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Development of expected value conflict tables for Florida-based traffic crashes

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Title:
Development of expected value conflict tables for Florida-based traffic crashes final report
Physical Description:
1 online resource (91 leaves) : ill. ;
Language:
English
Creator:
Florida -- Dept. of Transportation
University of South Florida -- Center for Urban Transportation Research
Publisher:
University of South Florida, Center for Urban Transportation Research
Place of Publication:
Tampa
Publication Date:

Subjects

Subjects / Keywords:
Traffic accidents -- Forecasting -- Florida   ( lcsh )
Roads -- Interchanges and intersections -- Florida   ( lcsh )
Traffic surveys -- Florida   ( lcsh )
Genre:
bibliography   ( marcgt )
technical report   ( marcgt )
non-fiction   ( marcgt )

Notes

Bibliography:
Includes bibliographical references (p. 41).
Funding:
Prepared in cooperation with the Florida Dept. of Transportation and the U.S. Dept. of Transportation under contract nos.
Statement of Responsibility:
by the Center for Urban Transportation Research, University of South Florida ; prepared for the Florida Department of Transportation.
General Note:
Title from cover of e-book (viewed Aug.12, 2011).
General Note:
"April 1996."

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University of South Florida Library
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University of South Florida
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All applicable rights reserved by the source institution and holding location.
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aleph - 029924247
oclc - 746571191
usfldc doi - C01-00006
usfldc handle - c1.6
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PAGE 1

DEVELOPMENT OF EXPECTED VALUE CONFLICT TABLES FOR FLORIDA BASED TRAFFIC CRASH E S FINAL REPORT Prepared for the Florida Department of Transportation by the Center for Urban T r ansporta t ion Research University of South Florida Apri l 1996 This report has been prepared in cooperation with the state of Florida Department of Transportation and the U.S. Department of Transportation under WPI No. 0510721, State Job No. 99700-7625-199, Contract No. B-9079, and CVTR AccoUIIt No. 21-17-147-LO. The opinions findings and conclusions expressed in this publication are those of the authors and not necessarily those of the State of Florida Department ofTransportation or the US. Department of Transportation.

PAGE 2

Rtport Documentati on L Ho. 1. Go"''""'"' Acu ion No. l. R.cirtiont' 1 C otolot No. Final Repore lll' l No. 0510721 .4., Tide otul Svbtitle S. Ropot Oore Development of Expected Value Conflict Tables for April 1996 Florida-Based Traffic Crashes 6. P111o--., Codt (Detailed Research Report) PtJfo(fllillt O 'tonirotion Atpor t No 1 Av\horfs) Michael c. Pietrzyk 9. Ortonitolion H t lllo 011.d Addrou 10 'Wolt Unit No. (TRAI S) center for Urban Transportation Research (CUTR) University o f south Florida'-College of Engineering 11. o C cll No. 4202 East Fowler Avenue -ENB 118 99700-:7625ll9 tampa, Florida 33620-5350 ll. ol R,,.,,, ond P, ... . (o,.c" \), Spol'lloi n g Agoncy HOSI'Ie ond AdcfU Final Report Florida o f Transportation Sept. 1 1994-April 19. 1996 60 5 Suwannee.Street u S;oMorinv Av,ncy Coc!'l" Tallahassee, FlOrida 3 2 399-0450 IS. Notu Prepared in cooperation with the u.s. Department of Transportation and the Federal Highway Administration. \6. Ahslloc.l .. The new crash. reporting requirement. in Florida has significantl y reduced the number of crash reports available for roadway safet y studies. Therefore, t h e demand for accurate'crash surrogatedata increased. Addit;i.onally, the curtent method of est imating crash surrogate data (Traffic Conflict Techni que s f o r Safety and Operations 'Engineers Guide, FHIIA-IP-88-026, Jan. 1989) is based on a National H ighway Institute study conducted i n 1982 in Kansas City. Missouri, for 48 intersections. .. This report documents a comprehe nsive traffic conflict study conducted by CUTR to obser v e cc>llect crash data and develop new, simplified, expected value tables for Florida-based intersections and conditions. Thirtee n traffic conflict types were surveyed from 178 intersections sampled from a five-county area in west-central F.lo rida. lthese tables can be used to estiDate the expected annual number of \different intersection types, and provide 90th and 95th percentile per day to evaluate relative safety problems at intersections . I 1 ; .c,.,w,,es 1;. Oth0"'"" s,.,, .... .,, crashes a t conflict rates conflicts, crash-to-conflict This report is available co the public I I I I I I I ' ; ratios, intersections, conflict through the National Technical Information observer training, expected values, Service, Springfield, Virginia 22161. !yearly crash prediction, Florida-based No I conditions for I :1. :.t,., ofF Of1U :
PAGE 3

METRI C (SI*) CO N VE R S I O N F ACTORS A PPROXI M ATE CON VERSIO N S TO Sl U N ITS IJIIIIfloOI WIMfl lltM w Mliii11P'i l'f h Jlft In "' "" ... ... "' .... "' .. IO T ,., ... ,.. lnt:htl let t y trds mllu .ou.a.r k'lcrt.s qu-.rt .... aoua yl!rds ..,., ....... ..... LENGTH '"' D lQ.4a O i U Ut 1\_J\EA .... ...... 0.1>6 ut ..,.. m iiU M ttft l mt\lt l "'' '''' kllomtlft l "'"''' toCWiliN fl111MMtrt.t ... , . M ASS (weight) ouneet 21 ,)$ pound.s o .S4 anon o" t2000 lb) o.to7 ti"'d Of.lf\C:..I Gil lions toublc ' wbic; y uds VOLU M E 29. SJ l .JI$ 0 0321 0.076S o nmt llllogr a m t ml.llllllft t turn mttrtt cub.., lfltlltl CUbHI NOTE : Voturn .. Orttltt lOCO L t h ll ll M snowl'l I n m ., TEM P E RATURE (e xact) F t twafthotq l l ti'IIM'fi.I W I $(9 ( If"' C.lllilf.S SV01fac-..o IMIICI-.ftlllft 'Sl I$ ll'll l'tmbol IOf t l'l e ST:S\111'1 ol MUIVollll'lli'!li S'ri"Mf mm m m m """' ... ... .... ... ... mL L m' m 'C i ___, .., : : t-= r .. ;: a !C"'i ., ------: .. II ;L. : I .. : : / L ... -!!--..., ---:; r .., -::; .., ..., ---:; --; .._, i .; -;; -r' g_ r = -2 ;r--=;----.. A PPRO XIM ATE CONVER SIONS T O 51 U N ITS hMMI W trl"' Vtu _,.o ... <4tlpt, ''""" mm m m ... .. .... ... .... 0 ... "'' L "'' m 'C mlllm t ltu "''" ' ""'"'' . kMOMtUU "'I Mwneuu melfu IClll recl IIJ!Offt llr1 1 M'IMM hKIOt9.t (t Q DOD frl, LENGTH 0.039 1 .09 O .Ut Af!.EA Q.QQ16 10 .76& 0.>0 .... lncnu 1 .. )'lldl mt._,
PAGE 4

TABLES OF CONTENTS EXECUT I VE SUM M ARY . . . . . . . . . . . . . . 1 I. PURPOSE . . . . . . . . . . . . . . . . . . . . . 2 II. CONFLICTS AT I N TERSECT I ONS . . . . . . . . . . 3 A. General De f ini t ion of Traffic Confl ict . . . . . . . 4 B. Conditions for a Traffic Co n f lict . . . . . . . . . . . . 4 C I denti f i cation of a Traffic Confl ict ...... .. ........ 4 Ill. INTERSECTION SAMPLING ........ ................. 5 A. State of F l orida and Study Area . . . . . . . . . . . . . 5 B. Intersection Categories . . . . . . . . . . . . . . . 6 C Samp ling Method . . . . . . . . . . . . . . . 7 D Intersection Information Verifications ... . ........ 9 IV. FIELD DATA COLLECTION OF INTERSECTION CONFLICTS . . . . 11 A. Observer Recrui tment a n d Train ing . . . . . . . . . . . . 11 B. Fie l d Work Requirements . . . . . . . . . . 12 C. Field Work Scheduling . . . . . . . . . . . . . . . . 14 D. Problems Encountered a n d Remed i es Uti l ized . . . . . . . . 14 V ANALYSIS OF CRASH REPORTS . . . . . . . . . . . 19 A Intersection Related Crashes . . . . . . . . . . . . . . 19 B. Crash Report Screen i n g . . . . . . . . . . . . . . . 19 C Prob lems Encountered and Remed i es Utilized . . . . . . . . 20 VI ANALYSIS OF CONFLICT AND CRASH DATA . . . . . . . . . 21 A. Analysis of Conflict Data . . . . . . . . . . . . . . . 21 B. Crash/Conf lict Ratio Data . . . . . . . . . . . . . . . 25 VI I. COMPAR I SON OF FLORIDA TABLES A N D NATI ONAL TABLES ....... 28 A. Intersection Classificat i ons . . . . . . . . . . . . . . 29 B. Data Collection . . . . . . . . . . . . . . . . . . 30 C C omparison of t he Florida and Nationa l Studies . . . . . . . 31

PAGE 5

VIII. SUMMARY OF FINDINGS . . . . . . . . . . . . 38 IX. RECOMMENDATIONS . . . . . . . . . . . 40 BIBLIOGRAPHY . . . . . . . . . . . . . . . . . . . . . 41 APPENDICES A Comparison of the Five -county Area with the State of F l orida . . 42 B. Distribution of Surveyed I ntersections in Five-county Area . . . . 50 C. Data Base for Conflict and Crash Data . . . . . . . . . . 65 D. Expected Conflict Value Ta b les for Florida-based Intersections . . 72 E. Crash / conflict Rat i o Tables for F lo r ida-based Intersections . . . . 82

PAGE 6

LIST OF TABLES Table Page 1. Intersection Categories 6 2. Distribution of Intersection Categories 10 3. Sampled Intersection Types and Intersection Volume Threshold Groups 30 4. Comparison of National and Florida Tables: Signalized, 4-Legged, 35 10,000 25,000 Daily Volume 5 Comparison of National and Florida Tables: Signalized, 4 Legged, 36 More t h an 25,000 Daily Volume 6. Comparison of National and Flor i da Tables: Unsignalized, 4 Legged 37 2,500-10,000 Daily Volume 7. Comparison of CrashfConflict Ratios for National and Florida Tables 38

PAGE 7

ACKNOWLEDGEMENTS The Center for Urban Transportat ion Research (CUTRl would li ke to recogn i ze and thank several key indiv i duals for their ass istance and contributions to this evaluation project and report. Patrick Brady, Transportation Safety Engineer, served as the project manager for Florida Department of Transportation (FOOT). Keith Crawford (FOOT, District 7) and Richard Gillenwater (FOOT, Distr ict 1 ), Ahmed Aburahmah {Manatee County), Art Chesley (Manatee County). Karl Stewart (Pasco County), Douglas Fraker (Polk County), Adrian Colefield (Sarasota County), and Deputy Brett Saunders (Hi llsborough Sher iff's Office) provided data and overall assistance during this project. The principl e i nvest igator and author for this project report was Michael Pietrzyk, Senior Research Associate and ITS Program Manager at CUTR. The project staff were Dr. Ram Pendyala, Assistant Professor Department of Civil and Environmental Engineering, University of South Florida (USFL Mark Dummeldinger, Department of Business Communications, USF, and CUTR Graduate Research Assistants Sujeeva Weerasuriya, Venkat Vattikuti, Weimin Huang Dr. Pendyala served as the pier reviewer for the pro j ect. Mr. Dummeldinger served as the statistical consultant to the project and analyzed the conflict and crash data Mr. Weerasuriya served as observer t raining instructor, field supervisor and co-author the reports. Mr. Huang served as the conflict and cras h database manager Joel Rey, Research Associate at CUTR, and Janet Becker, Editor at CUTR, provided assistance in observer training and field work schedu ling CUTR would also like to thank the following individuals who served as traffic conflict observers: Tracy-Ann Anthony, Danny Eadens, Daren Easter ling, Prashant Gadepalli, Paul Galonsky, William Gross, Sara Hagge, Cynthia Joiner, Mazen Khaddam, Ahsan Khalil, Jeff Kromalicki, Phyllis Lewis, Sr i kanth Pandurangi, Vasil Parousis Bhargava Puligandla, Amir Oazi, Margapuri Ravikiran, Frank Sasso, and Mudambi Vasudevan.

PAGE 8

EXECUTIVE SUMMARY The new crash reporting requirement in Florida has significantly reduced the number of crash reports available for roadway safety studies. Therefore, the demand for accurate crash surrogate data has increased. The current method of estimating crash surrogate data is based on a national study conducted during Summer 1982 in Kansas City, Missouri for 48 intersections. The mechanical characteristics and safety features of vehicles have undergone significant changes (e.g., anti-lock brakes) since then The r efore, investigating the va lidity of the national tables for curren t conditions and developing s i milar tables for F l orida-based intersection conditions were necessary. A comprehensi ve traffic con flict study was conducted by the Center for Urban Transportation Research (CUTR) to observe traffic conflicts, collect crash data and develop tabl es for Florida based intersections. During the study." the fifteen most common intersection types were ident i fied. The intersection types were categorized based on signali z ation, number of legs (three or four) and through (general ) laneage of the i n tersection. Thirteen traffi c conflict types were surveyed from 178 i ntersections samp l ed from a five -county (Hillsborough, Manatee, Pasco, Polk, and Sarasota) area The most recent three-year (1992 1994) crash history of the sampled i ntersections was colle c ted and re l ated to the conflict counts. Based on the conflict and crash data new and easy-to-use tables were developed for F l orida-based i ntersections. These new and simp l ified F l orida-based tab les can be used to estima t e the expected number of crashes at intersections. Additionally, the tables provide 90th and 95th percentile conflict rates per day for each of the fifteen intersection types and conflict types to evaluate the relative safety and operational problems at i ntersections.

