jump Start Fuel Flat Tire

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31 5.2 Incident Duration The total incident duration includes the inci dent clearance time and response time. The incident clearance time is calculated as the difference between the Road Ranger truck arrival time and the time it leaves the incide nt scene. The response time is calculated as the difference between the time the incident happened and the Road Ranger arrival time. The average response time is co mputed by the FSPE model us ing the beat length, average truck speed and number of patrol trucks. Table 5.4 shows the in cident duration by type of incident in each district. It should be noted that the incident duration here does not include response time. It is the difference in time from when Road Ranger service arrives at the scene of an incident and the time when the incident is cleared. It is found that flat tire, jump start, minor repairs, and tow to shoulder have a duration of about 20 minutes. Accidents averaged about 44 minutes for all of Florida. Breakdown type incidents have a duration of 14 minutes and debris averaged about 10 minutes. Table 5.4 Incident Duration by Type in Minutes in Each District In District 2, it was found that accidents had the highest duration with an average of 23 minutes. Among the breakdowns, flat tires had the maximum duration; and the occurrence of flat tire incident s is more frequent than any ot her type of incident. In this Breakdown District Flat Tire Fuel Cell Phone Jump Start Minor Repairs Overheat Abandoned Tow to Shoulder Call Wrecker Break down Accident Debris 2 15 10 11 13 10 N/A 9 11 N/A 12 23 5 4 18 11 20 20 19 17 5 17 11 15 38 7 5 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 6 20 14 8 20 21 18 8 22 N/A 15 49 14 7 17 9 23 19 18 16 6 25 11 14 40 13 Turnpike N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A Florida 19 13 9 19 20 18 8 20 11 14 44 10

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32 way flat tires are causing more delay than any other type of incident. Most other breakdown type incidents have a duration around 10 minutes. In District 4, it is observed that duration of in cidents is almost the same irrespective of the incident type for the 3 freeways. Figure 5.8 shows the incident durations for three freeways in District 4. Accidents have a higher duration than other incidents. On average, an accident lasted fo r 48, 33 and 40 minutes on I-75, I-95 and I-595, respectively. Fuel and debris have lesser durations of about 11 and 6 minutes. All other break-down type incidents have a duration with in the range of 16-20 minutes for all the 3 freeways. Figure 5.8 Incident Duration in Minutes by Type of Incident in District 4 Incident Duration District 4 0 10 20 30 40 50 60 Flat TireFuelCell PhoneJump StartMinor Repairs OverheatAbandonedTow to Shoulder AccidentDebris I-75 I-95 I-595 Since there is no incident durat ion data available for Distri ct 5, the incident durations used for estimating benefits are the average incident durations for all other districts. Durations for breakdown, debris, and accidents are assumed to be 14, 10 and 44 minutes respectively In District 6, flat tire, jump start, minor repairs and tow to shoulder have a duration of about 20 minutes. Cell phone and abandoned vehi cles have a low duration of 8 minutes

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33 while accidents have the highe st duration, 50 minutes. The deta il of incident durations on each of the patrolled freeway is shown in table 5.5. Table 5.5 Average Duration in Minutes by Type of Incident in District 6 Freeway Flat Tire Fuel Cell Phone Jump Start Minor Repairs Overheat Abandoned Tow to Shoulder Accident Debris I-75 19 21 24 19 21 21 14 25 34 12 I-95 24 19 23 25 27 23 9 26 53 15 I-395 20 22 7 21 26 19 22 20 57 10 I-195 18 18 11 24 22 20 11 26 59 19 SR 836 27 20 19 27 25 25 16 25 46 12 SR 112 30 21 21 30 29 29 24 29 63 12 SR 878 23 17 9 33 32 27 19 21 57 15 SR 826 22 20 21 23 23 23 20 25 48 19 SR 924 24 21 15 26 29 27 15 26 55 8 SR 874 26 21 18 27 30 27 14 22 55 8 District 6 24 20 19 25 26 24 16 25 50 15 In District 7, accidents have the maximum average duration of 40 minutes followed by tow to shoulder type incidents (average 24 minutes). Except for fuel and abandoned vehicles, all other breakdown type incidents had an aver age duration between 17-19 minutes. Fuel and abandoned vehicles have a low average duration of 9 and 6 minutes respectively. Figure 5.9 shows the av erage incident durations on I-275.

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34 Figure 5.9 Incident Durations in Minutes on I-275 in District 7 Incident Duration I-275 District 70 5 10 15 20 25 30 35 40Flat TireFuelCell PhoneJump StartMinor Repairs OverheatAbandonedTow to Shoulder AccidentDebris The Road Ranger logs for the Turnpike don’t have any information about the duration of incidents. Hence, for the analysis and calc ulation of benefit-cost ratio, the average duration in other districts was used as the in cident duration for the Turnpike Enterprise. 5.3 Lateral Distribution of Incidents Lateral distribution of incident refers to the location of the incident on the road i.e. on lane or shoulder (left or right). This info rmation is important to determine the loss in freeway capacity. Different incident types ha ve different tendencie s to occur along the road width. An accident would be more likely to block one or more lanes as compared to a flat tire (breakdown) type in cident which is more likely to occur on the shoulder. While estimating B-C ratio for the Florida Road Ranger program, it was found that logs maintained by the contractors did not contain sufficient information related to the lateral distribution of the incidents in most of dist ricts. Hence, a suitable assumption based on the past studies had to be made to evaluate the benefits of the program. Only District 6 logs maintained information about the latera l position of the incident attended. Table 5.6

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35 shows the percentage of incidents of each ty pe according to their position along the road width. All values are in percentage and the al l the freeways are in District 6. Also shown in the table is the percentage that was a ssumed for the present study. According to the HCM, the capacity reduction in case of an incide nt is same for left and right shoulder. Table 5.6 Lateral Distribution (%) of Incidents in District 6 I-95 I-395 I-195 SR 836 SR 112 SR 878 SR 826 SR 924 SR 874 District 6 Assumption for other districts Accident Right Shoulder 43.24 45.64 45.89 51.20 27.64 34. 67 74.57 35.48 30.48 58.74 55.90 Left Shoulder 26.32 10.76 20.54 20.09 7.72 22. 67 19.03 17.42 21.57 20.52 9.40 Lane 30.44 43.60 33.57 28.70 64. 63 42.67 6.40 47.10 47.95 20.74 34.60 Breakdown Right Shoulder 80.12 80.66 86.42 73.21 51. 04 46.34 85.70 53.34 48.98 74.43 89.60 Left Shoulder 14.76 7.55 3.96 9.54 6. 50 12.89 13.05 6.21 14.02 12.18 5.30 Lane 5.12 11.79 9.62 17.25 42. 46 40.78 1.25 40.45 37.00 13.39 5.00 Debris Right Shoulder 27.36 17.70 6.75 32.19 23. 17 11.00 74.63 27.61 16.57 43.15 14.20 Left Shoulder 4.56 50.00 10.81 14.17 5. 69 9.00 1.28 5.22 5.43 6.22 3.30 Lane 68.08 32.30 82.44 53.64 71. 14 80.00 24.09 67.16 78.00 50.63 82.40

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36 CHAPTER 6 BENEFIT AND COST ANALYSIS The benefits of the Road Ranger Program in clude reduced vehicular delays and fuel savings to the motorists because of the reduction in the incident delay and fuel consumption, and the reduction in the vehicu lar emissions. Apart from these visible benefits, a freeway service patrol reduces th e number of potential secondary crashes by quickly removing and clearing in cidents. It also benefits the road user s by reducing mental agony and anxiety. However, these bene fits are difficult quantify. For the present study, only vehicular delay, fuel and emi ssion savings have been included. 6.1 Delay and Fuel Savings Delay and fuel savings by the Road Ranger se rvice were calculated by the FSPE model described previously. The model was calibra ted for each district by inputting traffic profile, incident data, traffi c volumes, and beat information. As mentioned earlier, the travel time value has been estimated at $22.71 and fuel price at $1.96. The study also estimates savings in three t ypes of emissions, nitrogen oxides (NOX), carbon monoxide (CO) and reactive organic gases (ROG). Howeve r, due to difficulty in assigning a dollar value to the pollution, they have not been included in the final benefit-cost ratio. The monthly delay and fuel savings for each dist rict are summarized in Table 6.1. I-75 has BC ratio less than 1 as incident occurrence a nd traffic volumes are low compared to the capacities. SR 924 for District 6 is not include d in the table as it showed 0 benefits for similar reasons. However, in computing the overall B-C ratio for entire District 6 the cost of operation on SR 924 was included.

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37 Table 6.1 Benefit-Cost Ratio of Road Ranger Program in Each District District 2 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio I-10 2,916 66,212 3,599 7,054 74,831 13,665 6 I-295 683 15,518 1,031 2,020 17,538 27,330 1 I-95 2,628 59,677 3,963 7,768 67,444 27,330 3 Turner Butler Road 1,163 26,402 1,753 3,436 29,838 13,665 2 Total 7,389 167,809 10,346 20,278 189,651 81,990 2 District 4 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio I-75 16,522 375,215 24,922 48,847 424,062 90,036 5 I-595 18,260 414,685 27,544 53,986 468,671 90,036 5 I-95 239,809 5,446,062 361,734 708,999 6,155,061 150,060 41 Total 274,591 6,235,962 414,200 811,832 7,047,794 330,132 21 District 5 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio I-4 29,947 680,105 45,173 88,540 768,645 60,375 13 District 6 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio I-75 115 2,610 173 340 2,950 25,550 0 I-95 224,574 5,100,073 338,754 663,958 5,764,032 77,390 75 I-395 8,970 203,704 13,530 26,519 230,223 17,155 13 I-195 2,503 56,845 3,776 7,400 64,246 17,155 4 SR 836 296,902 6,742,648 447,856 877,799 7,620,447 52,025 147 SR 112 6,751 153,319 10,184 19,960 173,279 35,950 5 SR 878 20,216 459,096 30,494 59,768 518,864 23,325 22 SR 826 87,594 1,989,267 132,130 258,975 2,248,242 127,750 18 SR 874 57,378 1,303,045 86,550 169,638 1,472,683 35,960 41 Total 705,003 16,010,608 1,063,448 2,084,357 18,094,965 435,584 42 District 7 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio I-275 80,051 1,817,958 120,751 236,672 2,054,630 117,400 18 Turnpike Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio Northern Zone 13,299 302,028 20,058 39,313 341,341 53,802 6 Southern Zone 28,589 649,245 43,088 84,453 733,698 53,802 14 Overall Turnpike 41,888 951,273 63,146 123,766 1,075,039 107,604 10 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio FLORIDA 1,138,869 25,863,715 1,717,064 3,365,445 29,230,724 1,133,085 26

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38 6.2 Costs The costs of the Road Ranger service are diffe rent in each District. The monthly costs of the Road Ranger program in each di strict are listed in Table 6.1. 6.3 Benefit and Cost Ratio A measure of the Road Ranger program cost -effectiveness was estimated by calculating the benefit/cost ratio based on the monthly delay and fuel benefits to the motorists. The value of time for estimating the delay sa vings was taken as $22.71 per hour assuming average vehicle occupancy of 1.5 and percentage of trucks in total traffic as 5%. The cost of fuel was taken as $1.96 per gallon for the year 2004. The monthly benefit/cost ratios for five districts and Florida Tur npike are summarized in Table 6.1. As shown in Table 6.1, the overall benefit/cos t ratio for the whole Florida Road Ranger program is 25.8:1. The range of benefit/cost rati os for each district varies from 2.3:1 to 41.5:1. The average benefit and cost ratio of entire Road Rangers program is approximately 26:1. Two freeways (I-75 and SR 924 in District 6) show a benefit/cost ratio less than 1. The possible reason is low incide nt rates and low traffic volumes on these highways as compared to their capacities. When v/c is ve ry small, the FSPE model will not be able to estimate delay and fuel savings. The Turnpike is divided into total of 14 z ones (named 1 through 14). The zones 1-7 lie in southern region and 8-14 in the northern re gion. The evaluation results from the model output showed no benefits in zones 9, 10, 11 a nd 14 for the Turnpike District. The reason that these four zones show no benefit is that traffi c volumes on these zones are considerably low compared to their capacities. It was found that in the above zones the maximum volume/capacity (v/c) ratio was belo w 0.3. When the v/c ratio is very small, the FSPE model will not estimate delay and fu el savings. Although there is no benefit of the program in 4 of the 14 zones, overall the benefits exceed the total cost of the Road Ranger program in the Turnpike wi th a B/C ratio of almost 10.