PAGE 9

I. PURPOSE The Florida Department of Transportation entered i n to a contract with the University of South Florida, on behalf of the Center for Urban Transportation Research (CUTRl. to determine the impact of Florida-based crashes on the National Highway Institute's expected value tables and to develop, new, easy to use expected value tables for Florida conditions This report includes a compilation of two previous summary reports on the data collection plan and data collection results for this study, conflict and crash data analysis res ults, and recommendations to modify the national tables for Florida conditions. The first summary memo on data collection p l an provided a detailed description of intersection categories, sampling intersections, intersection information verifications, field staff recruitme n t and training, field work requirements, and field work scheduling The second summary memo on field work included intersection category distribution in the five-county area and conflict counts at sampled intersecti ons. Conflict and crash data analysis results are included i n the new expected value tab l es developed for F l orida-based intersections In this analysis, the national ( Kansas City b ased study) tables and Florida-based tab l es a r e compared. Recommendations are m a de based on results of the analysis. CUT R also prepared the Training Tool-Kit For Vehicle Conflict Observations At Intersections (April 1996) as an observer training aid and the Expected Value Conflict Tables For Florida-Based Traffic Crashes, user tables, (Ap ri l 1996) as a stand alone report to be included in the state highway safety manual 2

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The Florida-based tables can be used to: identify intersections with safety and operational problems identify high risk vehicle movements (the most frequently occurring conflict types) at intersections and take remedial actions prioritize safety improvements for a selected number of intersections estimate expected crashes at newly built or recently changed (i.e., change f rom unsignalized to signalized and/or number of l egs ) intersections estimate crashes at intersecti o ns where recent historical crash reports are not readily accessible or do not exist study in tersect ions other than high crash intersections II. CONFLICTS AT INTERSECTIONS Introduction According to FOOT Safety Eng inee rs, the requirement for reporting traffic crashes (in state crash database) in Florida has reduced the number of crash reports availab le for engineering study by approximately half. (The state crash database includes only those crashes involving hit and run fatality, DUI, and injury. However, the county crash databases i nclude all reported crashes on a ll roads). This situation has resulted in an increas ing difficulty in the identificati on and j ustification of highway safety improvements. If the anticipated consequences of hazardous conditions are to be resolved, there is a nee d t o supplement the available crash data o r sometimes use surrogate data (for example conflict data and their relationship to actual crashes) to identify highway safety problems. The current National Highway Institute (NHI) tables that list conflict da ta and their relationship to actual crashes are based on a study conducted during Summer 1982 i n Kansas City, Missouri. Since then, mechanical characteristics and safety features of vehicles have undergone significant changes (e.g .. anti-lock brakes). Therefore. investigating the validity of the tables for current conditions and developing similar tables for Florida-based intersect ions were necessary. 3

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Results of this study can be used to develop criteria to utilize these values in the development, justification, implementation and evaluation of highway safety improvement projects in accordance with FOOT's Highway Safety Improvement Program Guideline (Topic 500-000-1 00). A. General Definition of Traffic Conflict According to Traffic Conflict Techniques for Safety and Operations Engineers Guide (FHWA-IP-88-026 January 1989) a traffic conflict is defined as "An event involving two or more road users, in which the action of one user causes the other user to make an evasive maneuver to avoid a collision." The road users include motorists, pedestrians and cyclists. However, the current study was focused only on conflicts involv ing motor vehicles, which is i n accordance with the nationa l (Kansas City-based) study. B. Conditions for a Traffic Conflict According to the definition, therefore, presence of two or more vehicles is necessary for a traff ic conflict to occur. These vehicles must also be on a collision course [i.e., the vehicles must be attempting to occupy the same space at the same t ime), creating a conflicting driving environment to drivers of the involved vehicles. If these conditions exist in a traffic event, it can be termed a "traffic conflict." C. Identification of a Traffic Conflict A traffic conflict can be identified by careful observation of traffic flow at an intersection. When the action of a vehicle (first vehicle) places another vehicle (second vehicle) on a collision path unless the second vehicle takes evasive action to 4

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avoid a crash, this situation is identified as a traffic conflict. The evasive action of the second vehicle can be identified by one or more of the following. brake-light indication front lounging of the vehicle or squealing of t ires swerve of a vehicle Ill. INTERSECTION SAMPLING A. State of Florida and Study Area The population of in terest in the current study consisted of all in tersections in the State of Florida. However, se lecting samples from all over the state and conducting conflict counts with a constrained budget was neither practicable nor feasible. Therefore, selecting a sample area of the state that adequately represents the conditions of Florida intersect ions was necessary. A five-county area of west-central Florida !Hillsboro ugh, Manatee, Pasco, Polk, and Sarasota) was assumed to reflect the intersections in Florida and was selected as the sampling area (Initially, six counties including the five above and Pinellas were selected. However, Pinellas County was later dropped due to lack of responding to crash summary report requests). Several socioeconomic and tourism data indicators that contribute to defin i ng characteristics of the driving population of the five-county area were compared with that of the state to establish that the five-county area was a valid representa t ion of the state. The relevant socioeconomic factors are urban and rural population, income per cap i ta, age and gender distribution, higher education and employment, vehicles per household, and transportation to work. Appendix A provides the comparison graphs for these different factors. From the comparison graphs for the factors suggested above, It i s seen that the five-county area's averages match well with those of the state averages. The Florida Department of Commerce and Bureau of Economic Analysis reported, in their 1994 Florida Visitor Study, that Hillsborough and Sarasota are two of the top ten destinations of auto travelers. The report also shows 5

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that Hillsborough is one of the top ten destinat i ons of air travelers as well. Th is indicates that unfamil i ar drivers, ma i nly tourists, are well represented in the five county area. The factors investigated he re reflect the types of dri vers on the r oad network. Therefore, based on these set of factors the selected five-county area is indeed a representative area of the State of Florida. B Intersection Categories Through d i scussions among county traffic engineers, FOOT District 1 and 7 safety engi n eers and the FOOT Safety Offi ce in Tallahassee fifteen ( 15) intersection categories (or types) were identified (table 1) as common i n the State of Florida (as well as in the five-county sampled area). CUTR's objective was to find 12 examples {intersections) of each type in the five-county area, a total survey of 180 i ntersections. Table 1 Intersection Categories 1. S4A = s i gnalized, 4-legged, 2x2 10. U4A = unsignalized, 4-legged, 2x2 2. S4B signalized, 4-legged, 2x4 11 U4B = unsig n alized, 4le gged, 2x4 3. S4C = signalized 4-legged, 2 x 6 1 2 U4C = uns i gnalized, 4-legged, 2x6 4. 540 = signalized, 4-legged 4x4 13. U3A = unsignaliz e d. 3-legged 2x2 5. S4E = signalized, 4-legged 4x6 14. U3B = uns ignalized. 3egged, 2x4 6. S3A signalized 31 egged, 2x2 11:\C: -o. ?-" 7. 538 signalized. 3egged, 2x4 8 S3C = signalized, 3-legged, 2x6 Q -.. ... In compari son to the national tables, intersection types are also categorized by s i gnalized vs. unsignalized and 4-legged vs. 3-legged. I n the national tables, t hese in t ersect i ons are then sub-grouped according to different daily approach volume thresholds (2,500-10,000; 10,000-25,000; and greater than 25,000). Should traffic/safety analysts were to use t h ese national tables w ith different daily approach 6

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volume thresholds for an intersection safety study, conducting traffic volume counts would also be necessary along with conflict counts. For convenience in field data collection, therefore, laneage was used in the current study as a surrogate for the daily approach volumes. This will reduce the required scarce resources (time, labor, and money etc.) that otherwise would have been used for the safety study. The procedure of converting intersection laneage to corresponding daily approach volume thresholds {for comparison of national and Florida tables) is discussed in pages 29-30. C. Sampling Method Within t he five-county region, 14,347 intersections h ave available crash data for the 1992-1994 period. These intersections represent the sampling time frame from which the random sample of approximately 180 intersections for conflict observations were to be taken. The category of each i ntersection was unknown before random sampling. The first phase of the sampling plan randomly sampled 800 (ultimately 643, after dropping out Pinellas County) intersections from the 14,34 7. A unique number for each intersection by county was assigned, and a random number generation program selected the unique numbers by county until a total of 800 intersections were selected These randomly selected intersections were sorted by county, and each county (or FOOT District Office) was asked to furnish the category type for the intersections selected from their county (or the District) as well as any information that might excl ude an inte rsection from being sampled {i.e., capacity improvements in the last three years, or currently undergoing reconstruction). The sampling plan called for each category type to include a sample of 12 intersections to be studied {i.e., an equal number in each of the fifteen intersection categories). After the requested information was collected from the counties lor District office). CUTR began selecting intersections for the study. Both the information fro m the counties {or District offices) and the random sampling order were taken into consideration. 7

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After the first sampling phase was completed, 76 of the original 643 were accepted as intersections to be included in the study. CUTR also made the following observations during the first sampling plan: 1) The time between when the counties received the intersection list and when the requested informat ion was received was far too long (given the completion schedule for this research effort) to continue the current sampling method. 2) Because t he vast majority of intersections were of the smaller category types (e.g., 2x2l. the larger intersection types (e.g., 2x6, 4x4, and 4x6) would be more difficult to find given the current sampling plan. 3) The number of t imes CUTR staff would have to go back to the individual counties (or FOOT District Office) would have to be reduced to ass u re a timely response and to maintain the overall project schedule. Due to t hese observations, the sampling plan was changed to allow for easier access to the information In an efficient manner while still maintaining the desired randomness of the sampling. The following description of the second phase of sampling outlines the changes made in the selection method for the remaining intersections nee ded for conflict observation. The second phase of the sampling plan involved a member of CUTR meeting once with representat ives from each county (or District Office). and gathering information on as many i ntersections as the county (or District Office) could give. nme (approximately three hours for each visit) and knowledge limitations dictated that geometric information of 2,051 (or 14.3%) of the original 14,347 intersect ions were discussed and judged as acceptable for use in the study. Since the larger type of intersections were lacking following the first phase of sampling, the second phase of sampling in each county began with discussing those intersections with the greatest number of total crashes i n descending order in hopes of finding more of the la rger type intersections. 8

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From this list of 2,051, CUTR randomly sampled until each of the category types were filled with at least the desired 12 intersections. However, after this sampling two of the fifteen intersectio n categories {S3C and S3D) had less than 12 examples. Furthermore, at this point in the selection of intersections, f ir st-hand field verification was required to support all previous intersection characteristic data supplied by the counties (or FOOT District offices) before scheduling field crews for conflict observations. Locations of all the intersections selected for final analysis are plotted o n maps i n Appendix B. Intersections were marked on individual county base maps, and on a five-county area base map. The single, overall map illustrates the spatial relationship of the random selection of intersections. A list of the intersection names. sorted on county basis, are also include d as part of Appendix B. D. Intersection Info rm ation Verifications I n order to reduce lost t ime in the f ield due to ina ccurate intersection classification or location information, CUTR staff were assigned to visually verify the existence a n d characterization of every intersection previously identified and randomly selected for conflict observation Approximately 20 examples of each intersection type (except categories S3C and S3D that were lacking in examples following the second phase of sampling) were id entified for f i eld verification, in case any of the original 1 2 did not meet requirements for observation and had to be replaced from the sampling pool. Another reason for field verification was to ensure that Intersection reconstruction or adjacent construction, which could affect normal traffic flow, was not currently taking place. The best judgement and recollection of the counties (or FOOT District offices) determined if intersection reconstruction had occurred over the most recent three year period. Some of the remaining number of examples needed for categories S3C and 530 were f o und by searching the five-county area during the field verification period. The result of intersection verification, which led to the final distribution of intersection categories by county, is shown in table 2. 9

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Table 2 Distribution of I ntersection Categories In Five County Area INTERSECTION CATEGORY TOT. COUNTY INT. S4A S4B S4C S40 S4E S3A S3B S3C S30 U4A U4B U4C U3A U3B U3C Hillsboroug h 2 4 4 1 6 5 6 6 3 3 4 3 2 1 50 M anatee 2 6 4 1 3 4 1 2 6 4 I 3 1 42 Pasco 3 2 -I 2 -1 4 5 8 26 Polk 2 2 6 2 3 3 2 . 19 Sarasota 2 1 1 5 2 2 3 4 3 3 4 2 1 3 5 41 TOTAL 1 1 12 11 12 12 10 12 12 12 12 13 11 12 12 14 178 INTERSECTIONS Lege nd {Code for Intersection Typel: first Letter S/U : Signa l ized/ Unsignalized Second Numbe r 4/3 : 4-legged/ 3legged { or 'T') Th ird Letter Through Laneage: A = 2x2, B 2x4, C 2x6, 0 = 4x4, E = 4x6 10

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However, twelve individual intersections were difficult to find for all fifteenintersection categories. To achieve the desired twelve intersection observations, it was necessary to re-sample some intersections A total of 22 intersections (of 156 individual intersections) was sampled again. Due to the mis-classification that occurred and the lack of time and/or budget, re-sampling had to be limited. As a result, four different intersection categories, S4A, S4C S3A and U4C, were still short of the desired twelve observation samples. IV. FIELD DATA COLLECTION OF INTERSECTION CONFLICTS A Observer Recruitment and Training A carefully prepared observer training program is essential to any use of the NH I t ables (or the Florida-based tables). CUTR advertised for field work personnel throughout the USF-Tampa campus, and on April 21, 1995 conducted an orientation meeting for all those indiv i duals interested in being considered for employment. Approximately 40 persons (USF students) attended this meeting. CUTR briefed all attendees on the objectives of the project and the specific tasks they would be perfo rming. Attendees were also asked to complete an individua l profile sheet which detailed their availability, experience in traffic data collection academic level, and location and time preferences for field work. Following this meeting, CUTR staff used the profile information to assemble compatible two-person teams and individual reserves for the project. Ten 2-person teams and 15 reserves (a total of 35 field observers) were eventually established. The roster of field personnel, identif ied following the project orientation meeting, were required to participate in one of two comprehensive training sessions on conflict observations conducted by CUTR project staff. These identical training sessions were held on May 10 and May 16, 1995, and consisted of a fourhour classroom instruction and a three-hour field observation practice session and discussion The in tersection utilized for the afternoon practice portion of the training sessions was 11

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Bruce B. Downs Blvd./Pine St., a 4-legged. signalized, 6x2 intersection, immediately adjacent to the USFT ampa campus The training session included a thorough examination and discussion of t he definition of traffic conflicts and conflict types, a presentation of various scenarios where conflict types had to be determined, discussion of favorable conditions for conflict observation, technique for observing conflicts, requirements for documentation of conflict observations, requirements for intersection inventory documentation, review of "checklist" for tips and materials needed for f i eld work, first-hand practice and review with CUTR project staff of traffic conflict observation and documentatio n, and discussion and review of the entire training day's activities. Each attendee was also provided a copy of the Traffic Conflict Techniques for Safety and Operations Observers Manual prepared by the Federal Highway Administration (FHWAI. January 1989. Based on CUTR's experience, a 'Training Tool-Kit' was prepared for engineers and supervisors at public and private agencies who plan to conduct traffic conflict studies. This tool-kit, which should be used along with Observers Manual prepared by FHWA, January 1989, provides an essential guide to trai n observers for conflict observat ions at intersections. B. Field Work Requirements CUTR pro ject staff, after thorough review of the reports documenting the rationale and technique used to develop the national traffic conflict value tables, d e veloped the protocol for this project. Two-person teams were assigned to each intersection, with one person at oppos i te intersection legs observing conflicts. A total of two hours of conflict observation was documented for each leg ( i.e., 8 man-hours total for 4-legged intersection and 6 man-hours total for each 3-legged intersection). With 178 (excluding four i ntersections that did not fit into one of the f ifteen intersection types) intersections for observation, and six of fifteen intersection types being 3-legged, at least 1,256 total man-hours of conflict observation was recorded As a comparison, the national tables were based on a total of 1,536 man-hours of o bservation, however, this time was spread over only 48 intersections. Therefore, the 12

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methodology used in this study accounts for more variability among the various types of intersections. Conflict observation periods occurred over a four-hour period, either 7am-11 am or 2pm-6pm, Mondays through Thursdays. Following the National {Kansas City-based) study, only thirteen conflict types (including the "other" category for conflicts) were observed and recorded for signalized intersections. Namely, Same direction conflicts 1. left-turn 3. lane change It Opposing direction conflicts 1 left-turn "-r Cross traffic conflicts 1. left-turn from left ...It 3 right-turniross traffic from left 5. through, cross traffic from right -t 2 slow vehicle f 4. right-turn ( 2. r ight-turn on red <\ 2 through, cross traffic from left -, 4. left-turn, cross traffic from right ( 6. right-turn, cross traffic from right r-Twelve conflict types {except opposing right turn on red from the above lis t } were observed and recorded for unsignalized intersections. The number of each conflict types was recorded in hourly increments. As in the national Kansas City-based) study, only vehicle conflicts were recorded (i.e .. pedestrian and cyclist conflicts were neither observed nor recorded) 13

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Upon completion of the required period of conflict observations at each intersection and before the obse rvation team departing the intersection, an inventory of intersection characterist i cs was documented. The inventory included an intersection sketch, through and separate turn i ng laneage, pavement markings, overhead/roadside signage a general descr iption of adjacent land use, signalization (protected/permitted), presence of curb and gutter (rura l vs. urban). and other recurring events not related to conflicts (e.g., relative volume of trucks, relative vol ume of out-of-state/out-of-county l icense p l ates, excessive U turns, etc.). C Field Work Schedul i ng Again, using a random selection technique the day (Monday through Thursday) and time (7am am or 2pm6pm) to conduct conflict observations for each intersection was determined. The morning and afternoon periods were selected tor observations, which is in accordance with the national (Kansas City based) study, to capture typical peak hour condi tions. The conflict surveys were conducted for two consecutive 2 hour periods with 51 0 minute breaks in between. Therefore the maximum number of i ntersections a team of observers was scheduled, was limited to two in a single day. Further. if two intersections were scheduled i n a single day they were located in the same county (or not more than one hour traveling time apart from each other) To reduce fatigue errors, observer teams were never scheduled more than three intersections i n a consecutive two-day period D. Problems Encountered and Remedies Utilized Throughout the 14-week data collection period (June 6 through September 6, 1995), several problems were encountered that had to be remed ied before the data collection cou l d proceed These problems not listed in the order of importance, are documented below. 14

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a. CUTR frequently supervised the observation teams to verify the team members were conducting their work in accordance with the Data Collection Plan and the NHI "Observer's Manual" (provided to each observer). For example, about 60% of the intersections in Hillsborough County were supervised during conflict observation; about 20% of the total intersections surveyed were supervised. The other purpose of supervision was to assure consistency, accuracy, and completeness in observation across all observation teams. Every possible effort was made to schedule intersections close to both team members to minimize circuitous travel and keep the observation team in the same area/county for the week. One two-person team did not adhere to observation requirements for documentation and had to be dismissed, requiring six intersections to be re-surveyed. b. Even with initial screening of intersections randomly selected for conflict observation, it was later found that a total of six intersections (two from Polk County, three from Hillsborough County, and one from Sarasota County) had to be withdrawn because they had undergone geometric improvements within the last three years. c. Conflict observations were not made on holidays over the 14-week data collection period, which included Independence Day (July 4 Tuesday) and Labor Day (September 4 Monday), to avoid traffic variations. Since data collection for crashes were taken for the most recent three year period (1992, .1993, 1994), crashes occurring on holidays during t his period were also excluded. A total of 21 national holidays occurred over this three-year period and thus crashes recorded on these 21 days were not included in the crash portion of the database (e.g., New Year's Day, Martin Luther King Day, President's Day, Memorial Day, Independence Day, Labor Day, Veteran's Day, and Thanksgiving Day. Christmas fell on either Friday, Saturday, or Sunday during this time}. 15

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d. Conflicts under wet pavement conditions are not meant to be included in the analysis. Therefore, approximately 25 inte rsections had to be re surveyed due to inclement weather occurring just prior or during observations. When inclement weather occurred (i.e., weather necessitating either vehicle lights and/or windshield wipers to be engaged), the teams were instructed to remain at intersection for at least 30 minutes or until inclement condition vanished If inclement weather remained for more than 30 consecutive minutes, observers were instructed to stop the survey and the intersection was rescheduled later for the same day and time. If inclement weather stopped within the 30-minute per io d, observers were instructed to record stop and start times on their observation sheets, and resume their observations under dry pavement conditions (to capture a total of two hours of observation on each leg). e. During data collection, several intersections were undergoing repairs disrupting the normal traffic flow as the observers arrived on the scene. The observers were instr ucted to report such i nc i dents immediately and the in tersect ions were rescheduled at a later day at the same day and time. Only one intersection could not be rescheduled to avoid repair (non-capacity improvement) work. f. Approximately 20 intersection sketch sheets were initially unusable or questionable and had to be corrected either by further discussion with observation team and/or f i eld verification for a second t ime by CUTR project staff. g. Thirteen (13) intersections were initially mis-classified. The most common re ason for mis-classification was regarding the number of legs at an intersection. CUTR's rationale was that a signalized intersection should have at least one signal head serving each leg. For an unsignalized intersection, any leg with little or no traffic (dirt road, single-use driveway, short dead-end, etc.) was eliminated and accompanying conflicts also eliminated. 16

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Some intersections of the 13 that did not fit the conventional description of a three-legged or four le gged intersection (total of four) were included as anomalies only, and were not placed into one of the 15 intersection categories nor were they used in the development of crash to conflict ratios. h. Even though maps, with intersection locations marked, were provided to observer teams, severa l teams got lost or surveyed the wrong i ntersection (five). For example, in Manatee County streets and avenues are oriented one way north of the Manatee River and are oriented in the opposite manner south of the Mana tee River; 4th Avenue & 16th Street could exist in two p laces and thus had to be confirmed by the CountY. Also, one horseshoe-shaped street i n Pol k County had the same Intersection name and intersection type at each end; once again the County had to disti nguish which intersection was randomly selected for observation. 1. Observers were instructed to r ecord any recur ring or "special" events that occurred at each intersectio n during periods of conflict observations. Twenty different conflict types were noted as shown on the index sheet for the database contained i n Appendix C of this report. The three most frequently occurring even ts were: (a) slow-moving vehicles due to corner driveway for office, park ing lot, convenience store, gas station, (b) right turns on red, and (c) slow-moving vehicles due to trucks, bikes, or emergency vehicles. j. At the end of the field verification, there were two i n t ersect ion categor ies (S3C and S3D) that did not contain the desired twelve intersections. Finding enough samples for these categories was difficult. Therefore, r e-samp lin g some of t he selected intersections was necessary to achieve the desired twelve intersection observations. The 17

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intersections to be re-sampled were also randomly selected by day and time as before. A total of 22 intersections were sampled again. Additionally, due to the initial mis-classification and the lack of time andfor budget, re-sampling had to be limited As a result, four different intersection categories, S4A, S4C, S3A and U4C, were ultimately short of the desired twelve observation samples. k. The morning observation period began at 7am and ended at 11 am, and the afternoon observation period began at 2pm and ended at 6pm. As weather delays persisted, observers were instructed not to observe conflicts beyond one hour of the respective ending times for each observation period In three cases, because observations went beyond 7pm, conflict counts at these intersections were taken again. Likewise, crash reports from each county were screened to include only those crashes occurring between 7am and 6pm. I. Traffic conflicts observed that were not one of the twelve designated types were grouped under the category "Other Conflicts." Likewise, crash types not correspond ing to the twelve designated types are also listed as "Other Crashes." Other events were also observed during data collection that were not spec ifically traffic conflicts but just reoccurring in nature (e.g., U-turns and traffic cutting through corner gas stations and convenient stores). Observers were instructed to record these events individually under "Recurring{Special Events." However, these recur ring/special events recorded only for informational p urposes, were not used in developing ratios for "other" crashes to "other" conflicts due to their variability and inconsistencies. Twenty categories for this data were established following their documentation (this listing is included on the database index sheet in the Appendix C). 18

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V. ANALYSIS OF CRASH REPORTS A. Intersection Related Crashes There was no unique definition to "intersection-related crash" between counties and FOOT. For consistency in obtaining c ra sh reports from d ifferent agenc i es and analyzing crash reports, CUTR defined this term as meaning crashes withi n 100 feet of the intersection Th is dis t ance also corresponds to the instructions given to observers for record i n g of conflicts on the near-side and far-side of i ntersectio n approaches. B. Crash Report Screening Crash data from county databases (SCARS Seminole County Accident Report System, TARSTraff ic Accident Report System) for t he most recent three -y ear period (1994, 1993, 1992) was requested for each of the 156 originally sampled intersecti ons (178 total with 22 of the 156 being re-sampled). Crashes were recorded by type, correspo n d ing to conflict types as discussed late r in t his section, and excluded crashes occurring at night and early morning {from 6pm to 7am). o n Fridays and weekends, involving wet pavements, not intersection-related, and involving crashing into fixed objects, pedestrians, and cyclists. Th is screening was essential and is cons istent with the criterion of the national t ables. To avoid unusua l conflict counts due to changes in holiday t raffic at di fferent i ntersections, crashes occurring on national holidays (21 national holidays over the 3-yea r period) were also screened out. Using the information on direction, movement, locati o n and contributing causes of the crash reports, each crash was then classified to correlate with the corresponding twelve conflict types observed. The selected crashes were included in the main data base. About 31 5% of the total number of crashes were used for this analysis {following the "screening" process) in the five -county area 1 9

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An overall database (in Appendix C) was developed to include conflict counts and crash data of every sampled intersection. For each intersection, the database also included county, intersection street types (I.e., local, state, or federal). intersection type, observation period \am or pm). physical information \e.g. curb and gutter, pavement striping, right and left turn lanes etc.}. amount of out of state/county plates, truck volume and traffic volume (a subjective observation of "low", "medium", and "high"). C. Problems Encountered and Remedies Utilized During the crash report analysis period, several problems were encountered that had to be remedied to complete the crash analysis. These problems, not listed in the order of importance, are documented below. a. Since Hillsborough County does not utilize the SCARS crash software for reporting, CUTR had to rely on the Hillsborough County Sheriffs Office to provided the required customized crash summary information for the 50 intersections randomly selected in Hillsborough County. CUTR did not receive this 3year file from the Sheriffs Office until August 23, 1995 and it could not be screened by the Sheriffs Office data management staff to include only the 50 intersections of concern. Therefore, this massive database (approximately 25 megabytes) was screened by CUTR for further analysis, and selected only the crash reports required at the 50 intersections. b. Also, upon inspection of the Manatee County crash summary reports provided by the County, it was found that no crashes were recorded for a 5-month period in 1992 and 1993. This omission was rectified by the County, and the expanded crash reports were screened as before. c. In two crash reports from Hillsborough County, there was conflicting Information on movements (before the crashes) of the vehicles involved 20

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in the crashes and/or traffic signal phase (red, yellow or green). Therefore, the vehicle with the right of way and the resulting conflict type were difficult to determine. Since the conflict type could not be accurately determined, these crashes were removed from the analysis. d. At signalized intersections, some crashes had occurred when a through vehicle ran on red while the opposing left turn traffic had a green arrow. Since there was no corresponding conflict type, these crashes were listed as other crash type.' e. While analyzing crash reports, two intersections in Hillsborough County, were noted to have recently undergone capacity improvements (from unslgnalized to signalized). Because of these recent capacity improvements, the two intersections were removed from further analysis. VI. ANALYSIS OF CONFLICT AND CRASH DATA A. Analysis of Conflict Data The conflict data. once it had been collected according to the procedures described in pages 12-13, had to be compiled to make it suitable for analysis and interpretation. This section deals with preparing the data for analysis and giving guidelines to identifying intersections with unusually high conflict counts. Identification of Abnormally High Conflict Counts Background The data presented in the Florida Conflict Tables is the result of a research project that encompassed gathering conflict observations for 178 intersections within a five-21

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county region of Florida. Conflicts were observed for each of thirteen conflict types. These counts were then combined into two more categories (fifteen total conflict types). same-direction conflicts (summ ing counts from conflict types one through four ) and through-cross-traffic (summing count from conflict types seven and ten) Once these 2,670 (1 78 intersection x 15 conflict types) conflict values were found they were combined according to the inte r secti o n type from which they were sampled. The intersection types were classified based on t hree cha racteristics as described earlier: number of le gs (3 or 4). signalization (signalized or unsigna l ized), an d laneage (2x2, 2x4, etc.). The in tersec t ions were then analyzed within the i ntersect ion grou p i ngs. For each inte r section grouping, values for the mean and variance of the conflicts were obtained f or each conflict type. These values were t hen used in con junction with the Gamma p r obab i lity d istribution (as develo pe d by the national [ Kansas City-based) study and con firmed in this study) to determine t he 90th and 95th pe rcenti les of the conflict d is t ributions. Calculation of 90th and 95th Percentiles of Conflicts The 90th and 95th percen t i l es of conflicts for t he tables listed in Appendix 0 were calculated as follows. The 90th percenti l e (C90J for the conflict data is found using the following form ula: C90 = X9o' I A where, X9,> is the 90th percentile of the chi-squared distribution with v ( = (2 x mean2)/va riance) d egr ee s of freedom A = 2 x (mean/variance) 22

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Note : Example: Calculations of all similarly grouped conflicts and intersection types yield the conflict means and variances shown in the conflict tables. These values are used in the above calculations Assume that we are interested in finding the 90th percentile for t h e number of right-turn same direction conflicts observed at a signalized 4 legged 2x2 intersection (classif ied as S4Al. From table 0.1, we find: Therefore, mean = 16.82 variance=210.76 V = (2 X 16.822 ) /210.76 = 2 .685 A = 2 X (16.82 /21 0. 76) = 0.1596 Using a computer package, we find X902 = 5.74745 The 90th percentile for the conflict amounts is C90 = 5. 74745/0.1596 = 36.01 The 95th percentile (C95l for the conflict data is found using the following formula: Note: Cos = Xos2 I A where. X9.' is the 95th percentile of the chi-squared distribution with v [ = (2 x mean2)/variance] degrees of freedom A = 2 x (mean/variance) Calculations of all similarly grouped conflicts and intersection types yield the conflict means and variances shown in the conflict tables. These values are used in the above calculations. 23

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Example: Assume we are interested in finding the 95th percentile for the number of right-turn same direction conflicts observed a t a signalized 4-legged 2x2 intersection (classified as S4A). From table D. 1, we find: Therefore, mean = 16.82 variance= 210.76 V = (2 X 16.822 ) /210.76 = 2.685 A= 2x(16.82/210.76) = 0.1596 Using a computer package, we find X952 = 7.25922 The 95th percentile for the conflict amounts is c = 7.25922 /0.1596 = 45.48 Tables 0.1-0.15 in Appendix D report mean, variance, 90th and 95th percenti les for the 4-hour conflict observation period (with 2 hours per leg) for each conflict type for the fifteen different intersection types. Using the Florida Conflict Tables The first step in using the tables provided is to classify the subject intersection according to the number of legs, signalization, and laneage. Use the sampling procedures described earlier in thi s report to sample conflict counts from the subject in tersection and compute the total counts for the conflicts observed at ali of the intersection legs. Compare these total counts with the Florida Conflict Counts foun d i n the appropriate table (intersection type). If the conflict counts exceed the 90th and/or 95th percentile values given for the subject in t ersections type, this would be considered an abnormally high number of conflicts. 24

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A Word of Caution The data in the Flo r ida Conflict Tables are a result of the 178 intersections sampled in the five-county region of west-central Florida. The sampling was done according to the specifications set forth in pages 7-9. The data were collected on weekdays {Monday through Thursday). on dry pavement, and do not include secondary conflicts. When using the Florida Conflict Tables, the traffic safety analyst should make sure that the sampling procedures outlined in this document are followed precisely. Also, the data should be analyzed as described above to assure comparable results. B. Crash/Conflict Ratio Data Introduction In addition to analyzing the number of conflicts arising at the intersections sampled i n this study, the three-year (1992-1994) crash history for each intersection was also analy zed. This three-year crash history was researched to find the list of crashes that corresponded to our sampling procedure (i.e., Monday through Thursday, daytime, dry pavement crashes). These crashes were then classified according to the conflict types explained earlier. The result of the crash research was a listing of crashes caused by each of the thirteen conflict types for each of the 178 sampled intersections Before combining the crash data with the conflict data adjusting the conflict data to represent three years of weekday and non-ho l iday conflicts was necessary. Together, the crash and conflict data was then used to create a crash/conflict ratio for the thirteen conflict types for each intersection. Again, this data was sorted and analyzed by intersection type yielding the means and variances for the crash/conflict ratios of tables E.1-E.15 in Appendix E. Once the conflict counts have been observed, this data can be used to estimate crashes at a specific intersection. 25