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39 Appendix C contains the additional detail re garding the benefit-cost ratio on each freeway segment in each district. The savi ngs in vehicle emissions are included in Appendix D.

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40 CHAPTER 7 SENSITIVITY ANALYSIS 7.1 Introduction Sensitivity Analysis is the study of how the out put changes with change or variation in the conditions that effect the output. There ar e many situations when a system needs to be studied in terms of how the various inputs into the model change the model output. Example of these systems include simulation models used to forecast weather, traffic flow models, traffic delay models, chemical reactions, etc. These models are built to simulate or mimic reality. Many of these models are theoretical in nature, consisting of a series of equations, input factors and parameters to describe a certain process. The aim of these models is to approximate the real life processes. Sensitivity Analysis is closely tied to uncertainty analysis, which determines to find the uncertainty in output by using the variation in the input variables. The basic intent of conducting all sensitivity analysis is to determine: the factors that mostly contribute to the output variabili ty, region in the space of input factors for which the model output va riation is maximum, the optimal regions, the model parameters that are insignificant a nd can be eliminated from the final model, etc. In the present benefit-cost ratio study of the Road Rangers Program, a delay model is used to estimate the delay savings due to th e freeway service patrol program. The model uses various input parameters and set of complex mathematical equations to find the delay savings. As the model has been develo ped as a computer software using Visual Basic Applications (VBA), it becomes diffic ult to find the effect of various input variables on the model output. It is impossible to do all calculations and observe the effects of change in input variables on th e output. Therefore, to know this effect a sensitivity analysis is conducted. Broadly, a ll methods of sensitiv ity analysis can be classified into two categories: local anal ysis and global analys is. Local analysis concentrates on measuring the local impact of the factors or i nput variables. Global methods describe sensitivities over a whole area of interest. They need more observations and more complex sampling design. Sensitivity in one variable at a time is usually called

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41 a one at a time (OAT) method. This me thod cannot give information about the interactions in the pr ediction variables. Local methods have simple procedures and an easy sample design which does not demand much observations. In this study OAT method is used to know the trend in the outpu t on affecting the input variables. A more general attempt has been made in the present study to know how the various input factors affect the delay estimation. Delay savings (and hence Benefit-Cost rati o) estimated by the FSPE model is mainly affected by the follo wing input factors: Average Annual Daily Traffic Volumes (AADT), mean response time to incidents without Road Ranger service, frequency of incidents on the segment, capac ity of segment, number of service trucks, Segment length etc. There are other factors such as, incident du rations, percent of incidents by type, directional AADT factors, traffic profiles and la teral distribution of incidents of each type that affect the incide nt related delays. But these parameters have been kept constant in evaluating the sensitivity as their effect is significantly less. In this study the Florida wide average values have been used for these set of parameters as discussed earlier in the secti on. The input factors and how th ey influence the output are discussed in the following sections. 7.2 Mean Response Time Without Road Ranger Service Response time is the time in minutes that is required for the emergency vehicles to reach and respond to the incident. It is the time elapsed between th e occurrence of the incident and the time at which the response vehicle reaches the incident scene. This is an important variable as the di fference between the response times with and without Road Ranger service directly affects the amount of delay savings and hence Road Ranger benefits. This study used the average respons e time without Road Rangers Service to be 30 minutes. The response time with the serv ice is computed using number of trucks, segment length, truck speeds, etc. To perfor m the sensitivity analys is for mean response time 2 sections of 5 mile and 15 mile were considered. Both sections are 6 lanes wide with an average AADT of 150000. Mean re sponse time without the Road Rangers Service is varied between 25-35 minutes with an interval of 5 minutes, and B-C ratio is computed for the two segments. Also, for each segment B-C ratio is calculated separately for different number of patrolling trucks. Truck speeds have been kept constant at 30

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42 mph. It is important to include the number of patrolling truc ks and segment length as they would straightaway affect the time to detect and respond to the incidents. Figures 7.1 and 7.2 show the results for 5 mile and 15 mile segment respectively. The results are as expected i.e., there is an increase in B-C ra tio with increase in re sponse time without Road Rangers program. However, it can be seen that the for 5 mile section the B-C ratio is highest for 1 patrolling truck and for 15 mile section highest B-C ratio is for 3 patrolling trucks. This is because in 5 mile segment 3 trucks would not drastically bring down the response times. Though a slight decrea se would be observed, but the cost of the program would also go up due to increased cost of 3 patrolling trucks. However on the 15 mile segment keeping 3 trucks would be mo re beneficial in terms of reducing the response times compared to a single truck on a 15 mile stretch. As the segment length is more, three trucks are more effective comp ared to single truck patrolling the long segment. In order to understa nd the general effect of mean response time without Road Rangers service, another analysis on a 10 m ile section with two patrolling trucks was completed. The results are shown in figure 7.3. It is observed that th e benefit-cost ratio increases considerably as the mean respons e time without Road Ra ngers is increased. This means the Road Ranger service has more benefit in areas wh ere other services available are poor than the areas where the ex isting services are effi cient or have lower mean response times.

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43 Figure 7.1 Change in Benefit-Cost Ratio With Mean Response Time Without the Service on a 5 mile Section With Different Number of Service Trucks 0.00 5.00 10.00 15.00 20.00 25.00 253035Mean Response Time Without Road Rangers (in minutes)B-C Ratio 1 Truck Service 2 Truck Service 3 Truck Service Figure 7.2 Change in Benefit-Cost Ratio With Mean Response Time Without the Service on a 15 mile Section With Di fferent Number of Service Trucks 0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 90.00 253035Mean Response Time Without Road Rangers (in minutes)B-C Ratio 3 Truck Service 2 Truck Service 1 Truck Service

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44 Figure 7.3 Change in Benefit-Cost Ratio With Mean Response Time Without the Service on a 10 mile Section With Two Service Trucks 0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 510152025303540 Mean Response Time Without Road Rangers (in minutes)B-C Ratio 7.3 Capacity Capacity of the roadway is the maximum flow it can accommodate. Capacity is one of the parameters that has to be provided to the FSPE model for B-C ratio estimation. It is very exhaustive to go in the field and measure capacities of different roadway sections. Using past experience, capacity for the pr esent study is assumed to be 2100 pcphpl. Volume-capacity ratio (V/C) would directly influence the benefit of the Road Rangers program. That means clearing an incident dur ing the full capacity would save more on vehicular delays than assisting an incide nt during the non-peak hours. Freeways having high capacity (other characteristics remain ing same) would give lesser benefit. To understand the sensitivity of B-C ratio to capac ity, a 6 lane 10 mile segment with average AADT of 150,000 was chosen. B-C ratio on the segment was calculated by changing the capacity parameter only. Figure 7.4 shows the resu lts. It is found that the B-C ratio drops down as the road capacity is increased. This is expected because each incident causes a

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45 specific reduction in capacity. If capacity of th e road section is high, it implies that for the same incident patterns V/C ratios are lower for high capacity roads. Figure 7.4 Change in Benefit-Cos t Ratio With Freeway Capacity 5.00 10.00 15.00 20.00 25.00 30.00 19002000210022002300Capacity (vehphpln) B-C Ratio 7.4 Number of Incidents Number of incidents should directly increa se the benefits. During the study it was found that many road segments showed much le ss benefit because incident rates on those segments were low. In Florida the average in cident rates for year 2004 were found to be about 30 incidents per mile per month. Road Rangers would have more benefit on freeways receiving more incidents. The results are shown in figure 7.5. The graph was plotted by running the model for a 10 mile, 6 lane freeway with AADT of 150,000. All the other parameters were kept constant and the number of incidents for a one month period were increased between 200 and 1300. The graph shows an increase in B-C ratio at almost a constant gradient.

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46 Figure 7.5 Change in Benefit-Cost Ratio With Number of Incidents Per Month on the Beat Segment 0.00 10.00 20.00 30.00 40.00 50.00 60.00 20050080010001300No. of Incidents per monthB-C Ratio 7.5 Average Annual Daily Traffic The amount of traffic on the segment would dete rmine the savings in vehicle hours. If the traffic on a segment is very low, then the re duced capacity of roadwa y could be sufficient for the flowing traffic to pass without causing much delays. In this case Road Rangers program would be less benefici al. Similarly, the program woul d be more effective during the peak hour compared to off peak hours. Th is way we can see that the B-C ratio for the program would be high in the ar eas with high traffic volumes. To test the sensitivity, the model was run for a 4-lane segment of 10 miles. Separate curves were plotted for 1 and 2 trucks. Figure 7.6 shows that increase in AADT keeping other variables constant, increased the B-C ratio. It can be seen that the rate of growth gets rapid on increase in AADT volumes.

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47 Figure 7.6 Change in Benefit-Cos t Ratio With AADT Volumes 0.00 1.00 2.00 3.00 4.00 5.00 6.00 4500050000550006000065000AADT (vehicles per day)B-C Ratio 4-lane, 10 mile section, 1 truck 4-lane, 10 mile section, 2 trucks 7.6 Value of Travel Time (Dollars Per Vehicle-hour) The value of travel time for the present study for all delay quantifying purpose was used to be $22.71. Vehicular delay savings is the main component of the benefits of the Road Rangers program, hence value of travel time would be very critical in estimation of B-C ratio. High value of travel time value woul d estimate higher benefi ts and consequently higher B-C ratio study. As the main delay comp onents are vehicle delay savings and fuel savings, therefore for a particular case if a ll other variables are kept constant and only travel time value is varied then a linear relationship between B-C ratio and travel time value would be seen as shown in figure 7.7. Here a 10 miles section with AADT of 150,000 and 500 incidents a month is considered.

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48 Figure 7.7 Change in Benefit-Cost Ra tio With Value of Travel Time 0.00 1.00 2.00 3.00 4.00 5.00 6.00 15913172125 Value of Travel Time (dollars per vehicle-hour)B-C Ratio 7.7 Patrolling Truck Speed The speed of patrolling truck is essential in determining the response time to the incidents. Higher truck speeds would redu ce mean response time to incidents and consequently increase the benefits. Figure 7.8 shows the variation of B-C ratio with truck speed. As the truck speed is increased initially there is greater change in the benefit-cost ratio but the curve flattens out at the sp eed of about 30 mph. This means increasing further speed beyond 30 mph w ould not produce any significant increase in the benefits. As the truck speed is increased the response time to an incident, i.e. time required to detect and respond to the incident decreases. Consequently, the effective duration of the incident goes down and it is cl eared off quickly. Therefore, the benefits of the program would also increase due to quick detection, response and removal of the incident.

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49 Figure 7.8 Change in Benefit-Cost Rati o With Patrolling Truck Speed 0.00 5.00 10.00 15.00 20.00 25.00 5101520253035Patrolling Truck Speed (mph)B-C Ratio 7.8 Summary The benefit-cost ratio of the Road Ranger program depends on variety of factors that include: beat characteristics and service charac teristics. The beat characteristics include traffic conditions (AADT), lengt h, number and type of incide nts, number of lanes etc. Service characteristics include number of patrolling trucks, service period, speed of trucks, etc. The existing traffic volumes have greater impact on the be nefits of the service than any other variable. If there is a Road Ranger service on a high traffic volume segment its service would be more useful th an on a segment with low traffic volumes. This is because on high traffic volume segments even a small reduction in capacity due to incident can cause queue build up and traffi c delays. However, in low traffic volume segments, the remaining capacity may be suffici ent for traffic to go through. Similarly, as the capacity of the freeway is increased, the benefit is reduced considerably. The mean response time without Road Range r service determines the impact that Road Rangers can make in quickly detecting and clearing incide nts. Suppose, if the mean response time to incidents without Road Rangers service is not significantly differe nt from the response time with the service, then pr esence of Road Ranger service would not give any benefit.