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Using the Crash/Conflict Tables to Predict Crashes Crash/Conflict Rat i o tables (tables E.1-E.15 in Appendix El have been developed for each of the intersection types used in this report. These tables can be used to predict the yearly number of crashes at the intersection attributable to each of the conflict types. To generate these estimates, follow the five-step procedure detai led below: 1. Identify intersection grouping according to number of legs (three or four). signalization (signa l ized or unsignalized), and laneage (2x2, 2x4, etc ) 2. Observe conflict counts for the subject intersection following procedures detailed in pages 12-13 of this report. To find the total conflict count for each conflict type, add conflict counts for each conflict type during an observation period of two hours per intersection leg Th is total conflict count would equate to a 4-hour conflict count observation for each i ntersection 3. The estimate of the yearly (days including only Monday through Thursday, non holiday, and during daylight hours (7am to 6pm)) number of crashes for a particu la r conflict type is Yo = Conflict Count x Constant A where, Constant A = 201 x 5.5 x (mean of crash/conflict rati o). The value 201 is the number of non-holiday weekdays (Monday through Thursday) in a typical 365 dayyear (i.e., [365x4/7]-7 = 201). and value 5.5 is to extrapolate a two-hour count to an eleven -hou r day count. The Constant A can be obtained from tables E.1-E.15. 4 The variance associated with this estimate is Var (Y0 ) = Constant B + [(Conflict Count)2 x Constant C] 26

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where, Constant B = var(confl i ctJ x var(crashfconflict ratio}+ (mean of crashfconflict ratio}2 x var(conflict). Constants Band C can be obtained from tables E.1-E.15. 5 A 95th percentile rel iable estimate for the number of crashes caused by the specific conflict type is found using To illustrate with an example, we will assume t ha t we are o bs erving conflicts at an i ntersection t ha t is a signalized fourle gged 2x2 intersection (classified as S4AI. We also assume that 50 right turn same direction conflicts were observed during the total 4hour observation period Comparing this val ue to the 95th percentile of table D. 1 indicates that this would be most conflict to observe (since 50 > 45.49). Conflict Type Constant A Constant 8 Constant C 1. L eft-turn, Same direction 0 00751 0.28743 0 0 0062 2. S lo w vehicle, Same direction 0.02516 1.23874 0.00071 3. Lane change Same direction 0 .02066 0.00140 0 .00342 5. L eft-turn, Opposing direction 0.00728 0.01211 0 .00024 6 Lefttu r,...f rom-leh Cross traffic 0.00000 0 .00000 0.00000 7 Through, Cross traffi c from left 0 .01377 0.00140 0 .00152 8. R i ght-turn, C ros s traffic from left 0 .00000 0.00000 0 .00000 9. Left-tum, Cross traffic from right 0.00000 0 0 0000 0.00000 10. Through, Cross traffic from right 0.05510 0.00193 0.01822 11. Rightturn, Cross traffic from right 0 .00000 0. 00000 0 .00000 12. Right-turn on red, Opposing direction 0.00000 0 .00000 0 .00000 13 Conflicts o t her than 1 thro ugh 12 0 .03926 0.01739 0.00374 1 through 4, Same direction 0.00003 0.00001 0.00000 7 plus 10. Through, Cross traffic 0.00015 0.00000 0 .00000 Figure 1. (Table E 1) Florida-Based CrashfConflict Ratio for Intersect ion Type S4A 27

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The estimated yearly crashes of conflict type four are Yo = 50 X 0 .00801 = 0.4005 The variance associated with this estimate is Var(Y.) = 0.08567 + [502 x 0.00034] = 0.936 The 95th percentile reliable estimate for the yearly range of crash numbers caused by this specif i c conflict type is o.4oos :t 2 Jo.938 o.4oos 1.935 _. {-1.53,2.341 In this example v. is less than 2[Var(Y0)] ... Therefore. the range has a negative val ue. S i nce the number of crashes cannot be less than zero, the possible range of the crash numbers should be from 0 to 2. Therefore. the calculation estimates that zero to two right-turn same direction crashes most likely will occur (with a 95-percent confid ence) at the intersection during a one-year period. Even though this reflects crashes during a 201 -day year (Monday thr ough Thursday and from 7am to 6pm). this provides a basis for comparing intersection safety and operationa l prob l ems. VII COMPARISON OF FLORIDA TABLES AND NATIONAL TABLES Introduction The main emphasis of this project is to accomplish the following two objectives: 1. Create a set of conflict and crash/conflict ratio tables that are applicable to the intersections within the state of F l orida. 2 Create a set of tables that are relatively easy to use in practice. 28

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The f irst of these two objectives was considered when defining the five-county area from which the sampled Intersections were selected. A thorough discussion of the samp ling procedure used to accomplish this objective can be found in pages 7-9. A. Intersection Classifications As described earlier, the fifteen intersection classifications used in this study can be described using the following three variables: number of legs (three or four), signalization (signalized or unsignalized) and laneage (2x2, 2x4, 4x4, etc}. This classification technique was chosen to aid in ob ject ive number two listed above. The classification of an in tersection can be easily determined simply by examining the intersect io n that is to be studied Unlike the national (Kansas City-based) study, no daily volume counts need to be known in order to know which tables apply to a particular intersection. This enables easy use of the tables in c luded in this report. The intersection laneage was converted into da i ly traffic volumes just for comparison of the na t iona l and Florida-based tables. The first steP in conversion included a careful analysis of the adjacent land use (from Intersection sketches as discussed i n page 14) of each quadrant at the intersection. When every quadrant's (four in 4-leg and three in 3-leg intersections} land use was residential the intersection was classified as Group 1 (ne ighborhood or less than 10,000 daily approach volume). All the other intersections were grouped into either urban or rural depending on the location in each county/town and presence of curb and gutter (presence indicated intersection as urban). The FOOT Leve l -of-Service Manual and Highway Capacity Manual was then used to facilitate the conversion of laneage categories of urban and rural intersections into the equivalent volume categories. In tersect i ons in urban areas were assumed to be LOS-0 and intersect ions in rural areas were assu med to be LOS-C. The FOOT-LOS tab les provide average annual daily traffic (AAOT) volume for different roadway sections. This traffic volume information was used to estimate the total approach volume at intersections and group into corresponding traffic volume thresholds. For example, consider two intersecting state roads in an urban area. Let us assume that the inte rsec tion type is S4A (signa l ized 4-leg 2x2 laneage). The table 29

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E-1 (FOOT-LOS Standards Manual on page E1) lists AADT for one section of the state road as 11 600 vehicles per day. Therefore, approach volume at the intersection is twice that amount (2x11,600=23,200). This inte rsect ion can be classified as Group 2 (10,000-25,000 vehicles per day) intersection. Group 1 (2,500-10,000) Inc ludes all "neighborhood intersections" (e.g ., S4A, S3A, U4A, and U3A intersecti ons located within neighborhood areas); Group 2 (10,000-25,000) i nclude all intersections classified as S4A, S3A, U4A, and U3A; and Group 3 (greater than 25,000) include all intersections classified as S4B, S4C, S4D, S4E, S3B, S3C, S3D, U4B, U4C, U3B, and U3C. Table 3 shows the intersections sampled and group type by volume thresho lds. Table 3 Sampled Intersection Types and Intersection Volume Threshold Groups Intersection type Group 1 Group 2 Group 3 Total {2,500-1 0,000) (1 0,000-25 000) (> 25,000) S3A,S3B.S3C.S3D 3 10 33 46 U3A,U3B,U3C 8 4 26 38 S4A,S48,S4C,S4D,S4E 3 8 47 58 U4A,U4B,U4C 10 2 24 36 Total 24 24 130 178 B. Data Collection The manner i n which data at a particular intersection was collected was designed to minimize the expense and the use of f ie ld personnel. To study a particular i ntersection, each leg of the Intersection should be sampled for a two-hour period as described earlier. For three-leg intersections there shoul d be six hours of data collection. For four-leg intersections, eight hours of data should be collected (See pages 12-13 for more details concerning data collection of a particular intersection). Working i n two-person teams, the data necessary to study a specific intersection would require a maximum of four hours (i.e .. eight man-hours) to collect. This should allow specific intersections to be studied with a minimum of personnel and cost. 30

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C. Comparison of t he Florida and National Studies Variable Comparisons To satisfy both of the objectives listed above, it was determined to design a study that maxi mized the information that could be obtained while also maximizing the pra ctical usefulness of the results These two issues, obviously, conflict. The more complicated the design, the more information could be obtained while sacrificing the usefulness aspect. Conversely, a simple design t ha t was extremely easy to use would not provide the necessary information desired. It was here t hat the information contained in the national (Kansas Citybased) study was used to obtain guidelines as to what factors, or variables, affected conflicts. The national (Kansas City-based) study used the number of legs, signalization, and total daily volume of an intersection as the variables used to classify intersections Because this last variable is not eas ily available for all intersections, the Florida-based study used the number of through lanes for each roadway. I t was hoped that the ianeage variable used in the Florida-based study would substitute the dally volume variable of the national !Kansas City-based) study. Before recommending to use the laneage variable in practice, however, evaluating t he effectiveness of this variable is necessary. The conflict counts from the Florida intersection classifications were grouped according to intersection type and analyzed using standard Analysis of Variance (ANOVA) procedures. These procedures are defined in any introductory statistics text book. ANOVA procedures allow comparison of the conflicts after grouping the intersectio ns by the three classification variables (signalization, number of legs, and laneage). This enables one to determine statistically (i.e .. with a measure of confidence), which classification variables are necessary to use when classifying intersections. For instance, these analyses will determine if all three of these variables are necessary, or if using just number of leg s and signalization is sufficient for determining conflicts. I f using just number of legs and signalization is sufficient, 31

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then the laneage variable could be dropped from the analysis as it would not add significant information when determining conflict counts Obviously, if this were the case, the procedure would become much easier and the intersection groupings and analysis would simplify. The ANOVA procedures indicated (p < .05, i.e. within a 95 percent level of confidence) that the three intersection classification variables used were all significant variables when determining conflict counts at Florida intersections. The conclusion drawn from this result is that all three-intersection classification variables ( number of legs, signalization, and laneage) are necessary when trying to determine conflicts at Florida intersections. Specifically of interest, the laneage variable cannot be ignored when counting conflicts at Florida intersections. The next step in evaluating the laneage variable is to determine if conflict information is lost by eliminating the daily volume variable used in the national (Kansas City based) study. To accomplish this, within each Florida intersection type (consisting of the number of legs, signalization and laneage). the daily volumes were d e termined for each intersection as described on pages 29-30. The da ily volumes were t hen categorized us ing the three categories corresponding to the natio nal tables: 2,500-10,000, 10,000-25,000, and more than 25,000 vehicles per day. This data was again subjected to standard ANOV A procedures to determine if the newly created daily volume variable added information concerning conflict counts at Florida intersections. This analysis was performed for a ll fifteen intersection types and for each of the conflict types presented earlier. The analysis looked for statistical evidence to indicate that the daily volumes of t he i ntersections provided additional information about the number of conflicts at the intersection. Not once in all of the analyses studied did the daily volume variable contribute additional information for estimating conflicts a t Florida intersectio ns The practical result of this ana lysis is that the daily volume variable can be igno red when the signalization, number of legs, and laneage variables are used to type intersections in Florida conflict analysis. 32

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It was shown that the laneage variable is useful in determining the conflicts at Florida intersections. It was also shown that when the laneage variable is used, the daily volume of the intersection is not needed in the conflict analysis of an intersection. The conclusion drawn from this is that the laneage variab le used in the Florida-based study serves as a replacement for the daily volume variable used in the national (Kansas City-based) study. The added benefit is that the laneage variable is a much simpler variable to use in pract ice and should add to the ability to use the conflict and crash/conflict ratio tables. Data Comparisons To compare t he Florida and national studies, the intersec tions sampled in the Florida based study were reclassified using the techniques of t he national (Kansas City based) study. The results are shown in tables 4 7. Due to lack of adequate samples (less than 8 intersections) Group 2 unsignalized four-legged intersections were not compared. It is important to note that these conflict counts represent the total numbe r of conflicts for all the legs of the intersection adjusted for an eleven-hour day. (Note: Fo r uns ignal i zed i ntersec tions, the Florida data was changed to compare with the national {Kansas City-based) study. Data incl ude only those conflicts and crashes recorded on two-intersection (two-way stops) approach legs with right-of-way). The goal of this data comparison section was to determine what differences exist, if any, between the Florida and national data. There are two statist i cal procedures available to make broad conclusions of this type that will provide a measure of rel iab ility (i.e .. confidence Ieveil to the results. The first procedure involves using the sample summary information from the data (i.e., means, standard deviations, sample sizes. etc ) to make comparisons of the corresponding population information. The second procedure uses t he actual data corresponding to indiv idua l intersections and compares the data from one sample to that of the other. This comparison can yield results that make statements concerning the populations in question. Both of these procedures yield resu lts that can be quantified with a measure of reliability. 33

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The data from the Florida-based study can be used in both raw (individual observations) and summary (means, standard deviations, etc.) form. The data from the national (Kansas City-based) study, however, is available only in summary form. Any type of procedure, therefore. that requires individual observations cannot be used to compare the two studies. The only option to make the desired comparisons is to use the procedures that utilize the summary data that is available {conflict means and variances) from both the Florida and the nationa l (Kansas City-based) study. These procedures require an assumption about the populations that are being sampled from when the number of items (intersections) being sampled is small {n < 30, as in both studies). The assumption is that both populations sampled follow an approximate normal probability distribution (i.e., a bell-shaped curve). Unfortunately, the assumption that the conflict data follows a normal distribution is incorrect. I t is known that the conflict data does not follow a normal distribution. Therefore. this assumption is invalid and does not allow statistically significant comparisons to be made. The result of our fail ure to make the desired comparisons Is that no reliable compar iso ns can be made between the two studies. The only comparisons that can be made will lack the re liability component and should be used carefully. However, the following generalizations in the data presented in tables 4-7 are summarized below. (Caution: These generalizations have n o measure of reliability attached to them) The conflict types appear to have greater variation in the Florida-based study than in the national (Kansas City-based) study. The mean crash/conflict ratios that can be compared (table 7) indicate that these ratios are lower in the Florida-based study than in the national (Kansas City-based) study for all types of collisions compared. The variations associated with the crash/conflict ratios are lower for the Florida-based study than the national (Kansas City-based) study for all types of collisions compared. 34