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50 So, the areas with high respons e time without the Road Ra nger service will have more benefit from such a service than the areas which are alre ady having good response times without any Freeway Patrol se rvice. Also, program would yi eld greater benefit on areas experiencing high incident rates.

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51 CHAPTER 8 CONCLUSIONS The purpose of this study was to evaluate th e effectiveness of th e Road Ranger program in Florida. Five FDOT Districts and Florida’s Turnpike were selected for analysis due to the availability of Road Ranger data and activity logs. The FSPE model was calibrated for each district to estimate delays, fuel saving, and benefit/cost ratios. Traffic incident data were collected from each district Road Ranger activity log. Incident data were collected for at least one mont h and as long as one year depending on the availability of electronic Road Ranger logs. Additional data including the traffic volumes, geometry and capacity information, traffic profile and the cost of the Road Ranger program in each district were also complied. The findings from the analysis of incident da ta and benefits of the Road Ranger program are summarized below: 1. The Road Rangers have been found to assi st over 7.1 incident s every hour in a given district. The number of per hour assi sts in the Turnpike area is about 18.31; showing the need for expansion of such an incident management program. 2. The type and duration of incidents vary from one district to anot her. In general it is found that the most frequent incident type s occurring are breakdowns. Accidents and debris have a very small portion. However, in the Turnpike it is found that debris is almost 30 % of the inci dents. In other districts, debris formed a very small percentage. Flat tire is th e most frequent inci dent followed by fuel type incidents. In District 2, flat tires are about 22-35 % of all the incidents during different months. In the same district fl at tire, fuel and abandoned vehicles make up almost 65% of the total incidents. On I-275 in District 7 during a one month period (August) 53% of th e incidents assisted were flat tires or abandoned vehicles. The Road Ranger program on I95 in District 4 had 700 flat tire

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52 incidents assisted during a single month (J uly). This shows that flat tires are the most frequently attended incidents by Road Rangers followed by fuel type. It is clear that small incidents like flat tire fuel and minor repairs occur more often than accidents and debris. Frequency of occurrence of accidents in most districts is low compared to other type of incidents, but accidents last much longer than any other type of incident. 3. The study found that on average an accident lasted for about 44 minutes; break down and debris average durat ion is 14 minutes and 10 mi nutes respectively. It is observed that the incident durat ions for a particular incide nt in a district are quite close irrespective of the freeway. 4. The latest FSPE Beat Evaluation (FSPE) Model was found to be effective in evaluating the freeway serv ice patrol. The model uses capacity reduction values from the HCM and assigns incidents on freeway segments according to the vehicle miles traveled on that segment. The reduction in incident detection and response times with freeway service pa trols is an important parameter in determining the savings in delay with fr eeway patrol as opposed to not having one. The model estimates reduction in response times using number of patrol vehicles, their speed, beat length, etc. A deterministic queuing model is used to estimate the congestion related delay savings. 5. The estimated net benefits based on the average incident delay and fuel savings indicate that the Road Range r program produces significant benefits in all the five districts. The overall benefit/cost ratio for the Florida Road Ranger program is 25.8:1. The range of benefit/c ost ratios is from 2.3:1 to 41.5:1. The benefit/cost ratios for District 2, 4, 5, 6, 7, and Tur npike are approximately, 2:1, 21:1, 13:1, 42:1, 18:1, and 10:1, respectively. 6. The Road Ranger service provided additiona l benefits that were not included in the calculation of the benefit/cost rati o. The daily reductions in air pollutant emissions include a total of 3690 kg of reactive orga nic gases, 160 kg of carbon monoxide and 740 kg of oxides of nitrogen. In addition, the presence of Road

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53 Ranger service provides a sense of security on the freeway, and the quicker removal of incidents could reduce secondary accidents. The results of this study confirm that the Florida Road Ranger service is a successful, cost-effective operational progr am. The calibrated FSPE models for each district can be directly applied for future performance eval uation. Efforts should be directed to collect and maintain consistent formatted activity l ogs. Currently, the Road Ranger logs do not contain any information regarding the late ral location (shoulder or in lane) of the incidents except for District 6. Road Ranger lo gs from certain districts do not have any information regarding the duration of incide nts. There is a need to investigate and quantify the safety benefits of the Road Ranger service. Evaluation of safety effects requires data on incident patt erns, accidents, and congestio n levels over a long period of time. The present study required incident data li ke: the average durati on by type and lateral location of the incidents. All the data for the study was taken from the Road Ranger logs. However, because of lack of certain info rmation that was required to perform the evaluation, the study utilized many key variable s from other research. The Road Ranger logs do not contain any information regard ing the lateral location of the incidents (shoulder or in lane). So, for the purpose of the present study, the percent distribution of various incidents laterally was taken from previous researches on this topic. Road Ranger logs from certain districts do not have any in formation regarding the duration of incidents and hence the duration values for these dist ricts was assumed to be the same as the average over other districts. Duration of inci dents can significantly impact the calculated delay savings and accuracy of the results. Many of the free ways for which the incident duration is available does not contain comp lete information like: response times and restoration times. Road Range r logs should record informa tion related to response and restoration times. Response time can be approximated by interviewing the person being assisted and restoration time is from when the in cident is cleared to the time the traffic is restored to normal. The reduction in res ponse times with and without Road Ranger service is an important variable and can affect the accuracy of the results. To find the complete duration of incidents from the point it started to th e point it is cleared would

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54 require extensive field studi es and data collection. To fully understand the incident pattern and duration more rea listic data would be require d. The present study does not account for savings in secondary crashes and in this way the benefits of the Road Ranger services are underestimated. The secondary crash reduction estimation would require database of past years and real time current data. The ambiguity in travel time value and the average fuel cost could also aff ect the results of the present study.

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55 REFERENCES 1. Dutta, R. Tadi, D. Devadoss, M. Poola. Freeway Courtesy Patrol as a Roadside Assistance Program: Experience of Two Large Metropolitan Areas. Presented at the 76th Annual Meeting of the Transportation Research Board, Wa shington DC, 1997, January 12-16. 2. Masinick J. and Hualiang Teng, Rubberneck ing Impacts of Accidents on Traffic in Opposite Directions, Research Project Report for ITS Implementation Center, Center fro Transportation Studies, University of Virginia, August, 2004. 3. Fenno D. and M. Ogden. Freeway Service Patrols: A State of the Practice. Transportation Research Record 1634 Transportation Research Board, National Research Council, Washington DC, 1998, pp 28-38. 4. Latoski S., R. Pal, and K. Sinha. A Cost Effectiveness Evaluation of the Hoosier Helper Freeway Service Patrol. Final Re port, Phase 1 FHWA/IN/JTRP. September, 1998. 5. Florida Department of Transportation Traffic Systems and Operations. Freeway Service Patrol. www.dot.state.fl.us/trafficopera tions/rrangers/rdranger.htm. Accessed April 2005 6. Cuiciti P. and B. Janson. Incident Manage ment via Courtesy Patrol: Evaluation of Pilot Program in Colorado. Transportation Research Record, 1494. Transportation Research Board, National Research Council, Washington DC, 1995. 7. Hawkins P. A. Evaluation of the South We st Freeway Motorist Assistance Program in Houston. Report No. TX-94/1922-IF, Texa s Transportation Institute, College Station, Texas, 1993. 8. Skabardonis A. and M. Mauch. FSP Beat Ev aluation and Predictor Models: Users Manual, Research. Report No. UCB-ITS-RR-2005-XX, Institute of Transportation Studies, University of California-Berkley, California, 2005. 9. Goolsby, M. Influence of Incidents on Freeway Quality of Service. Highway Research Record, No. 349, Transportati on Research Board, Washington DC, 1971. 10. Smith, B., L. Qin and R. Venkatanarayana Characterization of Freeway Capacity Reduction Resulting From Traffic Accidents. Journal of Transportation Engineering, 2003.

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56 11. Skabardonis A., K. Petty, H. Noeimi, D. Rydzewski and P. Varaiya. I-880 Field Experiment: Data-base Development and Incident Delay Estim ation Procedures. Transportation Research Record 1554 Transportation Research Board, National Research Council, Washington DC, 1996. 12. Garib A., A. E. Radwan, H. Al-Deek. Estimating Magnitude and Duration of Incident Delays. Journal of Tran sportation Engineering, Vol. 139, 1997. 13. Morales J. Analytical Procedures for Estimating Freeway Traffic Congestion. ITE Journal of Transportation Engineering. Volume: 123, 1987. 14. Lindley J. Urban Freeway Congestion: Quantification of the Problem and Effectiveness of Potential Solu tions. ITE journal: volume: 57, 1987. 15. Sullivan, E. New Model For Predicting Freeway Incidents And Incident Delays. Journal of Transportation Engineering, Paper no. 13592, 1997. 16. Al-Deek, A. Garib and A. Radwan. Met hods for Estimating Freeway Incident Congestion, Part II: New Methods Pa per submitted to ASCE Transportation engineering journal. 17. Pierce R., C. Sun and J. Lemp. Incident Delay Modeling with the Use of Video Reidentification. CD-ROM. Transporta tion Research Board, Annual Meeting, Washington D.C., 2005. 18. http://www.floridastategasprices.com/

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57 APPENDICES

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58 Appendix A: Traffic Data Table A.1 Traffic Profiles of Various Districts in Florida Hourly Interval District 1 Dist rict 2 District 4 District 5 Di strict 6 District 7 Turnpike Midnite-1 0.87 0.94 1.09 1.01 1.29 1.18 1.07 1-2 0.56 0.57 0.67 0.64 0.79 0.77 0.67 2-3 0.43 0.57 0.57 0.51 0.54 0.62 0.54 3-4 0.40 0.46 0.59 0.57 0.55 0.65 0.54 4-5 0.74 0.62 0.90 0.88 0.84 0.97 0.82 5-6 1.86 1.53 2.14 2.33 1.93 2.19 2.00 6-7 4.77 4.53 5.52 5.34 4.75 5.20 5.02 7-8 7.38 7.39 7.70 7.07 6.60 6.72 7.14 8-9 6.92 7.09 7.39 6.71 6.42 6.32 6.81 9-10 5.67 5.33 5.55 5.88 5.58 5.58 5.60 10-11 5.73 5.20 5.00 5.28 5.23 5.56 5.33 11-Noon 5.60 5.75 4.94 5.61 5.43 5.72 5.51 Noon-1 5.59 6.29 4.99 5.53 5.54 5.68 5.61 1-2 5.84 6.08 5.16 5.67 5.61 5.53 5.65 2-3 6.05 6.10 5.66 5.79 5.32 5.54 5.74 3-4 7.25 6.53 6.40 6.35 6.79 6.03 6.56 4-5 7.62 7.56 7.48 6.47 6.85 6.81 7.13 5-6 8.39 8.10 8.11 7.36 7.37 7.26 7.76 6-7 5.81 5.66 6.57 5.91 6.26 5.89 6.02 7-8 3.87 4.01 4.39 4.27 4.76 4.40 4.28 8-9 2.97 3.14 2.98 3.32 3.57 3.32 3.22 9-10 2.47 2.75 2.54 3.22 3.42 3.28 2.95 10-11 1.95 2.17 2.19 2.44 2.69 2.59 2.34 11-Midnite 1.26 1.62 1.48 1.83 1.89 2.16 1.71

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59 Appendix A (Continued) Table A.2 Freeway and Traffic Characteristics in District 2 District 2 Segment I-10 1 2 3 4 5 6 7 8 9 10 Mile Point 3.28-11.48 11.48-15.65 15.56-16.16 16.1617.27 17.27-18.55 18.55-19.25 19.25-20.12 20.12-20.53 20.53-21.17 21.17-21 .67 Segment L 8.2 4.17 0.6 1.11 1.28 0.7 0.87 0.41 0.64 0.5 Lanes 4 4 4 4 6 6 6 6 6 6 AADT 45735 57500 70500 99500 102000 110000 117500 122000 147022 116500 I-10 1 2 3 4 5 6 7 8 9 10 Mile Point 0.75-2.60 Segment L 1.85 Lanes 6 AADT 139000 District 2 Segment I-295 1 2 3 4 5 6 7 8 9 10 Mile Point 3.07-4.87 4.87-9.59 9.59-11.70 11.7015.93 15.93-17.44 17.44-19.37 19.37-20.61 20.61-22.19 22.19-24.7 24.7-27.66 Segment L 1.8 4.72 2.11 4.23 1.51 1.93 1.24 1.58 2.51 2.96 Lanes 6 6 6 6 6 6 6 6 6 6 AADT 108000 119000 88000 83500 96000 108500 106000 78000 65000 54000 I-295 1 2 3 4 5 6 7 8 9 10 Mile Point 27.66-29.96 29.96-31.64 31.64-33.31 33.31-35.06 35.06-35.51 0-.37 0.37-1.91 Segment L 2.3 1.68 1.67 1.75 0.45 0.37 1.54 Lanes 6 6 6 6 6 6 6 AADT 47500 47500 44000 52500 47000 47000 43500 District 2 Segment I-95 1 2 3 4 5 6 7 8 9 10 Mile Point 0.7-2.6 2.6-3.89 3.89-4.62 4.62-5.22 5.22-5.83 5.83-7.13 7.13-7.89 7.89-9.26 9.26-10.59 0.2.23 Segment L 1.9 1.29 0.73 0.6 0.61 1.3 0.76 1.37 1.33 0.2 Lanes 6 6 6 6 6 6 6 6 6 4 AADT 139000 147500 124500 124000 132500 115000 88000 89500 78500 46000 I-95 1 2 3 4 5 6 7 8 9 10 Mile Point 2.23-3.77 3.77-6.36 0-5.46 5.466.59 6.59-7.36 7.36-9.31 9.31-11.64 11.64-13.09 13.09-13.47 13.47-15.27 Segment L 1.54 2.59 5.46 1.13 0.77 1.95 2.33 1.45 0.38 1.8 Lanes 6 4 6 6 6 6 6 6 6 6 AADT 62000 47500 71000 131000 127000 98000 121000 134500 110500 12220 I-95 1 2 3 4 5 6 7 8 9 10 Mile Point 15.27-16.79 0-0.75 Segment L 1.52 0.75 Lanes 6 6 AADT 119000 160500 District 2 Segment TB Road 1 2 3 4 5 6 7 8 9 10 Mile Point 0.51-1.11 1.11-3.03 3.03-4.11 4.115.22 5.22-6.30 6.30-8.22 8.22-10.05 10.05-12.09 12.09-12.82 Segment L 0.6 1.92 1.08 1.11 1.08 1.92 1.83 2.04 0.73 Lanes 4 4 4 4 4 4 4 4 4 AADT 78500 73000 81500 82000 8500 74500 61500 57500 39000

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60 Appendix A (Continued) Table A.3 Freeway and Traffic Characteristics in District 4 District 4 Segment I-595 1 2 3 4 5 6 7 8 9 10 Mile Point 0-1.1 1.1-2.09 2.09-3.07 3.07-4.07 4.07-4.59 4.59-6.13 6.13-8.39 8.39-10.44 Segment L 1.1 0.99 0.98 1 1.52 1.54 2.26 2.05 Lanes 6 6 6 8 8 8 8 6 AADT 140000 154000 143500 172000 181725 164500 182500 97500 District 4 Segment I-95 1 2 3 4 5 6 7 8 9 10 Mile Point 24.63-25.29 0-1.54 1.54-2.78 2.785.22 5.22-8.37 8.37-14.78 14.78-16.26 16.32-17.75 17.79-20.31 20.31-21.59 Segment L 0.66 1.54 1.24 2.44 3.15 6.41 1.48 1.43 2.52 1.28 Lanes 8 8 8 8 8 8 6 6 6 6 AADT 203000 203000 195000 186000 181500 168000 154500 141000 168500 168500 I-95 1 2 3 4 5 6 7 8 9 10 Mile Point 21.58-23.56 23.56-24.94 24.98-25.95 25.9627.21 27.22-28.43 28.47-31.28 31.28-33.00 33.03-34.76 34.76-36.95 37.00-4 0.38 Segment L 1.98 1.38 0.97 1.25 1.21 2.81 1.72 1.73 2.19 3.38 Lanes 6 6 6 6 6 6 6 6 6 6 AADT 166500 166500 140000 140000 148631 153000 171500 142000 115000 99000 I-95 1 2 3 4 5 6 7 8 9 10 Mile Point 40.38-44.18 44.18-46.02 0-7.49 7.6112.29 12.29-13.96 14.06-21.77 16.56-17.26 0-7.4 0.75-1.52 1.52-2.54 Segment L 3.8 1.84 7.49 4.68 1.67 7.71 0.7 7.4 0.77 1.02 Lanes 6 6 6 6 6 6 8 8 8 6 AADT 88526 67500 67500 58500 49500 42000 220000 212000 239394 259000 I-95 1 2 3 4 5 6 7 8 9 10 Mile Point 2.54-5.15 5.15-6.16 6.16-7.66 7.669.24 9.24-9.79 9.79-11.28 11.29-13.41 13.51-14.09 14.09-15.08 15.08-16.26 Segment L 2.61 1.01 1.5 1.58 0.55 1.49 2.12 0.58 0.99 1.18 Lanes 8 8 8 8 8 8 8 8 8 8 AADT 272000 279000 275000 275000 288000 288000 278000 259000 259000 260000 I-95 1 2 3 4 5 6 7 8 9 10 Mile Point 16.29-20.38 20.43-21.59 21.5923.68 23.68-24.63 24.63-25.28 0-1.54 Segment L 4.09 1.16 2.09 0.95 0.65 1.54 Lanes 8 8 8 8 8 8 AADT 243000 222800 200460 206000 203000 203000 District 4 Segment I-75 1 2 3 4 5 6 7 8 9 10 Mile Point 0-2.2 2.20-4.02 4.02-4.78 4.785.44 0-1.54 1.54-5.44 5.44-7.71 7.71-9.48 9.54-12.13 Segment L 2.2 1.82 0.76 0.66 1.54 3.9 2.27 1.77 2.59 Lanes 6 6 6 6 6 6 6 6 6 AADT 107000 102500 95500 138500 143500 113500 116500 125000 131500

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61 Appendix A (Continued) Table A.4 Freeway and Traffic Characteristics in District 5 District 5 Segment I-4 1 2 3 4 5 6 7 8 9 10 Mile Point 0-3.63 3.63-4.18 4.18-6.58 6.587.89 0-1.09 1.09-2.63 2.63-5.52 5.52-6.27 6.27-8.26 8.26-9.95 Segment L 3.63 0.55 2.4 1.31 1.09 1.54 2.89 0.75 1.99 1.69 Lanes 6 6 6 6 6 6 6 6 6 6 AADT 91000 61000 85000 116060 124000 147500 119000 151000 155582 122000 I-4 1 2 3 4 5 6 7 8 9 10 Mile Point 9.95-11.07 11.07-12.30 12.30-13.65 13.6515.02 15.02-15.53 15.53-16.84 16.84-17.18 17.18-17.5 17.5-18.31 18.31-18.8 Segment L 1.12 1.23 1.35 1.37 0.51 1.31 0.34 0.32 0.81 0.49 Lanes 6 6 6 6 6 6 6 6 6 6 AADT 127500 120500 147000 146500 171000 184500 175083 171500 154500 138000 I-4 1 2 3 4 5 6 7 8 9 10 Mile Point 18.8-19.65 19.65-20.41 20.41-21.30 21.3022.85 22.85-24.02 24.02-24.67 0-1.46 1.49-3.47 3.47-8.26 8.26-10.49 Segment L 0.85 0.76 0.89 1.55 1.17 0.65 1.46 1.98 4.79 2.23 Lanes 6 6 6 6 6 6 6 6 6 6 AADT 160000 134000 165000 166000 143000 103000 103000 126000 123133 95000 I-4 1 2 3 4 5 6 7 8 9 10 Mile Point 10.49-14.13 0-3.51 3.51-6.37 6.37-9.52 9.52-11.64 11.64-14.2 14.2-24.5 24.5-28.02 Segment L 3.64 3.51 2.86 3.15 2.12 2.56 10.3 3.52 Lanes 6 6 6 6 6 6 6 6 AADT 84500 79500 79500 74500 53500 49500 45000 39000

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62 Appendix A (Continued) Table A.5 Freeway and Traffic Characteristics in District 6 District 6 Segment I-95 (9) 1 2 3 4 5 6 7 8 9 10 Mile Point 0-0.975 0.9751.535 1.535-3.234 3.234-5.455 5.455-6.069 6.069-6.236 6.2367.261 7.2618.792 8.792-9.795 9.79510.798 Segment L 0.975 0.56 1.699 2.221 0.614 0.167 1.025 1.531 1.003 1.003 Lanes 4 6 6 6 8 10 10 10 10 10 AADT 64500 64500 138000 207000 207000 207000 225000 262000 220000 221000 I-95 (9) 1 2 3 4 5 6 7 8 9 10 Mile Point 10.79812.091 12.09112.653 12.653-13.208 13.20813.669 13.66914.351 14.35116.555 16.55517.26 Segment L 1.293 0.562 0.555 0.461 0.682 2.204 0.705 Lanes 10 8 8 8 8 8 8 AADT 237000 237000 185000 185000 185000 176000 220000 District 6 Segment I-195 (1) 1 2 3 4 5 6 7 8 9 10 Mile Point 4.794-4.91 4.423-4.794 2.136-4.423 0.793-2.136 0.569-0.793 Segment L 0.116 0.371 2.287 1.343 0.224 Lanes 4 5 6 6 3 AADT 99000 99000 96580 96580 96580 District 6 Segment I-395 (2) 1 2 3 4 5 6 7 8 9 10 Mile Point 3.174-2.454 2.454-0 13.048-11.952 Segment L 0.72 2.454 1.096 Lanes 6 6 4 AADT 74000 90344 106500 District 6 Segment I-75 (7) 1 2 3 4 5 6 7 8 9 10 Mile Point 0-0.251 0.251-2.202 2.2024.019 4.019-4.778 4.778-5.442 0-1.536 Segment L 0.251 1.951 1.817 0.759 0.664 1.536 Lanes 6 8 8 8 8 8 AADT 107000 107000 102500 95500 138500 143500 District 6 Segment SR 836 (6) 1 2 3 4 5 6 7 8 9 10 Mile Point 0-0.828 0.828-1.261 1.261-3.28 3.28-4.263 4.263-4.801 4.801-6.36 6.36-7.919 7.9198.462 8.462-9.497 9.49710.579 Segment L 0.828 0.433 2.019 0.983 0.538 1.559 1.559 0.543 1.035 1.082 Lanes 5 6 6 6 6 6 6 6 6 6 AADT 92000 92000 131893 119500 201500 191500 185000 139500 167500 146500 SR 836 (6) 1 2 3 4 5 6 7 8 9 10 Mile Point 10.57911.381 11.38111.952 Segment L 0.802 0.571 Lanes 6 4 AADT 127500 121000 District 6 Segment SR 874 (4) 1 2 3 4 5 6 7 8 9 10 Mile Point 0-1.545 1.545-2.181 2.181-3.703 3.703-4.114 4.114-6.949 Segment L 1.545 0.636 1.522 0.411 2.835 Lanes 6 4 8 4 4 AADT 74000 74000 118000 118000 45500 District 6 Segment SR 878 (3) 1 2 3 4 5 6 7 8 9 10 Mile Point 2.271-2.658 2.271-0.512 0-0.512 0.46-0 Segment L 0.387 1.759 0.512 0.46