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Table 4 Comparison of National and Flor ida Tables: Signalized, 4-Legged 10,000-25,000 Daily Volume (National table values shown in bold) Conflict Type Mean Variance Abnormally High Conflict Counts 90th Percentile 95th Percentile 1. l eft turn. Same d irection 63.25 9005.86 175.23 253.36 134.72 10298. 3 270.00 340.00 2. Slow vehi c le. Same direction 220.69 28603.00 445.96 551.27 377.94 4928.9 470.00 500.00 3. Lane change, Same d irection 0.00 0.00 . 7.62 52.80 17.00 22.00 4. Right-turn, Same d ire c t ion 74.94 3447.96 153.06 189.94 124.48 2445.10 190.00 220.00 5. left-turn, Opposing direction 44.69 1378.00 93.91 1 17.76 29.06 211.20 49.00 56.00 6. LefHurnfromleft, Cross traffic 1.38 6.48 4 .07 6.35 0.46 0.47 1.30 1.90 7. Throug h Cross traffic from left 2.06 34.03 5.91 1 1. 71 0.29 0.24 . 8 RighHum, C ross traffic from left 1.38 6.48 4.07 6.35 0.33 o. 19 0.80 1.10 9. L e ft turn, Cross traffic from right 4.81 47.00 13.06 18.58 0.52 0.13 1.00 1.2 10. Throug h C r oss traff i c from right 0 .69 3.78 1.97 3 .90 0.23 0.12 0.70 1.00 11. Right-turn. Cross traffic f rom right 34.38 689.27 69.35 85.68 3.71 2.84 6.00 7.00 12. R i ghttum on red, Oppos i ng direct i on 2.75 17.29 7.64 11.07 0.09 0.06 . 13. Conflicts other than 1 through 12 4 81 64.28 13.83 20.72 1 through 4, Same direction 358.88 78310.77 731.30 906.72 644.76 25338.40 860.00 930.00 7 p lus 10, Through, Cross traffic 2.75 34.57 8.31 13.83 0.52 0.22 1.1 1 1.40 Note : these conflict types are so rare that any number observed at an intersection should be considered abnormal. no collected data in the national tables 35

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Table 5 Comparison of National and Florida Tables: Signalized, 4-Legged, More than 25,000 Daily vo lu me (National table values shown in bold) Conflict Type Mean Varlaf)Ce Abnormally High Confli ct Counts 90th Percentile 95th Percentile 1. Left-tum, Same direction 5!.02 4224.09 13!.90 181.83 83.64 11613.70 265.00 360.00 2. Slow vehicle, Same d irection 229.83 16587.44 402.53 474.20 669.05 23994.70 870.0 940.00 3 Lane change, Same direction 38. 73 18. 21 2092.45 160.60 96.68 130.70 35.00 43.00 4. RighHurn, Same directio n 144.29 2856!.54 358.74 484.00 218.63 7687.50 470.00 510.00 5. Left -t urn, Opoos i ng d i rection 17.67 429.99 43.97 59.35 22.00 377.70 48.00 60.00 6 Left-turn from -left, Cross traffi c 0.59 10.83 0.39 2 .37 0.63 0.82 1.70 2.50 7 Through, C ross traffic from l ett 0.47 3 .72 0 .86 2 6 1 0.14 0.14 8. R ightt urn. Cross t raffi c from lef t 0.23 2.57 o .os 0.59 0.06 0.02 9 Leftt urn, Cross traffic from r ight 0.59 4 .25 1.39 3.40 0.42 0.26 1.10 1.40 10. Through, C r oss traffic f rom ri ght 0 .23 1.26 0.29 1.1 7 0.29 0.22 . 1 1 Right t urn, Cross traffic from right 13.81 456. 21 38.70 56.51 2 .60 2.27 4.60 5.40 1 2 Aight t urn on red, Opposing direction 4 .80 145.49 1 4 .32 26.12 0 .23 0.12 . 13. Conflicts other than 1 through 12 8.89 692.53 24.84 St.OS 1 t h rough 4 S a me direction 463.87 100851.23 888.62 1078.15 989.53 67198.40 1340.00 1460.00 7 plus 10, Through Cr oss t r aff i c 0 .70 4.76 1.90 4.07 0.43 0.34 1.10 1.50 Note: these conflict types are so rare that any number observed at an intersection should be considered abnormal. no collected data in the national tables 36

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Table 6 Comparison of National and Florida Tables: Unsignalized, 4-Legged, 2,500-10,000 Daily Volume (National table val ues shown in bold) Conflict Type Mean Variance Abnormally High Conflict Counts 90th Percen t i le 95th Percent ile 1 Left -turn, Same d irection 14.67 854.56 44.00 70.85 70.65 9648.20 110.00 130.00 2 Slow vehicle, Same direction 33.00 2548.56 92.10 134.00 101.86 9648.20 225.00 295.00 3. lane change, Same d irection 2.44 31 .09 7 .39 12.73 0.11 0.05 0 4 Right-tum. Same d irection 15.89 555.42 43.82 63.14 57.91 2197.30 120.00 160.00 5. Left-tur n, Opposing direction 4.89 101 .67 14.73 24.10 3.64 8.30 7 .50 9.00 6. left-t um-fromleft, C ross traffic 7.92 273.09 23.96 39.35 3.37 7 .79 7.00 9.00 7. Through, Cross traffic from left 0 61 3.36 1.69 3 .52 6.70 42.00 1.50 19.00 8 R i g hHurn, Cross traff i c from left 0.00 0 .00 0 0.57 0.83 --9. Leftturn, C r oss t r affic from right 2 .44 31.09 7 .39 12.73 4.99 72.70 16.00 23.00 10. Through. Cross traff i c from right 2.44 53.78 6.77 14.07 5 .23 11.60 10.00 12.00 11. R i ght turn. C ross traff i c from right 3 .67 37.81 1 0 .56 15.86 5.55 12.10 10.00 12.00 13. Conflicts other than 1 through 1 2 o .oo o .oo - 1 through 4, Same d i rection 66.00 9710.25 182.50 263.47 230.52 17929.20 410.00 490.00 7 p 1us 10, Through, Cross traf f i c 3 .06 84.03 8.46 17.59 1 1.93 75.20 24.00 29.00 Note: these conflict types are so rare that any number observed at an intersection shou l d be considered abnormal. no collected data in the nationa l tab l es 37

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Tab le 7 Comparison of Crash/Conflict Ratios for National and Florida Tables (National table values shown in bold) TVPe of Collision Total Daily Number of Mean Stand ard V olume Intersections Cras h / Conflict Deviation Ratio Same Direct ion > 25,000 47 0.088x10 0.091x10'8 12 1 .428x 1o 1.SOOx1o Same Direction 10.000 2 5,000 8 0.031x 1 o o .039x1o 14 2.663x1o 3 703x1a Opposing Left-Turn > 25.000 3 7 235.872x10'' 292.372x 1 12 671.087x1a Opposing LeftTurn 1 0 ,000 25,000 7 9.409x10 .. 16.272x10 .. 14 184.906x1o 187 .500x1a VIII. SUMMARY OF FINDINGS During t he traffic conflict study, CUTR has reached the following find ings. 1 The five -c o unty area (Hillsb orough, Manatee Pasco, Polk, and Sarasota) adequately represents t he conditions of Flor i da intersections 2. Traffic confl icts were classified in to 12 basic t ra f f ic conflict types and "other events" conflict type. Of these, same direction conflicts are the most common despite the i ntersection tYPe (i.e., whether signalized or not, number of l egs 3/4, or la nea ge). This f inding is i n accordance with the nationa l tables. 3. Cross traffi c confli cts at signalized inte rsecti ons can occur o n ly if a driver violat es t h e red light. Therefore, cross traffic conflicts at unsigna l ized intersections occur much more frequently than at s ig nali zed intersections 4. Since only the "reported" intersection related crashes were used in developing the Flor ida-based tables, the number of act ual crashes may be highe r than what is estimated from tables. 38

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5 "Intersection related" crashes are best defined as crashes that occur within the intersection itself and within an area up to 1 00-feet away from the intersection on each l eg. 6. An estimate of the expected number of crashes of a specific type and for a specific intersection type can now be computed from data gathered in a field study. The expected number of crashes ID.l is given by the multiplication of conflict rate (C.) and crash/conflict ratio IR.l D C R 7. Statistical tests performed on the collected conflict data shows that l aneage at intersections can effectively be substituted for approach volume thresholds. 8. The conflict types appear to have greater variation in the Florida-based study than in the national {Kansas City-based} study. The following variations were observed during the comparison. The mean crash/conflict rat i os that can be compared (Table 7) indicate that these ratio s are lower in the Florida-based study than in the national !Kansas City-based) study for all types of collisions compared. The var ia tions associated with the crash/conf lict ratios are lower for the Florida-based study than the national (Kansas City-based) study for all types of collisions compared 9. The rate of traffic conflicts can be used to provide measu r es of safety effectiveness only for the specific conflict types and intersection categories menti oned in this report. 1 0. The conflict and crash estimates are valid for weekday {Monday through Thursday and excluding any national holidays} from 7am to 6pm under dry pavement conditions 39

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11. If the 4-hour conflict count at an Intersection exceeds the 90th (or 95th) percentile values given in tables 0.1 through 0.15, it should be interpreted that the intersection has an unusual safety (or operational) problem. IX. RECOMMENDATIONS Based on the research findings of this study, CUTR recommends traffic safety analysts to estimate the expected crashes for Intersec tions in F lorida using the Florida-based tables. Traffic conflict surveys should be performed according to the procedures described in the FHWA reports (Bibliography 2 and 3) and this report. However, the applicability and accuracy of these tables should be further investigated for other urban and ru ral areas/counties both insi de and outside t he five-county study area. The applicability of the Florida-based tables during the tourist season (November through April) should also be investigated for any abnormal deviations of the developed conflict and crash/conflict ratio. CUTR also recommends investigating the conflict and crash/conflict r elationship during t imes when d r ivers are in a "non typical environment" (e.g., wet pavement conditions, nighttime, weekend, and holidays). Finally, given the robust data base (Appendix Cl of surveyed intersection characteristics, additional cross-relevances can be developed (For example, an examination of crash/conflict ra tios for protected left t urn 2x4 intersection). 40

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BIBLIOGRAPHY 1. Crowe, E. C., "Traffi c Conflict Values for Three-leg Unsignalized Intersections," Transportation Research Record 1287, TRB, National Research Council, Washington, D.C.,1990, pp. 185-194. 2. Par ker, M R., Jr., and Zegeer, C.V., "Traffic Conflict Techniques for Safety and OperationsEngi neer's Guide." FHWA-IP-88-026, FHWA, U .S. Departmen t of Transportation, Washington, D.C., January 1989. 3 Parker, M. R .. Jr., and Zegeer, C.V., "Traffic Conflict Techniques for Safety and Operations Observer's Man u al." FHWA-IP-88-027, FHWA, U .S. Department of Transportation Washington, D.C., January 1989. 4. Perkins, S.R., "GMR Traffic Conflic t s TechniqueProcedures Manual." General Motors Research Lab oratories, Warren, Mich., August 1969. 5. Florida Department of Commerce and Bureau of Economic Analysis, Florida Visitor Study 1994," Tallahassee, Florida, 1994. 6. Florida Department of T ranspor tation "Florida Highway System Plan, Le vel of Service Manuai,''Tallahassee. Florida, April 12. 1992. 7. Cen t er for Urban Transportation Research, "Florida Demographics and Journey to Work," A County Data Book, May 1993. 4 1

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Append i x A Compa r iso n of the Five -county Area w i th the State of Flor i da 42

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I 0 Urban Rura l 100 90 8 0 c 70 0 ;:; J!2 60 :> "' &. 50 0 -40 c " 30 cf 2 0 1 0 0 !: 0 .>< .. >'" ;f -""' 0> g -"' :> --.. c .. .. .. 0 c .. :> .. 0 .. .0 ::: " "' "' -"' -0 .. !!l: 0 .. 1:. 0 e .. 0 .. > .. .0 ::; "' <( U<( "' x -.. -"'< "' F igure A 2 Per Capita Income ( 1992) Comparison ( F lorid a Statis tical Abstracts) 44

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90 80 70 60 "' 50 E " 40 cl: 30 20 10 0 0 "' <.> 0 .. if. 0 .. .0 ::l: !!! 'f .. 0 "' !! .. .. > .. <( (I) ., ... " -"' c " 0 > U<( '""' Q> "-< D 0 -14years I 1 5 24 years 0 25 44 years 45 64 years a 65 yeats and over 1m 1 8 yeacs a n d over Fig u re A.3 Age Distribution Comparison (1993 Estimated Data, Florida Statistical Abstracts} 45

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I Ma l a 0 Female J 54 53 52 51 so '" 49 -c 4a u -" ... 4 7 4 5 45 44 43 "' 0 0 0> 0 u - 0 G -e ... 0 :; :;: 0 ,.o -" 0 -G - e -. - - ; o!! "' < U< o, > 0 u::;c Figure A. 4 Populat ion Gender Comparison (1993 Est imated Data, F l orida Statistical A bstr ac t s ) 46

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60 Higher Educat ion 0 Ernpl oymant 50 40 0> .. c 30 .. <.> -.. 0.. 20 10 0 ""' .. "' .. -"' 0 c -.& "' ::;; !!} :;: 0 "' .. >" <.> -0 0 -"' 0.. -.. c"' "' "' -" :;; 0.. -.. -"'> 0 > "'
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80 7 0 80 50 c v :f 40 30 20 10 0 8 g c :,; D f f .. - - -,.. cf > ii:< Cl Drive ;slono 11 Carpool PUb lic trsnsport 0 Othet tnNt'IS 111 Wal k.cf/Worked at l'lorM Figure A. 6 Transportation to Work Comparison (Workers over age 16) (1990 Data, F l o r ida Statistical Abstracts) 48

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! Lhone 1112 03 4 o r more 50 40 -= 2 30 20 1 0 0 0 0 >" "' u 0 -"' -0 -"' = 0 .. " = .. 0 g .& > ::!! "' U<: "' !!!. :;: -0 !! "' F igure A 7 V ehicles p e r Household Comparison {1990 Census Datal 4 9

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Appendix B. Distribution of Surveyed Intersections in Five-county Area 50

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.. . Surveyed Intersection Locations 0 1 0 20 Miles Legend County Bolmd;3ryl Roads Intersect i on !lDD Urbanized Area 51

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Hillsborough County Surveyed Intersections " .-, ., 52 ,, N Legend Roads Intersection r lllllllllll Urbanized Area

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INDIVIDUAL INJEBSECDQNS SAMPLED FROM HILLSBOROUGH COUNTY Map Database Intersection At Type # List# 1 397 41 Hw & Crenshaw Leke Rd. S4A 2 219 Harnev Rd. & Sligh Ave. S4A 3 204 50th St. & Palm River Rd. S4B 4 17 56th St. & Sligh Ave. S4B 5 150 60 HW & 78th St. S4B 6 280 Hillsborough Ave. & Hoover Blvd. S4B 7 50 Dale Mabry Hw. & Humphrey St. S4C 8 761 Dale Mabry Hwy & N. Vlg Dr. S4C 9 158 Hillsborough Ave. & George Rd. S4C 10 94 Hillsborough Ave. & Webb Rd. S4C 11 85 39HW& 60HW S4D 12 67 50th St. & causeway Blvd. S4E 13 10 Bruce B. Downs Blvd & Fletcher Ave. S4E 14 54 Dale Mabry Hw & Ehrl ich Rd. S4E 15 322 Dale Mabry Hw. & N. Lekeview Dr. S4E 16 5 Dale Mabry Hw. & Waters Ave. S4E 17 8 Hillsborough Ave.&. Memorial HW S4E 18 258 301 HW &. Fowler Ave. S3A 19 400 60th St. & Port Sutton Rd. S3A 20 136 Casey Rd. & Gunn HW S3B 21 161 Kelly Rd. & Memorial HW S3B 22 115 Ehrlich Rd. & Turner Rd. S3B 23 228 301 HW & Balm Riverview Rd. S3C 24 106 Hillsborough Ave. & Kelly Rd. S3C ?0 QO A"A R. "" ,,,.. 53