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63 Appendix A (Continued) Table A.5 Continued District 6 Segment SR 924 (8) 1 2 3 4 5 6 7 8 9 10 Mile Point 0-2.004 2.004-3.837 3.837-4.527 4.527-5.378 Segment L 2.004 1.833 0.69 0.851 Lanes 6 6 6 8 AADT 63500 37500 42000 42000 District 6 Segment SR 826 1 2 3 4 5 6 7 8 9 10 Mile Point 0-0.861 0.861-0.946 0.946-1.324 1.324-1.864 1.864-2.876 2.8763.623 3.623-3.926 3.926-5.015 5.015-6.041 6.041-6.521 Segment L 0.861 0.085 0.378 0.54 1.012 0.747 0.303 1.089 1.026 0.48 Lanes 4 4 9 6 4 4 8 8 8 8 AADT 44500 63500 63500 63500 98500 109500 109500 191000 194500 198500 SR 826 1 2 3 4 5 6 7 8 9 10 Mile Point 6.521-7.04 7.04-7.234 7.234-8.363 8.363-9.208 9.20810.381 10.38111.372 11.37212.227 12.22713.161 13.16114.362 14.36214.972 Segment L 0.519 0.194 1.129 0.845 1.173 0.991 0.855 0.934 1.201 0.61 Lanes 8 7 8 8 8 8 8 8 8 8 AADT 191000 205000 205000 218000 204000 160000 191000 203000 181000 169500 SR 826 1 2 3 4 5 6 7 8 9 10 Mile Point 14.97215.484 15.48416.378 16.37818.985 18.98520.013 20.01321.014 21.01422.015 22.01523.024 23.02423.449 23.44923.814 23.81424.19 Segment L 0.512 0.894 2.607 1.028 1.001 1.001 1.009 0.425 0.365 0.376 Lanes 6 6 6 6 6 6 8 8 8 4 AADT 169500 119000 118000 134000 144500 144500 162000 141500 160500 160500 District 6 Segment SR 112 1 2 3 4 5 6 7 8 9 10 Mile Point 0-0.964 0.964-0.994 0.994-1.156 1.156-1.668 1.668-2.192 2.192-2.7 2.7-3.644 3.664-4.132 Segment L 0.964 0.03 0.162 0.512 0.524 0.508 0.944 0.468 Lanes 4 4 6 6 6 6 6 8 AADT 26000 97000 97000 100500 90000 102500 109000 109000

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64 Appendix A (Continued) Table A.6 Freeway and Traffic Characteristics in Turnpike District 7 Segment I-275 1 2 3 4 5 6 7 8 9 10 Mile Point 0.5-1.19 0.5-2.30 2.30-2.55 2.553.23 3.23-3.55 3.55-4.51 4.51-5.29 5.29-6.29 6.29-7.32 7.32-8.339 Segment L 0.69 1.8 0.25 0.68 0.32 0.96 0.78 1 1.03 1.019 Lanes 6 6 6 4 4 6 8 6 8 6 AADT 4600 78500 74000 93000 80500 89000 97500 114500 144000 168000 I-275 1 2 3 4 5 6 7 8 9 10 Mile Point 8.339-10.53 10.53-12.46 12.46-13.75 13.7514.54 14.54-19.65 0-1.31 1.31-2.15 2.15-2.62 2.62-3.25 3.25-3.84 Segment L 2.19 1.93 1.29 0.79 5.11 1.31 0.84 0.47 0.63 0.59 Lanes 8 4 4 6 8 6 6 6 6 6 AADT 134000 90000 81500 117500 129000 129000 131000 131000 171500 170500 I-275 1 2 3 4 5 6 7 8 9 10 Mile Point 3.84-4.62 4.62-5.12 5.12-6.44 6.446.86 6.86-7.25 0-.15 0.45-0.71 0.71-1.44 1.44-2.45 2.45-3.46 Segment L 0.78 0.3 1.32 0.42 0.39 0.15 0.26 0.73 1.01 0.84 Lanes 6 6 6 6 8 8 6 6 6 6 AADT 176500 187500 157500 163500 228000 133417 133417 150000 159500 153500 I-275 1 2 3 4 5 6 7 8 9 10 Mile Point 3.45-4.29 4.29-5.01 5.01-6.51 6.51-7.51 7.51-8.80 Segment L 1.01 0.72 1.5 1 1.29 Lanes 6 6 6 6 6 AADT 152000 120500 124500 93500 69500

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65 Appendix A (Continued) Table A.7 Freeway and Traffic Characteristics in Turnpike Turnpike Segment Zone 1 1 2 3 4 5 6 7 8 9 10 Mile Point 0-1 1-2 2-5 56 6-9 9-10 10-11 11-12 12-13 13-16 Segment L 1 1 3 1 3 1 1 1 1 3 Lanes 6 6 6 6 6 6 6 6 6 6 AADT 40400 40400 40400 47500 53500 54800 54800 54800 93200 119200 Zone 1 1 2 3 4 5 6 7 8 9 10 Mile Point 16-18 18-19 Segment L 2 1 Lanes 6 6 AADT 149400 79900 Zone 2 1 2 3 4 5 6 7 8 9 10 Mile Point 19-20 20-22 22-25 25-26A 26A-26B 26B-29 29-30 30-34 34-35 Segment L 1 2 3 1 0.5 3 1 4 1 Lanes 6 6 6 6 6 6 6 6 6 AADT 86000 105700 105700 163600 90000 90500 91300 91300 82600 Zone 3 1 2 3 4 5 6 7 8 9 10 Mile Point 29-30 30-34 34-35 35-39 39-43 43-47 47-49 Segment L 1 4 1 4 4 4 2 Lanes 6 6 6 6 6 6 6 AADT 91300 91300 82600 77900 40500 52500 70000 Zone 4 1 2 3 4 5 6 7 8 9 10 Mile Point OX-3X 3X-47 47-49 49-53 53-54 54-58 Segment L 0.5 0.5 2 4 1 4 Lanes 6 6 6 6 6 6 AADT 62100 72400 97600 105400 105200 107100 Zone 5 1 2 3 4 5 6 7 8 9 10 Mile Point 53-54 54-58 58-62 62-63 63-66 66-67 67-69 Segment L 1 4 4 1 3 1 2 Lanes 6 6 6 6 6 6 6 AADT 105200 107100 104100 95100 95100 83600 86900 Zone 6 1 2 3 4 5 6 7 8 9 10 Mile Point 0-1 1-2 2-3 36 6-8 8-10 10-12 12-15 15-16 16-23 Segment L 1 1 1 3 2 2 2 3 1 7 Lanes 6 6 6 6 6 6 6 6 6 6 AADT 82300 63800 69000 62600 52600 42400 49100 61500 58900 59100 Zone 7 1 2 3 4 5 6 7 8 9 10 Mile Point 69-71 71-75 7581 81-86 86-88 88-93 Segment L 2 4 6 5 2 5 Lanes 6 6 6 4 4 4 AADT 78000 92700 86300 80200 66500 66500 Zone 8 1 2 3 4 5 6 7 8 9 10 Mile Point 93-97 97-98 9899 99-106 106-109 109-116 Segment L 4 1 1 7 3 7 Lanes 4 4 4 4 4 4 AADT 62400 59800 59800 53900 53900 39300 Zone 9 1 2 3 4 5 6 7 8 9 10 Mile Point 116-133 133-138 138-142 142-144 144-152 Segment L 4 1 1 7 3 7 Lanes 4 4 4 4 4 4 AADT 30500 34600 34600 34600 28100

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66 Appendix A (Continued) Table A.7 Continued Zone 10 1 2 3 4 5 6 7 8 9 10 Mile Point 152-193 Segment L 41 Lanes 4 AADT 25300 Zone 11 1 2 3 4 5 6 7 8 9 10 Mile Point 193-229 Segment L 36 Lanes 4 AADT 24300 Zone 12 1 2 3 4 5 6 7 8 9 10 Mile Point 229-236 236-242 242-244 244-249 249-254 Segment L 7 6 2 5 5 Lanes 4 4 4 4 4 AADT 24300 24300 22900 38600 48500 Zone 13 1 2 3 4 5 6 7 8 9 10 Mile Point 254-265 265-267A 267A-267B 267-272 Segment L 11 2 0.5 5 Lanes 4 4 4 4 AADT 58000 86200 67100 63000 Zone 14 1 2 3 4 5 6 7 8 9 10 Mile Point 272-285 285-288 288-296 296-304 304-309 Segment L 13 3 8 8 5 Lanes AADT 37100 37100 28300 34400 32800

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67 Appendix B: Benefit/Cost Ratio In Each District Table B.1 Road Ranger Benefits in District 2 (Jan-Sep) District 2 (Jan-Sep) Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio I-10 26240 595910 39574 77565 673475 210980 3.19 I-295 6877 156177 10372 20328 176505 210980 0.84 I-95 23650 537092 35668 69909 607000 210980 2.88 Turner Butler Road 1001 22733 1510 2959 25692 210980 0.12 Total 57768 1311911 87123 170761 1482672 843920 1.76 Table B.2 Monthly Road Ranger Benefits in District 2 on I-10 (Jan-Sep) I-10 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio January 1046 23755 1578 3092 26847 23870 1.12 February 1077 24459 1624 3184 27642 22330 1.24 March 4079 92634 6152 12057 104692 23870 4.39 April 4096 93020 6177 12108 105128 23100 4.55 May 3753 85231 5660 11094 96324 23870 4.04 June 2289 51983 3452 6766 58749 23100 2.54 July 3814 86616 5752 11274 97890 23870 4.10 August 4717 107123 7114 13943 121066 23870 5.07 September 1369 31090 2065 4047 35137 23100 1.52 Total 26240 595910 39574 77565 673475 210980 3.19 Table B.3 Monthly Road Ranger Benefits in District 2 on I-295 (Jan-Sep) I-295 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio January 538 12218 811 1590 13808 23870 0.58 February 328 7449 495 970 8418 22330 0.38 March 600 13626 905 1774 15400 23870 0.65 April 1078 24481 1626 3187 27668 23100 1.20 May 1038 23573 1565 3068 26641 23870 1.12 June 1084 24618 1635 3204 27822 23100 1.20 July 750 17033 1131 2217 19249 23870 0.81 August 1046 23755 1578 3092 26847 23870 1.12 September 415 9425 626 1227 10651 23100 0.46 Total 6877 156177 10372 20328 176505 210980 0.84

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68 Appendix B (Continued) Table B.4 Monthly Road Ranger Benefits in District 2 on I-95 (Jan-Sep) I-95 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio January 1598 36291 2410 4724 41014 23870 1.72 February 2083 47305 3141 6157 53462 22330 2.39 March 2021 45897 3048 5974 51871 23870 2.17 April 2955 67108 4457 8735 75843 23100 3.28 May 1437 32634 2167 4248 36882 23870 1.55 June 2909 66063 4387 8599 74662 23100 3.23 July 3088 70128 4657 9128 79257 23870 3.32 August 3685 83686 5558 10893 94579 23870 3.96 September 3874 87979 5843 11451 99430 23100 4.30 Total 23650 537092 35668 69909 607000 210980 2.88 Table B.5 Monthly Road Ranger Benefits in District 2 on Turner Butler Road (JanSep) TB Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio January 114 2589 172 337 2926 23870 0.12 February 181 4111 273 535 4646 22330 0.21 March 186 4224 281 550 4774 23870 0.20 April 78 1771 118 231 2002 23100 0.09 May 64 1453 97 189 1643 23870 0.07 June 87 1976 131 257 2233 23100 0.10 July 91 2067 137 269 2336 23870 0.10 August 117 2657 176 346 3003 23870 0.13 September 83 1885 125 245 2130 23100 0.09 Total 1001 22733 1510 2959 25692 210980 0.12 Table B.6 Road Ranger Benefits in Districts 4, 5 and District 7 District 4 (July) Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio I-75 16522 375215 24922 48847 424062 90036 4.71 I-595 18260 414685 27544 53986 468671 90036 5.21 I-95 239809 5446062 361734 708999 6155061 150060 41.02 Total 274591 6235962 414200 811832 7047794 330132 21.35 District 7 (August) Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio I-275 80051 1817958 120751 236672 2054630 117400 17.50 District 5 (Jan-Aug) Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio I-275 239579 5440839 361387 708319 6149158 483000 12.73

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69 Appendix B (Continued) Table B.7 Average Monthly Road Ranger Benefits in District 6 District 6 Study Period Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio I-75 12 Months 115 2610 173 340 2950 25550 0.12 I-95 11 Months 224574 5100073 338754 663958 5764032 77390 74.48 I-395 9 Months 8970 203704 13530 26519 230223 17155 13.42 I-195 10 Months 2503 56845 3776 7400 64246 17155 3.75 SR 836 12 Months 296902 6742648 447856 877799 7620447 52025 146.48 SR 112 12 Months 6751 153319 10184 19960 173279 35950 4.82 SR 878 12 Months 20216 459096 30494 59768 518864 23325 22.24 SR 826 12 Months 87594 1989267 132130 258975 2248242 127750 17.60 SR 874 12 Months 57378 1303045 86550 169638 1472683 35960 40.95 Total 705003 16010608 1063448 2084357 18094965 435584 41.54 Table B.8 Monthly Road Ranger Benefits on I-75 in District 6 I-75 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio January 103 2339 155 305 2644 25550 0.10 February 53 1204 80 157 1360 25550 0.05 March 80 1817 121 237 2053 25550 0.08 April 62 1408 94 183 1591 25550 0.06 May 94 2135 142 278 2413 25550 0.09 June 117 2657 176 346 3003 25550 0.12 July 165 3747 249 488 4235 25550 0.17 August 170 3861 256 503 4363 25550 0.17 September 106 2407 160 313 2721 25550 0.11 October 132 2998 199 390 3388 25550 0.13 November 133 3020 201 393 3414 25550 0.13 December 164 3724 247 485 4209 25550 0.16 Total 1379 31317 2080 4077 35394 306600 0.12

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70 Appendix B (Continued) Table B.9 Monthly Road Ranger Benefits on I-95 in District 6 I-95 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio January 155323 3527385 234294 459216 3986602 77390 51.51 February 202537 4599615 305513 598806 5198421 77390 67.17 March 232701 5284640 351013 687986 5972626 77390 77.18 April 236154 5363057 356222 698195 6061252 77390 78.32 May 114373 2597411 172524 338147 2935557 77390 37.93 June n/a n/a n/a n/a n/a n/a n/a July 225630 5124057 340347 667081 5791138 77390 74.83 August 235924 5357834 355875 697515 6055349 77390 78.24 September 233396 5300423 352062 690041 5990464 77390 77.41 October 261009 5927514 393714 771680 6699194 77390 86.56 November 273058 6201147 411889 807303 7008450 77390 90.56 December 300208 6817724 452843 887572 7705296 77390 99.56 Total 2470313 56100808 3726297 7303542 63404350 851290 74.48 Table B.10 Monthly Road Ranger Benefits on I-395 in District 6 I-395 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio January 7952 180590 11995 23510 204100 17155 11.90 February 7129 161900 10754 21077 182977 17155 10.67 March 9337 212043 14084 27605 239648 17155 13.97 April 12265 278538 18501 36262 314800 17155 18.35 May 4120 93565 6215 12181 105746 17155 6.16 June n/a n/a n/a n/a n/a n/a n/a July n/a n/a n/a n/a n/a n/a n/a August n/a n/a n/a n/a n/a n/a n/a September 11132 252808 16792 32912 285720 17155 16.66 October 10821 245745 16323 31993 277737 17155 16.19 November 10148 230461 15308 30003 260464 17155 15.18 December 7824 177683 11802 23132 200815 17155 11.71 Total 80728 1833333 121773 238674 2072007 154395 13.42

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71 Appendix B (Continued) Table B.11 Monthly Road Ranger Benefits on I-195 in District 6 I-195 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio January 2143 48668 3233 6336 55003 17155 3.21 February 2300 52233 3469 6800 59033 17155 3.44 March 3597 81688 5426 10635 92322 17155 5.38 April 3001 68153 4527 8873 77025 17155 4.49 May 1353 30727 2041 4000 34727 17155 2.02 June n/a n/a n/a n/a n/a n/a n/a July n/a n/a n/a n/a n/a n/a n/a August 1957 44443 2952 5786 50229 17155 2.93 September 3158 71718 4764 9337 81055 17155 4.72 October 2609 59250 3935 7714 66964 17155 3.90 November 2190 49735 3303 6475 56210 17155 3.28 December 2723 61839 4107 8051 69890 17155 4.07 Total 25031 568454 37758 74005 642459 171550 3.75 Table B.12 Monthly Road Ranger Bene fits on SR-836 in District 6 SR-836 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio January 263849 5992011 397998 780076 6772087 52025 130.17 February 260820 5923222 393429 771121 6694343 52025 128.68 March 336891 7650795 508177 996027 8646821 52025 166.21 April 278841 6332479 420612 824400 7156879 52025 137.57 May 263571 5985697 397579 779254 6764952 52025 130.03 June 302450 6868640 456225 894201 7762840 52025 149.21 July 301646 6850381 455012 891824 7742205 52025 148.82 August 323257 7341166 487611 955717 8296884 52025 159.48 September 217916 4948872 328711 644274 5593146 52025 107.51 October 344479 7823118 519623 1018461 8841579 52025 169.95 November 340027 7722013 512907 1005298 8727311 52025 167.75 December 329079 7473384 496393 972930 8446314 52025 162.35 Total 3562826 80911778 5374277 10533583 91445362 624300 146.48

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72 Appendix B (Continued) Table B.13 Monthly Road Ranger Bene fits on SR-112 in District 6 SR-112 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio January 8318 188902 12547 24592 213494 35950 5.94 February 6954 157925 10490 20560 178485 35950 4.96 March 7389 167804 11146 21846 189650 35950 5.28 April 6396 145253 9648 18910 164163 35950 4.57 May 5853 132922 8829 17305 150226 35950 4.18 June 5636 127994 8502 16663 144657 35950 4.02 July 7483 169939 11288 22124 192063 35950 5.34 August 8973 203777 13535 26529 230306 35950 6.41 September 6153 139735 9281 18191 157926 35950 4.39 October 4894 111143 7382 14469 125612 35950 3.49 November 6742 153111 10170 19933 173044 35950 4.81 December 6223 141324 9387 18398 159723 35950 4.44 Total 81014 1839828 122204 239520 2079348 431400 4.82 Table B.14 Monthly Road Ranger Bene fits on SR-826 in District 6 SR-826 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio January 69521 1578822 104868 205541 1784362 127750 13.97 February 73669 1673023 111125 217804 1890827 127750 14.80 March 85612 1944249 129140 253114 2197363 127750 17.20 April 80380 1825430 121248 237645 2063075 127750 16.15 May 92105 2091705 138934 272311 2364015 127750 18.51 June 126578 2874586 190934 374231 3248817 127750 25.43 July 89503 2032613 135009 264618 2297231 127750 17.98 August 72416 1644567 109235 214100 1858667 127750 14.55 September 79318 1801312 119646 234506 2035817 127750 15.94 October 95081 2159290 143423 281109 2440399 127750 19.10 November 82469 1872871 124399 243822 2116693 127750 16.57 December 104480 2372741 157601 308898 2681639 127750 20.99 Total 1051132 23871208 1585560 3107698 26978906 1533000 17.60

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73 Appendix B (Continued) Table B.15 Monthly Road Ranger Bene fits on SR-874 in District 6 SR-874 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio January 53104 1205992 80104 157003 1362995 35960 37.90 February 66266 1504901 99958 195917 1700818 35960 47.30 March 62842 1427142 94793 185794 1612936 35960 44.85 April 55414 1258452 83588 163833 1422285 35960 39.55 May 57892 1314727 87326 171159 1485886 35960 41.32 June 58465 1327740 88190 172853 1500593 35960 41.73 July 53704 1219618 81009 158777 1378395 35960 38.33 August 56180 1275848 84744 166098 1441945 35960 40.10 September 48058 1091397 72492 142085 1233482 35960 34.30 October 65124 1478966 98235 192541 1671507 35960 46.48 November 53358 1211760 80487 157754 1369514 35960 38.08 December 58124 1319996 87676 171845 1491841 35960 41.49 Total 688531 15636539 1038602 2035659 17672198 431520 40.95 Table B.16 Monthly Road Ranger Bene fits on SR-878 in District 6 SR-878 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio January 5295 120249 7987 15655 135904 23325 5.83 February 32119 729422 48449 94961 824383 23325 35.34 March 9532 216472 14378 28182 244653 23325 10.49 April 31252 709733 47141 92397 802130 23325 34.39 May 26492 601633 39961 78324 679958 23325 29.15 June 8667 196828 13074 25624 222452 23325 9.54 July 27150 616577 40954 80270 696846 23325 29.88 August 30005 681414 45260 88711 770124 23325 33.02 September 5403 122702 8150 15974 138676 23325 5.95 October 27181 617281 41001 80361 697642 23325 29.91 November 12250 278198 18478 36217 314415 23325 13.48 December 27241 618643 41091 80539 699182 23325 29.98 Total 242587 5509151 365926 717214 6226365 279900 22.24

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74 Appendix B (Continued) Table B.17 Overall Annual Benefit of Road Ranger Program in Turnpike Region Table B.18 Monthly Road Ranger Benefits in Zone 1 Zone 1 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio January 6988 158697 10542 20662 179360 7812 22.96 February 6053 137464 9130 17895 155358 7308 21.26 March 6527 148228 9845 19296 167524 7812 21.44 April 7192 163330 10849 21264 184594 7560 24.42 May 8684 197214 13099 25674 222888 7812 28.53 June 7892 179227 11905 23334 202561 7560 26.79 July 7709 175071 11629 22793 197864 7812 25.33 August 7409 168258 11176 21905 190163 7812 24.34 September 6752 153338 10185 19963 173301 7560 22.92 October 7800 177138 11765 23059 200197 7812 25.63 November 8486 192717 12801 25090 217807 7560 28.81 December 7478 169825 11280 22109 191934 7812 24.57 Total 88970 2020509 134206 263044 2283552 92232 24.76 Annual Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio Northern Zone 159592 3624334 240690 471752 4096087 645624 6.34 Southern Zone 343062 7790938 517060 1013437 8804375 645624 13.64 Overall Turnpike 502654 11415272 757750 1485190 12900462 1291248 9.99

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75 Appendix B (Continued) Table B.19 Monthly Road Ranger Benefits in Zone 2 Zone 2 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio January 7422 168554 11195 21942 190496 7812 24.39 February 6418 145753 9681 18975 164728 7308 22.54 March 6924 157244 10444 20470 177714 7812 22.75 April 7926 179999 11504 22548 202547 7560 26.79 May 9207 209091 13888 27220 236311 7812 30.25 June 8364 189946 12617 24729 214676 7560 28.40 July 8185 185881 12346 24198 210080 7812 26.89 August 7846 178183 11835 23197 201379 7812 25.78 September 7160 162604 10801 21170 183774 7560 24.31 October 8272 187857 12478 24457 212314 7812 27.18 November 9007 204549 13587 26631 231179 7560 30.58 December 7938 180272 11975 23471 203743 7812 26.08 Total 94669 2149933 142351 279008 2428941 92232 26.34 Table B.20 Monthly Road Ranger Benefits in Zone 3 Zone 3 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio January 558 12672 841 1648 14321 7812 1.83 February 594 13490 896 1756 15246 7308 2.09 March 640 14534 966 1893 16428 7812 2.10 April 706 16033 1065 2087 18121 7560 2.40 May 853 19372 1287 2523 21894 7812 2.80 June 775 17600 1170 2293 19893 7560 2.63 July 758 17214 1143 2240 19454 7812 2.49 August 727 16510 1096 2148 18658 7812 2.39 September 662 15034 999 1958 16992 7560 2.25 October 766 17396 1156 2266 19662 7812 2.52 November 833 18917 1257 2464 21381 7560 2.83 December 735 16692 1108 2172 18864 7812 2.41 Total 8607 195465 12984 25449 220914 92232 2.40