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INTERSECDQNS SAMPLED ffiOM H IL L S BOROUGH COUNTY (Continued! Map D at abase In tersectio n At Type # List# 26 346 41 HW & Apollo Beach Blvd. S3D 27 264 56th St. & Fletc h er Ave. S3D 28 2256 Gunn Hwy. & Himes Ave. S3D 29 1438 36th Ave & Mavdell Dr. U4A 30 2646 Pebble Croek Dr. & Regents Park Dr U4A 31 654 Valrico Rd. & Wheeler Rd. U4A 32 c 20th St. & E Fletcher Ave. V4B 33 566 60 Hwy & Smith Ryals Rd. V4B 34 d Fletche r Ave. E & 19th St. V4B 35 125 60 HW & Moon Ave. V4C 36 a Dale Mabry Hw. & Hamilton Ave. V 4C 3 7 b Dale Mabry Hw. & S lig h Ave. V4C 38 732 Bloomingdale Ave. & Holland D r U3A 39 1674 Armo r Dr & Holloway Rd. U3A 40 1929 Clwd Meadows Dr & Ridge Stone Or. U3A 41 909 41 Hwv & Pembroke Rd. U3B 42 782 Fletche r Ave. & R esed a Ct. U3B )4 Ok Trace Wv & AvA II 54

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Ul c i ., 0 . .., 0 Q) ('! Q) -c "i \ >. Q) <:: :::l (/J i!' c :::l 0 (.) Q) Q) "' c: "' ::E "' !!! c < .Q .., -Q) .., II) !:l c .., 55

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INTERSECTIONS SAMpt..EO FROM MANAm COUNTY Map Database Node II Intersection At Type # L ist# 44 182 18710 9th Ave. W & 26th St. W S4A 45 430 15493 9th Ave. W & 39th St. W 54 A 46 24 762 51st St. W. & SR 684 (44th Ave WI S48 47 9 493 9th St. E & Oneco Rd. 153rd Ave. El S48 48 102 522 US 301 & CR 683 (Ell e nton Gillette Rd) S4B 49 246 1734 30th Ave. E. & US 301 ISR 683) S4B 50 31 889 9th St. E. & 301 Blvd. S48 51 75 1427 49th St. E !Experimental Farm Rd) & US 41 S4C 52 46 912 69th Ave W & U$41 ISR 45) S4C 53 83 1 18 4 43rd St. W & SR 6 4 (Manatee Ave.) S4C 54 20 927 Orlando Ave & US 41 ISR 45) S4C 55 44 1215 301 B l vd. & US 41 (1st St.) S4D 56 29 1165 75m St W & SR 64 (Manatee Ave ) S4E 57 4 770 26th St W & SR 684 !44th Ave. WJ S4E 58 8 917 8avsho r e Gardens Pkv & 14m St. w IUS 41 1 S4E 59 225 1078 SR 684 !Cortez Rd.) & SR 789 !Gulf Rd. ) 53A 60 313 9553 Palm Dr. (Mar in a Dr ) & Gulf Dr. S3A 61 126 642 57th St. E & SR 64 (Braden ton Harcadia Rd.) S3B 62 274 831 60th Ave E & US 301 (SR 43) S3C 63 330 US 41 (14m St. Wl & Florida Bl v d. S3C 64 1237 19560 18m Ave. w. & 39m St. w. U4A 65 1204 15808 18th St. W. & 48th Ave w. U4A 66 602 16133 26th Ave. W. & 5 1st St. W. U4A 67 350 15907 2 1st Ave W. & 34th St. W. U4A I
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INTERSECTIONS SAMPlED FROM MANAUE CoUNTY (Continued! Map Database Node II Intersection At Two # List# 69 244 1193 32nd St. W. & SR 64 (Manatee Ave.! U4B 70 272 1774 10th St. W. & US 41 Bus (8th Ave. Wl U4B 71 825 1292 50th St. W & US 19 (SR 551 U4B 72 185 1773 26th Ave. W & US 41 Bus (14th Ave. WI U4B 73 a 941 1st St IUS 411 & 32nd Ave. E. U4C 74 1880 40473 Holmes Blvd. (HBl & SR 789 U3A 75 1201 30649 13th St. W. & 13th Ave. W. U3A 76 1130 31156 27th St. E. & 30th Ave. E. U3A 77 160 1411 21st St. W & US 41 Bus U3B 78 593 31953 Bayshore Gardens Pkwv & Columbia Dr U3B 79 577 31024 26th St. W. & 52nd Ave. Ter. W. U3B 80 661 739 99th St. W & SR 684 (Cortez Rdl U3B 81 547 957 10th Ave. W. & U .S. 41 Bus U3B R? 11Q7 '"' w .. "4 b.v6 I 57

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::... l J ... SLI . .' , <.If" -Ifill( z ... .. .: .. ' '10!' '' ' .. - .. OS "l .. !!! c < N 0 "0 Q) N "' -"' "0 c: "0 c: "' OS Q) Q) .0 0 c: Ol a: :::::> -Q) ..J I I

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INJERSECDQNS SAMPLED FR O M PASCO COUNTY Map Datab ase Node# Intersection At Type # List# 83 78 10163 Plathe Rd. & CR 77 (Rowan Rd.) S4A 84 85 10311 SR 54 & Coatos Rd. S4A 85 54 10043 Hol ida y La k e Dr & ALT 1 9 S4A 86 485 10562 US 1 9 & Bonita O r. S4C 87 17 6000 US 19 & CR 518 (Trouble Creek Rd. ) S4C 88 2 6003 US 19 & Main St. NPR S4E 89 89 10206 R i dge Rd. & Bass Lake Or S3A 90 726 10874 Fairfax Or. & CR 77 ( Regency Park Blvd.) U4A 91 153 60091 US 19 & Palmetto Rd. NPR U4C 92 64 10511 US 19 & Bartelt Rd. U4C 93 1244 10287 Sugar Creek Blvd & Knoll Brook L n. U3A 94 176 10007 SR 52 & Pine Forest Dr U3A 95 169 10390 Moon Lake Rd. & Lacey Or. U3A 96 1098 10959 Mahogany Dr. & Colony Rd. U3A 97 770 10930 Parkway Blvd. & Geneva Rd. U3A 98 1 1 9 10236 US 19 & Bougenvlll e Dr. U3C 99 135 10444 US 19 & Bolton Ave. U3C 100 158 10134 US 19 & Coventry Dr. U3C 101 895 11097 US 19 & Edna Avo U3C 102 1456 11174 US 19 & Oak ley Ave U3C 103 83 70005 Washington St. & US 19 U3C 104 146 101A? IJ 1 !'I II. I nui< AvA LJ3r. 59

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.. l "' !!! c Q -o Q) -o <.:> .!::! (/) CD c -o "' c: Q) "' "' 01 0 CD -e Q) ....1 a: ..5 ::::> 60

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INJEBSECDQNS SAMPLED ffiOM POLK COUNTY Map Database Node If fntefsect:ion At Type II List# 105 69 548 SR 37 & Parker St. S4A 106 150 5003 CountY Line Rd. & US 92 (Ne w Tampa HW) S4A 107 51 477 Chestnut Rd. & Memorial Blvd. S4B 108 126 1534 US 27 & Polk CitY Rd. S48 109 15 342 SR 37 & SR 60 S4D 110 148 2185 S i kes Blvd. & lime St. W (C i ty) S4D 1 1 1 87 799 I ngraham Ave N & E Main St. S4D 112 85 712 Hollingsworth Rd. & Bartow HW (Bartow Rdl S4D 113 9 186 US 27 & Waverly Rd. (Cypress Gardens Rd. ) S4D 114 144 1998 Combee Rd. & Skyv iew Dr. S3A 115 1501 3384 Polk CountY Pkwy & CR 378 S3A 116 27 383 SR 37 & Pablo St. (CitY! S38 1 17 33 404 SR 37 & Belmar St. E S38 118 32 401 SR 37 & Ariana St. S38 119 1094 1692 Edgewood Dr. & CR 376 S3D 120 883 1274 Bortow Rd. (US 98) & Edgewood Dr. S3D ,, A4 I QA A. Rn ll4R 61

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Sarasota County Surveyed Intersections Legend Roads I nte r sect i on J I DI!IIII Urbanized Area 62 CR 7 80 SR72 .. : US41

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INTERSECTIONS SAMPLED FROM SARASOTA COUNTY Map Database Node# Intersection At Type # Li s t II 122 60 ,.. I Rd. & Blvd. 54 A 123 142 116 Bus41 &C r Rd. S4A 124 74 US41&r Rd. S4B _1_25 4 1 60120 S4C 126 19 711 I Rd. & Rd. S4D -127 10 801 1 Rd. & I Vista St. S4D 128 77 60716 Rd. & Jacaranda 129 9 60389 Proctor Rd. & Sw ift Rd. 130 18 21 0 Rd. & US 41 S4D 131 6 60113 Bee Rd. & Swift Rd. (Tuttle AvA I 132 132 67974 Pky & I 133 183 477 Pass Rd. & Beach Rd. S3A 134 45 703 Beneva Rd. & Gulf Gate Dr. S3B 135 135 8001 Rd. (SR 776) & Jacaranda Blvd. S3B 136 208 60025 17th St. & Long Meadow Dr. S3B m 448 60119 Bee 'Rd. & '"'' Ave S3C 138 85 I Rd. & I S3C _139 157 Rd. & 17th S t S3D 140 141 364 us 41 Blvd. S3D 141 1065 ... Olive Av e. & 1 St. U4A 142 206 Rd. & ._., Blvd. U4A 143 700 Gull Gate Dr. & 1 Cir. U4A 144 631 'Vista & Brink Ave. U4B 145 191 177 us 41 & 1 Dr !1st St ) U4 B l..w. 144 rSt.&t' n. '" 63

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INIEBSECDONS SAMPLED EBPM SARASOTA COUNTY !Continued) Map Database Node# lntecsection At Type II list I 147 50 60104 Bee Ridge Rd. & School Ave. U4C 148 1084 66906 Longhorn Or. & Mesa Way U3A 149 490 60076 Bahia Vista St & Bahia Vista Ct. U3B 150 380 225 US 41 & Buccaneer Dr U3B 151 350 60255 Gulf Gate O r & Superior Ave. U3B 152 76 60126 Be Ridgo Rd. & Maceachen Blvd. U3C 153 117 60127 Boo Ridge Rd. & Rivera O r. U3C 154 399 600 Fruitville Rd. & Bailey Rd. U3C 155 143 60137 Bee Ridge Rd. & Strathmore Blvd. U3C 156 202 JlW.36 A Rd. & Rf.,A "'r 64

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Appendix C. Data Base for Conflict and Crash Data 65

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Index for Database No = intersection survey serial number Co = countv of the intersection 1: Hillsborough County 4: Polk County 2: Manatee CountY 5: Sarasota County 3: Pasco County LIST = intersection list number INT = interse ction type DT = survey date. in the order of month and day TM = surv ey team number ST = intersection street type 1 : loca l local 2: state state GP = intersection group type according to its traffic volume 3: local state 1: AAOT < 10,000 vpd 2: AADT 10,000-25,000 vpd 3 : AAOT > 25,000 vpd CF = conflict numbers for type 1 to 1 2. other conflicts, and total conflicts OB = observation period 1 : in the morning 2: in th e afternoon AF = acc i dent numbers for type 1 to 1 2 other accidents. and total accidents PV = presence of pavement striping. 1: yes 2: no CG = presence of curb and gutter 1: yes 2: no CS = estimation of percentage level of outof-state/county vehicle license plates for the survey period 1 : low 2: average 3: high TK = estimation of truck volume for the survey period. 1 : low 2: average 3: high TR = esti mation of traffic volume for the survey period 1: low 2: average 3: high RT = presence of right-turn lane 1: none 2: some approaches 3: all approaches 66

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L T = presence of leftturn lane 1: none 01 = presence of divided lanes 1: none 2: some approaches 3: all approaches 2: some approaches 3: all approaches RE = reoccurring and special event during observation 1: by-pass through gas station/convince store 2: slow vehicles due to a close in tersect ion 3: right turn on red 4: slow vehicles due to office/factory/parking lot/gas station/convince store 5: slow vehicles due to bump/dip/construction and maintenance 6: Uturn vehicles 7: traffic accidents during observation 8: vehicles running on red ligh t 9: through traffic using rightturn lane 1 0: short lefttur n lane 11 : railway c lose to intersect ion 1 2: heavy school bus traffic 13: Four lanes changed to two lanes beyond intersectio n 14: slow vehicles due to truck/bike/emergency vehicle 15: rain during observation ( < 30 min.! 16: right-turn vehicles using bike lane 17: rain during observation (30 min.) 18: many pedestrians crossing intersection 19: one lane closed dur ing observation 20: view blocked for leftturn la ne during observation 67

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0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 a ... 0 0 ... .-.-0 N 0 0 0 0 N 0 0 0 ... N N 0 0 0 N 0 0 0 0 0 0 0 ... 0 0 .-0 0 ... N N N N N N N n N N N N N n N N N N 0 0 N N N n 0 0 n n ... n n 0 0 0 :r -0 0 0 -.. 00 -0 0 0 0 o N .-... ..-0 N N N n M 0 N 0 .-0 0 0 0 0 0 0 0 0 M -M N M --------P .-.-.N N f'll ."" ----8 -... ------..-... ... N ... N ... -... N .N ... N - ---...-.-..P ... ... -... .-.... ... N N N N 0 .-0 0 -N 0 n n N 0 0 .-0 0 0 --N ... ... n n o o n -N 0 0 0 0 0 .-0 0 0 0 .-.-... 0 .0 0 0 0 0 0 0 0 N 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 o 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 .-0 .-0 0 0 N N 0 0 .-.-0 0 .-0 0 0 0 0 .-0 N 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 u 0 ... o o N o n n o o o ... 0 0 .-0 0 0 0 0 0 N 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ... 0 0 0 N 0 0 0 0 0 0 .-0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 o o N o o o o o o o o o o ... n o o o o o o o o o ... o o o o o o o o o o o o o o o o o o 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 '! ... ,.. "f N 0 0 (>I N 0 0 0 M 0 .,. .,. 0 0 N 0 0 N 0 0 N ... 0 0 0 0 0 0 0 0 0 ... 0 0 0 ... 0 0 0 ... -... 0 0 0 0 0 () 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 'l 0 0 .-0 (>I 0 ,. 0 0 N ,. .-,. 0 0 0 0 0 0 0 0 0 0 .-0 0 0 0 ,. 0 0 0 0 0 0 0 0 -!:! :: 0 ... 0 (\I .-0 0 0 N M 0 0 0 0 0 0 0 0 0 0 0 0 ,. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 N 0 0 0 0 0 0 0 0 0 0 Q N ... ,. .-... N N N N N ,. N N ,. N N N N N N N N N N ,. N N N N ... .-N N ,. N .. ,. ,. s ; 0 0 0 0 0 0 1 0 0 0 0 0 0 l) 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 N 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 : o .. o o o n ... n .. --N e o ... o o o .. o o o o M 0 0 g 0 0 0 0 0 0 0 0 0 N 0 0 0 N 0 0 0 0 0 0 0 0 0 0 N 0 0 0 0 0 0 0 0 0 0 .-0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0 0 0 0 0 ll 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 l) o o o o o o N o o o o o o o o o o o o o o o n o o o o o o o o o o o o o o o o ... o o 0 0 0 .. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 (\1 n o o .o n o o o o o o o 6 0 0 0 g ft 0 0 N ft M ... M n n n n N n N M M M M M N n n ... .. n .. n M M n .. -t; ... n ... ----" --.. .. -... ... -... ---71

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Appendix D. Expected Conflict Value Tables for Florida-based Intersections 72