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76 Appendix B (Continued) Table B.21 Monthly Road Ranger Benefits in Zone 4 Zone 4 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio January 3880 88115 5853 11472 99587 7812 12.75 February 3356 76215 5063 9923 86138 7308 11.79 March 3612 82029 5449 10680 92709 7812 11.87 April 3982 90431 6007 11774 102205 7560 13.52 May 4803 109076 7246 14202 123278 7812 15.78 June 4361 99038 6579 12895 111933 7560 14.81 July 4271 96994 6443 12629 109623 7812 14.03 August 4099 93088 6184 12120 105208 7812 13.47 September 3746 85072 5651 11076 96148 7560 12.72 October 4320 98107 6517 12774 110881 7812 14.19 November 4705 106851 7098 13912 120762 7560 15.97 December 4151 94269 6262 12274 106543 7812 13.64 Total 49286 1119285 74352 145730 1265015 92232 13.72 Table B.22 Monthly Road Ranger Benefits in Zone 5 Zone 5 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio January 3011 68380 4542 8903 77283 7812 9.89 February 2606 59182 3931 7705 66888 7308 9.15 March 2998 68085 4523 8865 76949 7812 9.85 April 3102 70446 4680 9172 79619 7560 10.53 May 3734 84799 5633 11041 95840 7812 12.27 June 3391 77010 5116 10027 87036 7560 11.51 July 3323 75465 5013 9826 85291 7812 10.92 August 3189 72422 4811 9429 81852 7812 10.48 September 2907 66018 4385 8596 74613 7560 9.87 October 3357 76237 5064 9926 86164 7812 11.03 November 3657 83050 5517 10813 93864 7560 12.42 December 3227 73285 4868 9542 82827 7812 10.60 Total 38502 874380 58084 113844 988224 92232 10.71

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77 Appendix B (Continued) Table B.23 Monthly Road Ranger Benefits in Zone 6 Table B.24 Monthly Road Ranger Benefits in Zone 7 Zone 6 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio January 14 318 21 41 359 7812 0.05 February 14 318 21 41 359 7308 0.05 March 15 341 23 44 385 7812 0.05 April 17 386 26 50 436 7560 0.06 May 21 477 32 62 539 7812 0.07 June 19 431 29 56 488 7560 0.06 July 18 409 27 53 462 7812 0.06 August 18 409 27 53 462 7812 0.06 September 16 363 24 47 411 7560 0.05 October 19 431 29 56 488 7812 0.06 November 20 454 30 59 513 7560 0.07 December 18 409 27 53 462 7812 0.06 Total 209 4746 315 618 5364 92232 0.06 Zone 7 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio January 4942 112233 7455 14613 126845 7812 16.24 February 4272 97017 6445 12632 109649 7308 15.00 March 4605 104580 6947 13616 118196 7812 15.13 April 5084 115458 7670 15033 130490 7560 17.26 May 6124 139076 9239 18108 157184 7812 20.12 June 5560 126268 8388 16440 142708 7560 18.88 July 5443 123611 8211 16094 139705 7812 17.88 August 5224 118637 7881 15446 134084 7812 17.16 September 4777 108486 7207 14125 122610 7560 16.22 October 5506 125041 8306 16280 141322 7812 18.09 November 5999 136237 9050 17738 153975 7560 20.37 December 5283 119977 7970 15621 135598 7812 17.36 Total 62819 1426619 94768 185745 1612365 92232 17.48

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78 Appendix B (Continued) Table B.25 Monthly Road Ranger Benefits in Zone 8 Zone 8 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio January 1207 27411 1820 3567 30978 7812 3.97 February 1083 24595 1634 3203 27798 7308 3.80 March 1156 26253 1744 3418 29671 7812 3.80 April 1384 31431 2087 4091 35521 7560 4.70 May 1468 33338 2214 4339 37678 7812 4.82 June 1498 34020 2259 4428 38447 7560 5.09 July 1472 33429 2220 4351 37780 7812 4.84 August 1408 31976 2123 4161 36137 7812 4.63 September 1154 26207 1740 3410 29618 7560 3.92 October 1141 25912 1721 3373 29285 7812 3.75 November 1049 23823 1583 3103 26925 7560 3.56 December 960 21802 1448 2838 24640 7812 3.15 Total 14980 340196 22593 44282 384478 92232 4.17 Table B.26 Monthly Road Ranger Benefits in Zone 12 Zone 12 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio January 6807 154587 10266 20121 174708 7812 22.36 February 6108 138713 9212 18055 156768 7308 21.45 March 6505 147729 9811 19229 166957 7812 21.37 April 7837 177978 11819 23166 201144 7560 26.61 May 8269 187789 12471 24443 212232 7812 27.17 June 8010 181907 12080 23677 205584 7560 27.19 July 8301 188516 12519 24538 213053 7812 27.27 August 7945 180431 11982 23485 203916 7812 26.10 September 6505 147729 9811 19229 166957 7560 22.08 October 6435 146139 9705 19022 165161 7812 21.14 November 5905 134103 8906 17455 151558 7560 20.05 December 5388 122361 8126 15927 138288 7812 17.70 Total 84015 1907981 126707 248347 2156327 92232 23.38

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79 Appendix B (Continued) Table B.27 Monthly Road Ranger Benefits in Zone 13 Zone 13 Veh-hrs Delay Savings ($) Fuel (gallons) Fuel Savings ($) Total ($) Cost ($) B-C Ratio January 4912 111552 7408 14520 126071 7812 16.14 February 4409 100128 6649 13033 113161 7308 15.48 March 4705 106851 7096 13908 120758 7812 15.46 April 5633 127925 8495 16651 144576 7560 19.12 May 5975 135692 9011 17662 153354 7812 19.63 June 5760 130810 8687 17026 147836 7560 19.56 July 5991 136056 9035 17709 153765 7812 19.68 August 5728 130083 8639 16932 147015 7812 18.82 September 4697 106669 7084 13884 120553 7560 15.95 October 4646 105511 7007 13733 119244 7812 15.26 November 4233 96131 6384 12513 108644 7560 14.37 December 3908 88751 5894 11552 100303 7812 12.84 Total 60597 1376158 91390 179124 1555282 92232 16.86

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80 Appendix C: Savings In Vehicl e Emissions In Each District The FSPE model used to estimate Road Range r service in present study estimates the savings in vehicular emissions for three ty pes of gases, Carbon Monoxide (CO), Nitrogen Oxides (NOX) and Reactive Organic Gases (R OG). Since, it is difficult to assign dollar value to the emissions/pollution; the savings in emissions was not included in the final Benefit-Cost ratio. The following tables in this section describe the estimated savings in vehicular emissions for various Dist ricts and Turnpike in Florida. Table C.1 Savings in Vehicular Emissi ons in District 2 on I-10 (Jan-Sep) I-10 ROG (kg) CO(kg) NOX(kg) January 157 7 33 February 161 7 34 March 611 27 127 April 614 27 128 May 563 24 117 June 343 15 71 July 572 25 119 August 707 31 147 September 205 9 43 Total 3933 171 817 Table C.2 Savings in Vehicular Emissi ons in District 2 on I-295 (Jan-Sep) I-295 ROG (kg) CO(kg) NOX(kg) January 81 4 17 February 49 2 10 March 90 4 19 April 162 7 34 May 156 7 32 June 162 7 34 July 112 5 23 August 157 7 33 September 62 3 13 Total 1031 45 214

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81 Appendix C (Continued) Table C.3 Savings in Vehicular Emissi ons in District 2 on I-95 (Jan-Sep) I-95 ROG (kg) CO(kg) NOX(kg) January 240 10 50 February 312 14 65 March 303 13 63 April 443 19 92 May 215 9 45 June 436 19 91 July 463 20 96 August 552 24 115 September 581 25 121 Total 3545 154 736 Table C.4 Savings in Vehicula r Emissions in District 2 on Turner Butler Road (Jan-Sep) TB ROG (kg) CO(kg) NOX(kg) January 17 1 4 February 27 1 6 March 28 1 6 April 12 1 2 May 10 0 2 June 13 1 3 July 14 1 3 August 18 1 4 September 12 1 3 Total 150 7 31 Table C.5 Savings in Vehicular Em issions in Districts 4, 5 and 7 District 4 (July) ROG (kg) CO(kg) NOX(kg) I-75 2471 104 484 I-595 2731 115 535 I-95 35869 1504 7030 Total 41071 1723 8049 District 7 (August) ROG (kg) CO(kg) NOX(kg) I-275 11973 502 2347 District 5 (Jan-Aug) ROG (kg) CO(kg) NOX(kg) I-275 35834 1502 7023

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82 Appendix C (Continued) Table C.6 Savings in Vehicular Emissions on I-75 in District 6 I-75 ROG (kg) CO(kg) NOX(kg) January 15 1 3 February 8 0 2 March 12 1 2 April 9 0 2 May 14 1 3 June 17 1 3 July 25 1 5 August 25 1 5 September 16 1 3 October 20 1 4 November 20 1 4 December 25 1 5 Total 206 9 40 Table C.7 Savings in Vehicular Emissions on I-95 in District 6 I-95 ROG (kg) CO(kg) NOX(kg) January 23232 974 4553 February 30294 1270 5937 March 34806 1459 6821 April 35322 1481 6922 May 17107 717 3353 June n/a n/a n/a July 33748 1415 6614 August 35288 1479 6916 September 34910 1464 6842 October 39040 1637 7651 November 40842 1712 8004 December 44903 1883 8800 Total 369490 15491 72412

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83 Appendix C (Continued) Table C.8 Savings in Vehicular Em issions on I-395 in District 6 I-395 Veh-hrs ROG (kg) CO(kg) NOX(kg) January 7952 1189 50 233 February 7129 1066 45 209 March 9337 1397 59 274 April 12265 1835 77 360 May 4120 616 26 121 June n/a n/a n/a n/a July n/a n/a n/a n/a August n/a n/a n/a n/a September 11132 1665 70 326 October 10821 1619 68 317 November 10148 1518 64 297 December 7824 1170 49 229 Total 80728 12075 506 2366 Table C.9 Savings in Vehicular Em issions on I-195 in District 6 I-195 ROG (kg) CO(kg) NOX(kg) January 321 13 63 February 344 14 67 March 538 23 105 April 449 19 88 May 202 8 40 June n/a n/a n/a July n/a n/a n/a August 293 12 57 September 472 20 93 October 390 16 76 November 328 14 64 December 407 17 80 Total 3744 157 734

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84 Appendix C (Continued) Table C.10 Savings in Vehicular Em issions on SR-836 in District 6 SR-836 ROG (kg) CO(kg) NOX(kg) January 39464 1655 7734 February 39011 1636 7645 March 50389 2113 9875 April 41707 1749 8174 May 39423 1653 7726 June 45238 1897 8866 July 45118 1892 8842 August 48350 2027 9476 September 32594 1367 6388 October 51524 2160 10098 November 50859 2132 9967 December 49221 2064 9646 Total 532899 22342 104437 Table C.11 Savings in Vehicular Em issions on SR-112 in District 6 SR-112 ROG (kg) CO(kg) NOX(kg) January 1244 52 244 February 1040 44 204 March 1105 46 217 April 957 40 187 May 875 37 172 June 843 35 165 July 1119 47 219 August 1342 56 263 September 920 39 180 October 732 31 143 November 1008 42 198 December 931 39 182 Total 12117 508 2375

PAGE 95

85 Appendix C (Continued) Table C.12 Savings in Vehicular Em issions on SR-826 in District 6 SR-826 ROG (kg) CO(kg) NOX(kg) January 10398 436 2038 February 11019 462 2159 March 12805 537 2510 April 12023 504 2356 May 13776 578 2700 June 18933 794 3710 July 13387 561 2624 August 10831 454 2123 September 11864 497 2325 October 14221 596 2787 November 12335 517 2417 December 15627 655 3063 Total 157220 6592 30812 Table C.13 Savings in Vehicular Em issions on SR-874 in District 6 SR-874 ROG (kg) CO(kg) NOX(kg) January 7943 333 1557 February 9912 416 1942 March 9399 394 1842 April 8288 348 1624 May 8659 363 1697 June 8745 367 1714 July 8033 337 1574 August 8403 352 1647 September 7188 301 1409 October 9741 408 1909 November 7981 335 1564 December 8694 364 1704 Total 102985 4318 20183