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Notes on tables: Intersectio n Categories : [S ignalized /Unsignalized J. [4-legged/3-legged (or 'T')] [Through Laneage: 2x2, 2x4, 2x6, 4x4, 4x61 The conflict counts were obtained dur i ng a 4-hour observation period on a weekday (Monday through Thursday excluding holidays) between 7am to 6pm under dry pavement conditions. These counts do not include secondary conflicts. Blanks (-) indicate that these conflict types are so rare that any number observed at an intersection should be considered abnormal. 73

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Table 0.1 Florida-Based Conflict Table For Signalized, 4-legged. 2x2 Intersections Conflict Type Mean Variance Abnormally High Conflict Counts 90th Percentile 95th Percentile 1. Same direction 14.09 424.29 38.64 55.42 2. Slow vehicle, Same direction 43.55 919.07 84.07 102.28 3. Lane change, Same direction 0.18 0 .36 0.46 1.06 4 Rightturn, Same direction 16.82 210.76 36.01 45.49 5 Lett-turn, Opposing direction 7.00 41.20 15 .44 19.74 6. LefHurnfrom-loft, Cross traffic 0.18 0.16 0.55 0.93 7. Through, Cross traffic from left 0.27 0.82 0.70 1.59 8. Right-turn, Cwss traff i c from left 0.18 o. 16 0.55 0.93 9. Left-turn, Cross uaffic from right 1.91 1 7.29 5.77 9.70 10. Through, Cross t raffi c from right 0.09 0.09 0.23 0.53 1 1. Right turn, Cross traffic from right 5.27 21.62 11.41 14.47 12. Righ Hurn on red, Opposing d i rectio n 0.36 0.45 1.08 1.68 1 3. Conflicts oth e r than 1 through 1 2 1 .09 3.29 3.13 4.69 1 throug h 4 Same direction 74.64 3521.45 153.53 19 1.01 7 plus 10, Through, Cross traffic 0 .36 0.85 1.08 1.99 Table 0.2 Florida-Based Conflict Table For Signalized, 4-Legged, 2x4 Intersections Con f lict Type Mea n Variance Abnormally High C o nflict Counts 90th Percentil e 95th Percentile 1 Leftt um, Same d irect ion 6 .58 66.27 16.79 22.96 2. Slow vehicle, Same direction 35.58 583.90 67.91 82.29 3. Lane change, Same d irection 8.08 152.08 22.54 32.76 4. Rlghtturn, Same direction 11.67 168.79 28.31 37.74 5. Leftturn, Opposing d irection 2.25 3.48 4 .72 5.92 6. Left turnfrom left, Cross t r aff i c o.oo o.oo . 7 Through, Cross traffic from left 0.08 0.08 0 .20 0 .49 8. Rightturn. Cross traffic hom left 0.00 0.00 . 9. leftturn. Cross traff ic from right 0.25 0.39 0.75 1.36 tO. T hroug h, C ross traffi c from right o.oo 0.00 11. Rlghtturn, Cross traffic from right 1.67 4.24 4.25 5.81 l2. Rightturn on red. Opposing direction 0.58 0.63 1 .S 5 2.18 13. Conflicts ot her than 1 through 12 0 .17 0.15 0.50 0.88 1 through 4, Same direction 61 .92 1997.90 121.60 148 81 7 plus 10, Through, Cross traffic 0.08 0.08 0.20 0.49 74

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T a b l e 0 .3 -Florida-Ba s e d Conflict T a b l e F o r S i g n a lized, 4-legge d. 2x6 I n t e r s e c tion s Con f l ict Type Mean Variance A bnormally H i gh Con f l ict C o unt s 90th Pe rcenti l e 95th Pe rcenti l e 1 Left-turn Same direction 13. 7 3 287.22 34.98 4 7 .83 2 S l ow vehicle. Same directio n 44.73 706.42 80.36 9 5 .44 3 Lane c hang e Same d i r e ction 5 .55 11.87 10.16 1 2.15 4. R i ght-tur n S a me d irection 49.64 216 6 .85 110 7 1 142. 1 2 5 Left t um, O pposi n g d irect ion 2 .09 3 .09 4 4 2 5 .56 6 L ef t tum-f r om l elt, C r oss traff i c 0 .09 0 .09 0 .23 0 .53 7 Throug h C ross traffic f r om l e ft 0 .00 0.00 . 8 RlghNurn Cross traff i c from l eft 0.18 0.36 0 .46 1.06 9 Leftt um. Cross t r affi c f rom rig h t 0.0 0 0.00 . tO. Through C ross traff i c hom fight 0 .09 0.09 0 2 3 0 .53 1 1. R i g hHurn, Cross traffic from r ight 5 .27 43.02 13.48 1 8 .47 1 2 Rig h t-turn on red. Opposing d i r ecti on 1.27 1 0 .82 3.77 7 01 1 3 C o nfli c t s o t h er t h an 1 t hro u gh 1 2 2.91 44.89 8.79 15.22 1 through 4, Same dire ct ion 113 .64 6358.85 220.22 268.24 7 p l us 10. T h ro u gh, C r oss traff i c 0 .09 0.09 0.23 0.5 3 T a b le 0 4 F l orida Based Con f lict T abl e F o r Sig na liz e d, 4-legg e d 4x4 I n t e r s e c t io n s Conflict Type Mean Variance Abnormally High Con fl i ct Count s 90ch Per c e n t i l e 95t h Percentile 1 L e t t -turn, Same direct ion 7 .60 75.55 18.56 24.97 2 S l ow vahicte, Same d i rection 40.50 4 8 8 .09 70.12 8 2.31 3 Lane c hange, Same dire ct ion 6.67 44.24 1 5 .33 19 9 4 4 A i g h t t u r n Same d ireccion 21.17 581 .24 5 1.93 6 9.59 5. Lef t tum Opp osing d irectio n 3.75 22.39 9 .65 13.27 6 L eft-t urnf r om-le f t Cros s t ratt i c 0 .33 1.3 3 0.81 1.94 7 T hrough, C ross lra ff i c f rom l eft 0 .25 0 .39 0.75 1.36 8 R i ght turn, Cr oss tratt i e fro m l e ft 0 0 0 0 .00 . 9. lefc-turn, Cros s tra ff i c f rom rig h t 0 .08 0 .08 0 .20 0.49 10. Through Cross t raUi f rom right 0 .00 0 .00 . 1 1 R ightturn. Cross t raffic from rig h t 1 .25 4. 2 0 3.58 5.33 1 2 Right-t um o n red, Oppo s ing d irecti o n 0 .67 5 .33 1.62 3 .88 1 3 Conflict s other than 1 t hrough 1 2 0 .92 6.63 2.63 5 19 1 through 4, Same d irection 75.83 2088.52 137.09 163.15 7 plus 10, Through, C ross t r affic 0 .25 0.39 0.75 1.36 75

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Table 0.5 Aorida-Based Conflict Table For Signalized. 4-legged. 4x6 Intersections Conflict Type Mean Variance Abnormally High Conflict Counts 90th Percent i l e 95th Percentile 1. Lefttum, Same d irect ion 9.67 149.70 24.92 34.29 2. Slow vehicle Same direction 46.58 501.36 76.59 88.45 3. Lane change, Same d ire ction 7 75 78.02 19.02 25.49 4. AighHurn, Same direction 24.42 418.63 51.53 64.72 5 Leftturn. Opposing direction 4.67 25.88 11.21 14.87 6 Leftturnfrom l eft, Cross traffic o .oo o.oo . 7. Through, Cross traffic f rom left 0.00 0.00 . 8. Right-turn Cross traffic from left 0 .00 0.00 . 9. Left-turn, Cross traffic from r igh t 0.08 0.08 0.20 0.49 10. Through, Cross traffic from right 0 .08 0.08 0.20 0.49 11. Right-tum, C r oss traffic f rom r ight 2.08 5.17 5.01 6.64 12. Right-turn on red, Opposing direction 1.00 4.00 3.00 4 .84 1 3. Conflicts other than 1 through 12 2 .5 8 42.63 7.70 14.10 1 throug h 4, Same direction 88.42 2570.81 156.40 184.83 7 plus 10, Through, Cross traffic 0.08 0.08 0 .20 0.49 Table 0 6 Florida -Based Conflict Table For Signalized, 3-Legged, 2x2 Intersection s Conflict Type Mean Varia n ce Abnormally High Conflict Counts 90th Percent ile-95t h Percentile 1 Left turn, Same direction 13.10 364.32 35.88 51 .4 0 2. Slow vehicle Same direction 20.00 388.22 45.71 59.29 3. Lane change, Same direction 1.40 14.04 4.10 7 8 1 4. Righttum, Same direction 10.70 171.12 27.14 37.02 5. Lefttum. Opposing d irect i on 2.20 4.62 5.01 6.48 6 Cross traffic 0 .60 1.60 1.81 2 .99 7 Throug h Ctoss traffic from left 0 .00 0.00 . 8. Right-turn, Cross traffic from left 0.00 0.00 . 9. Left-turn, Cross traffic f rom right 0.10 0.10 0.27 0 .58 10. Through Cross traffic from right 0.20 0 .40 0.53 1.16 1 1. R ight tutn, Cross traffic from right 1.30 4.90 3.76 5.68 12. Rightturn on red Opposing direction 0.00 0.00 . 13. Conflicts other than 1 t h r oug h 12 0.00 o.oo . 1 through 4, Same direct i on 45.20 1597.73 97.95 124.29 7 plus 10, Through, Cross traffic: 0.20 0.40 0 .53 1 .16 76

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Tabla D. 7 -Florida-Basad Conflict Tabla For Signalized, 3-laggad, 2x4 Intersections Conflict Type Mean Variance Abnormally High Conflict Counts 90th Percentile 95th Percentile 1. Same direction 2.83 12.15 7.21 9.85 2. Slow vehicle, Same direction 34.42 1097.36 77.77 100.37 3. Lane change, Same direction 6.33 38.79 14.46 18.75 4 Righttvrn, Same d irection 5.25 37.30 13.01 17.52 5. Left-tum, Opposing direct ion 2.83 15.24 7.58 10.68 6. Lefttunrfromleft, Cross traffic 0.17 0.15 0.50 0.88 7 Through, Cross traffic from left o.oo o.oo -8. Rightturn, Cross traffic from left 0 .00 0.00 -9. Left-tum, Cross traffic from right 0.08 0.08 0.20 0.49 10. T hrough, Cross traffic from right 0.00 0.00 11 Right-turn Cross traffic from right 2.25 7.84 5.76 7.89 12. Right-turn on red, Opposing direction 0 .08 0.08 0.20 0.49 13. Co nf l icts other thon 1 through 12 0.42 0.45 1.18 1.75 1 through 4, Same direction 48.83 1366.52 98.10 121.ot 7 plus 10, Through, Cross traffic 0.00 o.oo . Table 0.8 F lorida-Based Conflict Table For Signalized, 3-legged, 2x6 Intersections Conflict Type Mean Variance Abnormally High ConfliCt CQunts 90th Percentile 95th Percenti le 1. left-tum, Same direction 13.75 538.39 39.69 59.72 2 Slow vehic l e. Same direction 45.00 1216.73 91.44 113.25 3. lane change, Same direction 3 .75 8.39 7.61 9.41 4. Right-turn, Same direction 24.6 7 389.70 50.90 63.40 5. letNurn, Opposing direction 3.50 52.09 10.55 17.25 6. Left tum from l eft Cross traffic 0.17 0.15 0.50 0.88 7 Through, Cross traffic hom left 0.00 0.00 -8. R ightturn, Cross traffic from left 0.67 1.52 1.97 3.07 9. Left-tum, Cross traffic from right 1.08 1.36 2.58 3 .42 10. Through, Cross traffic from right 0.17 0.15 0.50 0.88 11. Right-turn, Cross traffic from right 3.25 11.30 7.61 9.97 12. Right-turn on red. Opposing dire<:tion 0.17 0.15 0.50 0.88 13. Conflicts other than 1 through 12 2.83 35.24 8.55 14.09 1 through 4, Same direction 87.17 4819.79 179.46 223.33 7 plus 1 o. Through, Cross uaffic 0.17 0.15 0.50 0 .88 77

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Table 0.9 Florida-Based Conflict Table For Signalized, 3-Legged, 4x4 Intersections Confl ict Type Mean Variance Abnormally High Conflict Counts 90th Percentile 95th Percentile 1 LefNurn, Same d ire<:tion 13.67 472.61 38.69 57.02 2. Slow Same direction 39.42 843.90 78.18 96.00 3. Lane change, Same direction 2.83 1.61 4.53 5.19 4. Right-turn, Same direction 15.75 170.39 33.06 41.44 5. Left-tum, Opposing direction 1.83 5.42 4.73 6.52 6. Left-tum-fromleft, Cross traffi c 1.17 10.33 3.38 6.57 7. Through, Cross traffic from l eft 0.00 0.00 . 8. Right turn, Cross traffic from left 0.00 0.00 --9. Left-tum, C1oss traffi c f rom right 0.17 0.33 0.41 0.97 10. Throug h, C ross traffic from r i ght 0.00 0.00 --11. Rightturn, Cross traffic ftom right 1.00 1.64 2.59 3.58 12 Rightturn on Opposing d ire<:tion 0.92 3.72 2.77 4 .57 13. Conflicts other than 1 through 12 0 .25 0.39 0.75 1.36 1 through 4, Same direct ion 71.67 2818.06 142.48 1 75.11 7 plus 10, T h r ough Cross traffi c 0.00 0.00 -Table 0.10 Florida-Based Conflict Tab le For Unsignalized, 4-Legged, 2x2 Intersections Conflic t Type Mean Variance Abnormally High Conflict Count s 90th Percentile 95th Percentile 1. left turn Same direction 4.50 130.82 13.40 24. 61 2. Slow vehicle, Same direction 12.92 395.72 36.14 52.70 3. Lane change, Same direction 0.33 0.79 0 .98 1.86 4, RighHurn, Same d irection 5 .58 60.27 15.0 0 21.19 5 left-turn. Opposing d irection 1.83 19.06 5.52 9.75 6. Cross traffic 1.33 6.79 3.99 6.36 7. Through, Cross traff i c from left 0.67 2.06 2.02 3.37 8 Right-turn, Cross traff ic from left 0 .00 0.00 --9. L eftturn, Cross traffi c from right 1.92 12.08 5.64 8.73 10. Through, Cross t raffic from right 0.75 2.39 2.26 3.69 1 1. Right-turn, Cross traffic from right 1.25 2.93 3.34 4 .69 13. Conflicts other than 1 through 11 0 .5 8 2.99 1.63 3.35 1 t h rough 4, Same direction 23.33 1302.97 65.39 95.49 7 plus 10, Through, Cross traff i c 1.42 7.90 4.25 6.83 78