PAGE 96

86 Appendix C (Continued) Table C.14 Savings in Vehicular Em issions on SR-878 in District 6 SR-878 ROG (kg) CO(kg) NOX(kg) January 792 33 155 February 4804 201 942 March 1426 60 279 April 4674 196 916 May 3962 166 777 June 1296 54 254 July 4061 170 796 August 4488 188 880 September 808 34 158 October 4066 170 797 November 1832 77 359 December 4074 171 799 Total 36284 1521 7111 Table C.15 Savings in Vehicular Emission s in Zone 1 in Florida’s Turnpike Zone 1 ROG (kg) CO(kg) NOX(kg) January 1045 44 205 February 905 38 177 March 976 41 191 April 1076 45 211 May 1299 54 255 June 1180 49 231 July 1153 48 226 August 1108 46 217 September 1010 42 198 October 1167 49 229 November 1269 53 249 December 1118 47 219 Total 13306 556 2608

PAGE 97

87 Appendix C (Continued) Table C.16 Savings in Vehicular Emission s in Zone 2 in Florida’s Turnpike Zone 2 ROG (kg) CO(kg) NOX(kg) January 1110 47 218 February 960 40 188 March 1036 43 203 April 1141 48 224 May 1377 58 270 June 1251 52 245 July 1224 51 240 August 1174 49 230 September 1071 45 210 October 1237 52 242 November 1347 56 264 December 1187 50 233 Total 14115 591 2767 Table C.17 Savings in Vehicular Emission s in Zone 3 in Florida’s Turnpike Zone 3 ROG (kg) CO(kg) NOX(kg) January 83 3 16 February 89 4 17 March 96 4 19 April 106 4 21 May 128 5 25 June 116 5 23 July 113 5 22 August 109 5 21 September 99 4 19 October 115 5 22 November 125 5 24 December 110 5 22 Total 1289 54 251

PAGE 98

88 Appendix C (Continued) Table C.18 Savings in Vehicular Emission s in Zone 4 in Florida’s Turnpike Zone 4 ROG (kg) CO(kg) NOX(kg) January 580 24 114 February 502 21 98 March 540 23 106 April 595 25 117 May 718 30 141 June 652 27 128 July 639 27 125 August 613 26 120 September 560 24 110 October 646 27 126 November 704 30 138 December 621 26 122 Total 7370 309 1443 Table C.19 Savings in Vehicular Emission s in Zone 5 in Florida’s Turnpike Zone 5 ROG (kg) CO(kg) NOX(kg) January 450 19 88 February 390 16 76 March 448 19 88 April 464 19 91 May 558 23 109 June 507 21 99 July 497 21 97 August 477 20 93 September 435 18 85 October 502 21 98 November 547 23 107 December 483 20 94 Total 5758 242 1127

PAGE 99

89 Appendix C (Continued) Table C.20 Savings in Vehicular Emission s in Zone 6 in Florida’s Turnpike Zone 6 ROG (kg) CO(kg) NOX(kg) January 2 0 0 February 2 0 0 March 2 0 0 April 3 0 0 May 3 0 1 June 3 0 1 July 3 0 1 August 3 0 1 September 2 0 0 October 3 0 1 November 3 0 1 December 3 0 1 Total 31 1 6 Table C.21 Savings in Vehicular Emission s in Zone 7 in Florida’s Turnpike Zone 7 ROG (kg) CO(kg) NOX(kg) January 739 31 145 February 639 27 125 March 689 29 135 April 760 32 149 May 916 38 179 June 831 35 163 July 814 34 159 August 781 33 153 September 714 30 140 October 823 35 161 November 897 38 176 December 790 33 155 Total 9394 394 1839

PAGE 100

90 Appendix C (Continued) Table C.22 Savings in Vehicular Emission s in Zone 8 in Florida’s Turnpike Zone 8 ROG (kg) CO(kg) NOX(kg) January 181 8 35 February 162 7 32 March 173 7 34 April 207 9 41 May 220 9 43 June 224 9 44 July 220 9 43 August 211 9 41 September 173 7 34 October 171 7 33 November 157 7 31 December 144 6 28 Total 2243 94 439 Table C.23 Savings in Vehicular Emission s in Zone 12 in Florida’s Turnpike Zone 12 ROG (kg) CO(kg) NOX(kg) January 1020 44 212 February 916 40 190 March 975 42 203 April 1175 51 244 May 1239 54 257 June 1201 52 249 July 1244 54 258 August 1191 52 247 September 975 42 203 October 965 42 200 November 885 38 184 December 808 35 168 Total 12593 548 2616

PAGE 101

91 Appendix C (Continued) Table C.24 Savings in Vehicular Emission s in Zone 13 in Florida’s Turnpike Zone 13 ROG (kg) CO(kg) NOX(kg) January 736 32 153 February 661 29 137 March 705 31 146 April 844 37 175 May 896 39 186 June 863 38 179 July 898 39 187 August 859 37 178 September 704 31 146 October 696 30 145 November 634 28 132 December 586 25 122 Total 9083 394 1887

PAGE 102

92 Appendix D: FSPE Model Excel Sheets The FSPE model uses Microsoft Excel workbo ok for all inputs and outputs. MS excel interface makes the model user friendly and c onvenient to enter data and read the results. Figures E.1 (Input) and E.2 (Output) show the excel sheets used by the model. Figure D.1 FSPE Model MS-Excel Input Sheet FSP Beat Evaluation & Prediction Routines (version 12.1) Input Data Worksheet A. Beat/Service Description B. Beat Design Characteristics District 6 Beat Length (miles) 4.11 Analyst Harkanwal #Segments 8 Date July DIRECTION-1 NB Beat #/Name 281 Segment# 1 2 3 4 5 6 7 8 Beat Description I-95 Length (mi) 0.964 0.03 0.162 0.512 0.524 0.508 0.944 0.468 # Mixed-Flow Lanes 2 2 3 3 3 3 3 4 StartTime EndTime # FSP HOV Lane N N N N N N N N Hours of Operation/# FSP Trucks (hr:min) (hr:min) Trucks Rt Shdr Y Y Y Y Y Y Y Y AM Peak 0:01 6:00 2 Lt Shdr (Median) Y Y Y Y Y Y Y Y Midday 6:01 18:00 3 PM Peak 18:01 22:30 2 DIRECTION-2 SB Segment# 1 2 3 4 5 6 7 8 Number of Service Days/Yr 31 Length (mi) 0.964 0.03 0.162 0.512 0.524 0.508 0.944 0.468 Cost of FSP Service ($/truck-hr) $35.00 # Mixed-Flow Lanes 2 2 3 3 3 3 3 4 HOV Lane N N N N N N N N Rt Shdr Y Y Y Y Y Y Y Y Lt Shdr (Median) Y Y Y Y Y Y Y Y D. Incident Characteristics Total FSP Assists (Inc/yr) 400 C. Beat Traffic Characteristics Incident # Incidents Mean time Segment # 1 2 3 4 5 6 7 8 Type/Location or (%) spent (min) AADT 26000 97000 97000 100500 90000 102500 109000 109000 Accident Right Shoulder 3.59 51.13 AM PEAK Dir. NB NB NB NB NB NB NB NB Lt Shldr (Median) 1.00 51.13 D factor (%) 50.00 50.00 50.00 50.00 50.00 50.00 50.00 50.00 1-Lane 8.40 51.13 MD PEAK Dir. NB NB NB NB NB NB NB NB Breakdown Right Shoulder 43.13 14.68 D factor (%) 50.00 50.00 50.00 50.00 50.00 50.00 50.00 50.00 Lt Shldr (Median) 5.50 16.82 PM PEAK Dir. SB SB SB SB SB SB SB SB 1-Lane 35.88 16.82 D factor (%) 50.00 50.00 50.00 50.00 50.00 50.00 50.00 50.00 Debris Right Shoulder 0.53 6.50 Lt Shldr (Median) 0.13 6.50 1-Lane 1.64 6.50

PAGE 103

93 Appendix D (Continued) Figure D.2 FSPE Model Output in MS-Excel FSP Beat Evaluation & Prediction Routines (version 12.1) Summary Evaluation Results Worksheet Input Data FSP Operational Parameters District 4 Delay Cost ($/veh-hr) $13.45 Analyst Harkanwal Fuel Cost ($/gal) $1.96 Date July Beat #, Name 281 Mean Response time w/o FSP (min) 30.0 Beat Description I-95 Beat Length (miles) 17.26 FSP Response Time (min) AM Peak 11.5 Start End # FSP Midday 8.6 Hours of Operation/ # FSP trucks Time Time Trucks PM Peak 11.5 AM Peak 0:01 6:00 3 Midday 6:01 18:00 4 FSP Response Time Reduction (min) PM Peak 18:01 23:00 3 AM Peak 18.5 Midday 21.4 Number of Service Days/Yr 365 PM Peak 18.5 Cost of FSP Service ($/truck-hr) $35.00 Total FSP Assists (Incidents/yr) 1,654 Traffic Profile Weekday Time Period Daily/Annual Savings-Performance Measures AM Peak Midday PM Peak Savings-Performance Measures Daily Annual Delay (veh-hrs) 3.2 619.4 23.7 Delay (veh-hrs) 646.37 235,924 Fuel Consumption (gal) 4.8 934.4 35.8 Fuel Consumption (gal) 975.00 355,873 Emissions Emissions ROG (kg/day) 0.48 92.65 3.55 ROG (kg/day, kg/yr) 96.68 35,288 CO (kg/day) 0.02 3.88 0.15 CO (kg/day, kg/yr) 4.05 1,480 NOx (kg/day) 0.09 18.16 0.70 NOx (kg/day, kg/yr) 18.95 6,916 Cost Effectiveness Cost Effectiveness Delay Benefits ($/day) $43 $8,331 $319 Delay Benefits ($/day, $/yr) $8,694 $3,173,172 Fuel Benefits ($/day) $9 $1,831 $70 Fuel Benefits ($/day, $/yr) $1,911 $697,511 Total Benefits ($/day) $53 $10,163 $389 Total Benefits ($/day, $/yr) $10,605 $3,870,684


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Singh, Harkanwal Nain.
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A benefit-cost analysis of a state freeway service patrol :
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by Harkanwal Nain Singh.
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[Tampa, Fla] :
University of South Florida,
2006.
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ABSTRACT: The Road Ranger program is a freeway service patrol (FSP) designed to assist disabled vehicles along congested freeway segments and relieve peak period non-recurring congestion through quick detection, verification and removal of freeway incidents in Florida. It consists of approximately 88 vehicles in fleet and provides free service to about 918 centerline miles. The program is funded by the Florida Department of Transportation (FDOT) and its partners, and is bid out to private contractors. The objective of this study is to examine and evaluate the benefits of the Road Ranger service against their operating costs in five of the seven FDOT Districts and Florida Turnpike Enterprise. The five Districts were chosen due to the availability of Road Ranger program data and activity logs for analysis.The Road Ranger program provides direct benefits to the general public in terms of reduced delay, fuel consumption, air pollution and improved safety and security. The benefits would ^be expected to be more significant during the peak period when demand reaches or exceeds capacity than in the off-peak and the mid-day period where capacity may not be as significant an issue. The costs considered in this analysis include costs of administration, operation, maintenance, employee salaries, and overhead costs.Incident data were obtained from the daily logs maintained by the Road Ranger service provider containing important information about the time, duration, location, and type of service provided. Other data collected for this study include average daily traffic volume, geometric characteristics of the freeways, unit cost of Road Ranger service, etc.The Freeway Service Patrol Evaluation (FSPE) model developed by the University of California-Berkley was calibrated and used to estimate the benefit-cost ratio for the Road Ranger program. The estimated benefit/cost ratios based on delay and fuel savings indicate that the Road Ranger program produces significant benefits i n all the five Districts and Turnpike. The range of benefit-cost ratio of the Road Ranger program in different districts is from 2.3:1 to 41.5:1. The benefit -cost ratio of the entire Road Ranger program is estimated to be in excess of 25:1.
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Thesis (M.A.)--University of South Florida, 2006.
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Adviser: Ram Pendyala, Ph.D.
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Road rangers program.
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Roadway capacity.
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Freeway incident management.
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