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Table 0.11 Florida-Basad Conflict Tabla For Unslgnalizad, 4-Laggad, 2x4 Intersections Con f l ict Type Mean Variance Abnormally H igh Con f lict Counts 90th Percentile 95th Percentile 1. left-turn, Same direct i on 5.00 57.00 13.89 20.12 2. S low vehicle, Same direction 22.23 305.69 45.49 56.49 3 Lane change, Same direction 4 .38 21.09 10.33 13.57 4. Right-turn, Same d i rectio n 6.00 28.67 13.06 16.60 5. lefttu tn, Oppos i ng direct i on 1.69 15.73 5 11 8.93 6. Left-tunrfrom-left, Cross traffic 1.23 2.86 3.29 4 .63 7. Throug h, C ross t raffi c f rom left 0.96 2.90 2.08 3.73 8. Right-turn, Cross traffic f r om left 0 15 0.14 0.46 0.83 9. left-turn, Cross traffic from right 0.69 0.56 1.66 2.20 10. Through, Cross traHic f rom right 0 .62 1.09 1.78 2.68 11. RighHutn, Cross traffic from right 1.85 2 .64 3 .99 5.06 13. Conflicts o t he r than 1 t h rough 11 0.31 1.23 0.71 1.79 1 t h rough 4 Same direction 37.62 847.76 76.38 94.58 7 plus 10, Through, Cross traffic 1.31 3.56 3.57 5.10 Table 0.12 Florida Based Conflict Table For Unsignallzed, 4-Lagged, 2x6 Intersections Conflict Type Mea n Variance Abnormally High Conflict Counts 90th Percentile 95th Percentile 1 Left-t urn, Same d irect i on 7.45 376.27 22.06 41.1 5 2. S low vehicle Same direction 48.18 1788.36 104.02 131.80 3. Lane change, Same d i recti on 4.00 24.00 10.16 13.86 4. RighHvrn, Same d i recti on 24.00 459.80 52.27 66.46 5. Left-turn, Opposing d ire<:tion 2 .55 11.87 6 .76 9.48 6 Left-tvrnfrom left, Cross traffic 0.64 1.45 1.89 2.98 7 Through, Cross traffic f rom left o .oo o .oo . 8. Right-turn, C ross traffic from left o. 18 0.36 0.46 1.06 9. Leftturn, Cross traffic f rom right 2.18 11.16 6.09 8.87 10. Through Cross traffic from r igh t 0.55 0.87 1 .5 8 2.39 11. R i ghtturn, C ross traffic f rom r ight 3.64 10 .65 7 .94 10.10 13. Confl icts other t han 1 t h r oug h 11 11.36 681.25 34.34 59.36 1 through 4, Same direction 83.64 3066.65 157.76 190.41 7 plus 10. T hrough. Cross traffic 0 .55 0 .87 1.58 2.39 79

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Table 0.13-Florida-Based Conflict Table For Unsignalized, 3-Legged, 2x2 Intersections Conflict Type M""n Variance Abnormally High Conflict Counts 90th Percentile 95th Percentile 1 Left-turn, Same d irection 4.67 76.42 13.84 21.70 2. S low vehicle, Same direction 10.75 195.30 28.05 38.88 3. Lane change, Same direction 0.00 0.00 . 4 Right-turn. Same direction 3 .92 58.45 1 1. 71 18.68 5. Left tum, Opposing direction 0.75 6.75 1.82 4.37 6. left turnfromleft. Cross traffic 1.08 3.36 3.13 4.72 7. Through, Cross traffic f rom left o. 17 o. 15 0.50 0.88 8. Right-turn. Cross traffic from left 0.00 0.00 . 9. Left-tu rn, Cross traffic from right 0.50 3.00 1.22 2.91 10. Through, Cross traffic tram right 0.17 0.15 0.50 0.88 1 1. Right-turn, Cross traffic from right 0.08 0.08 0.20 0.49 13. Conflicts other t han 1 through 11 0.58 4.08 1.42 3.40 1 through 4, Same direction 19 .33 786.97 52.86 75.64 7 plus 10, Through, Cross traffic 0.33 0.24 0.92 1.32 Table 0.14 Florida-Based Con flict Table For Unsignalized, 3-Legged, 2x4 Intersections Conflict Type Mean Variance Abnormally High Conf l ict Counts 90th Per cent ile 95th Perc::entile 1 Laft-tu rn. Same direction t.92 10.45 5.53 8.32 2. Slow vehicle, Same direction 13.25 111.11 27.26 33.92 3 Lane change, Same direct ion 1.50 2.27 3.46 4.51 4 Rightturn, Same direction 2.83 8.52 6.62 8.67 S. Lett -t v rn Opposing d i rection 0.25 0 .20 0.74 1 14 6. lefHurn-trom-l eft, Cross traffic 0.83 2.33 2.46 3.82 7. Through, Cross traffic from left 0 .08 0.08 0.20 0.49 8. Right-tum, Cross tlafflc f rom left 0.00 0.00 . 9. Left-turn, Cross ttaffic from right 0.33 0.24 0.92 l.32 10. Thr ou g h, C ross traff ic from right 0.08 0.08 0.20 0 .49 11. Right-wrn, C ross traffic f r om right 0.50 0.64 1.42 2.09 1 3 Conflicts other than 1 through 11 6.08 307.17 17.25 34.70 1 t h r ough 4, Same direction 1 9 .50 204.09 38.57 47.31 7 plus 10, Through, Cross traffic 0.17 0.15 0.50 0.88 80

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Table 0.15 Florida-Based Conflict Table For Unsignalized, 3-legged, 2x6 Intersections Conflict Type Mean Variance Abnormally H igh Conf l ict Cou nts 90th Percentile 95th Percentile 1 Left-turn. Same direction 11 .43 344.11 32.58 48.35 2 Slow vehicle. Same direction 35.43 575.96 67.54 81.80 3. Lane change, Same direct i on 6.50 43.04 15.04 19.60 4. Right-turn, Same direction 16.00 347.23 39.67 53.45 5 Left-turn, Opposing direction 3.14 15.36 8.05 11.03 6 leftturn from left, Cross traffic 1.57 5 .80 4.39 6.39 7 Through, Cross traffic from left 0.29 0.68 0.81 1.63 8 Right-turn, Cross tratfic from l eft 0.00 0.00 . 9. Lef t t urn, Cross traffic from right 0.64 0.86 1.76 2 .51 10. Through, Cross traffi c from r ight 0 .36 0 .55 1.08 1.77 11. R l ghNurn C ross traff ic from right 2.64 8.71 6.42 8.57 13. Confl icts ot h er than 1 through 1 1 3 .86 116.29 11. 11 21.82 1 through 4, Same direction 69.36 1734.55 1 25. 1 8 148.91 7 plus 10, Thtough, Cross traffic 0 .64 1.02 1.8 1 2 .66 81

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Appendix E. Crash/conflict Ratio Tables for Flor ida based Intersections 82

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Notes on tables: Intersection C ategories : [Signalized/Unsigna lized I. [4-legged/3-legged (or 'T')) [Through Laneage: 2x2, 2x4, 2x6, 4x4, 4x6J The conflict counts were obtained during a 4-hour observation period on a weekday ( Monday through Thursday excluding holidays) between 7am to 6pm under dry pavement conditions. T hese counts do not include secondary conflicts. 83

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Table E.1 Florida-Based Crash/Conflict Ratio Table For Signalized, 4-Leggad, 2x2 Intersections Conf l ict Type Constant A Const ant B 1. Laft turn, Same direction 0.00751 0 .28743 2 Slow vehic le, Same direction 0.02516 1.23874 3. Lane change. Same direction 0.02066 0.00140 4. Rightturn. Same d i rection 0.00801 0.08567 5. left-turn, Opposing direction 0.00728 0.01211 6. leftturnfrom -left, C ross traff ic 0.00000 0.00000 7. Through, Cross traffi c from left 0.01377 0 .00140 8. Right-turn Cross traffic from left 0.00000 0.00000 9. LefHurn Cross traffic from righ t 0.00000 0 .00000 10. Throug h Cross traf f ic from r ight 0.05510 0.00193 11. Right-turn. Ctoss traffic from r ight 0.00000 0.00000 12. Righttum on red, Opposing direction o.ooooo 0.00000 13. Confli ct s other than 1 t hrough 12 0 .03926 0 .01739 1 through 4 Same d irec tion 0.00003 0.00001 7 p l us 10, Through, Cross traff i c 0.00015 0.00000 Table E.2 Florida-Based Crash/Conflict Ratio Table For Signalized, 4-Legged, 2x4 Intersections Conflict Type Constant A C o nsta nt B 1 leftturn. Same direction 0.01130 0.07628 2. Slow vehicle, Same direction 0.06407 4.01093 3. Lane change, Same d irection 0.12069 6.44873 4. Righ t tum Same d irect ion 0.00912 0.08442 5. left-tum. Opposing direct ion 0 .37577 1. 13852 6. left-tum-from-left. Cross ttaftic 0.00000 0.00000 7 Through, Cross traff ic from l eft 0.00000 0.00000 8. R ig h t turn, Cross traffic from left 0.00000 0.00000 9. left-tum Cross traffic from right 0.00000 0.00000 10. Through, Cross traffic from right 0.00000 0.00000 11. RighHum, Cross traffic from right 0 .00000 0.00000 12. Right-t urn on red, Opposing direction 0.00000 0.00000 13. Conflicts othe r than 1 through 1 2 0.00000 0.00000 1 through 4, Same direction 0.00007 0.00001 7 plus 10, Through, Cross traff i c 0.00000 0.00000 84 Constant C 0.00062 0.00071 0.00342 0.00034 0.00024 0.00000 0.00152 0.00000 0.00000 0 .01822 0.00000 0.00000 0.00374 0.00000 0 .00000 Constant C 0 .00102 0.00276 0.02784 0.00042 0.18621 0.00000 0.00000 0 .00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000

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Table E.3 Florida-Based Crash/Conflict Ratio Table For Signalized, 4Legged, 2x6 Intersections Conflict Type Constant A Constant B 1 L eftturn Same d i rection 0.01030 0 .18657 2. Slow vehicle, Same direction 0.05578 3.48699 3. Lane change, Same direction 0.09095 0.54088 4. Right t u rn, Same d irec tio n 0.02582 13.31867 5. Left-tum, Opposing d irection 0 .11938 0 .10798 6 L efttum-from-left, Cross traffic 0.00000 0 .00000 7. Through, Cross traffic from left 0.00000 0 .00000 8. Rightturn, Cross traff i c from left 0.00000 0.00000 9. Left-tum, Cross traffic f rom right 0 .00000 0.00000 10. Thro ug h. Cross traffic f rom right 0.04723 0.00162 11. RighHurn, Cross traffic from right 0.01503 0 1 1657 12. RighH urn on red, Opposing d i rection 0.00000 0.00000 1 3 Conflicts other than 1 through 12 0 .00167 0.00125 1 throug h 4, Same d i rection 0.00006 0 .00004 7 p lus 10, Through, Cross tr affic 0.00027 0.00000 Tab l e E 4 Florida-Based Crash/Conflict Ratio Table For Signalized, 4-Legged, 4x4 Intersections Conflict Typ e Constant A Constant B 1. LefHum, Same d irection 0.03005 0.81882 2 Slow vehi cle, Same direction 0.07236 5.02167 3 lane change, Same direction 0.22871 11.92438 4. Right-turn, Same direction 0.02669 0 .93909 5. Lef t-turn. Opposing direction 0.29417 3.50343 6. left-turn f rom-left. Cross t ra ffic 0.00000 0.00000 7. Through, Cross traffic f r o m l eft 0.04132 0 .00594 8. R ightturn, Cross traffic from l eft 0 .00000 0.00000 9. Leftt u r n Cross traffic from r ight 0 .03005 0.00090 10. Through, Cross traffic from right 0.00000 0.00000 11. Rightturn, Cross t,taffic from right 0.04508 0.05659 12. Right-turn on red, Opposing direct ion 0.00000 0.00000 13 Conf l icts other than 1 th r oug h 12 0.34284 2.74920 1 t h rough 4, Same direction 0.00010 0.00004 7 p lus 10 Through, Cross traffic 0.00027 0.00000 85 Constant C 0.00054 0.00182 0.03728 0.00548 0.02068 0 .00000 0.00000 0 .00000 0.00000 0.01561 0.00248 0.00000 0.00003 0 .00000 0.00000 Constant C 0.00994 0.00505 0.21721 0.00090 0.06996 0 .00000 0 .01366 0.00000 0.00994 0.00000 0.01143 0.00000 0.29720 0 .00000 0.00000

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Table E.S Florida-Based Crash/Conflict Ratio Table For Signalized, 4-Legged, 4x6 Intersections Conflict Type Constant A Constant B 1. Lefttutn Same direction 0.03189 0.57680 2. Slow vehicle, Same direction 0.09325 7 .69109 3 lane change. Same direction 0.28563 17.72090 4 Right tum Same direction 0.12303 42.00368 5. Left-turn, Opposing direction 0.24093 4.84 718 6. Left -tum-fromleft, Cross traffic 0.00000 0.00000 7. Through. Cross traffic from l eft 0.00000 0.00000 8. Righ t-tum, Cross traff i c from left 0.00000 0.00000 9. Left-tu m, C ross traffic from right 0.00000 0 .00000 10. Through, Cross traffic from right 0.00000 0.00000 11. Rightl u rn, Cross traffic from right 0 .05510 0.07540 12. Right-turn on red, Opposing direction 0.01377 0.00987 13. C onflicts ot h er than 1 through 1 2 0.26187 12.94030 1 through 4, Same direction 0.00016 0.00012 7 pl us 10, Through, C r oss traffic 0.00000 0 .00000 Table E.G Florida-Based Crash/Conflict Ratio Table For Signalized, 3-Legged, 2x2 Intersections Conflict Type Constant A Constant B 1. lett-turn, Same direction 0.00000 0.00000 2. Slow vehicle, Same d irection 0.12523 23.56865 3. Lane c-hange. Same direction 0.00000 0 .00000 4. Righ t turn, Same direction 0.00000 0.00000 5. leftturn, Opposing direction 0.05143 0.07172 6. Lefttum-fromleft, Cross traffic 0.00000 0 .00000 7 Through Ctoss ttaffic f r o m l eft 0.00000 0.00000 8. RighH urn, Cross traffic fr o m l eft 0 .00000 0 .00000 9 LeftttJrn, Cross traffi c from right 0.00000 0.00000 10. T h rough Cross traffic from right 0.00000 0 .00000 1 1 A i ghtturn, Cross traffic from right 0 .00000 0.00000 1 2 Right' turn on red, Opposing direction 0 .00000 0 .00000 1 3. Confl i cts other than 1 th rough 1 2 0.00000 0.00000 1 through 4, Same direction 0.00005 0 00001 7 plus 10 Through, Cross traf fic 0.00000 0 .00000 86 Constant C 0.00284 0 .00664 0.14554 0.08520 0.12926 0 .00000 0.00000 0.00000 0.00000 0.00000 0.01154 0.00228 0.23498 0.00000 0.00000 Consta n t C 0.00000 0.04503 0 .00000 0.00000 0 .01287 0 .00000 0 .00000 0.00000 0 .00000 0.00000 0.00000 0.00000 0 .00000 0.00000 0 .00000

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Table E 7 Florida-Based Crash/Conflict Ratio Table F o r Signalized, 3Legged, 2x4 I n tersect i ons Conflict Type Constant A Constant 8 1. Left-tum. Same d ir ection 0.01002 0.01463 2. S low vehic le, Same direction 0.04604 5.43469 3 lane change Same d i rection 0.05040 0.52679 4. Rlghttum, Same direct ion 0 .0131 4 0.06090 6 Leftturn. Opposing direction 0.20815 1 .51679 6. Lett-turn-from-left. Cross traffi c 0.00000 0.00000 7. Through, Cross traffic f rom left 0.00000 0.00000 8. R ighHurn, Cross traffic from left 0.00000 0.00000 9. lefttu rn, Cross traffic from right 0.00000 0.00000 10. Through, Cross traffic f rom rig h t 0.00000 0.00000 1 1. Right-turn, Cross traffi c from right 0.00501 0.00236 12. Right-t urn on r ed, Opposing direction 0.00000 0.00000 13. Conflicts other than 1 through 12 0.16530 0 .0401 3 1 t hrough 4, Same d i rection 0 .00008 0 .00002 7 plus 10, Through, C r oss traffi c 0 .00000 0.00000 Table E.S AoridaBased Crash/Conflict Ratio Tab l e For S i gnalized. 3-Legged, 2x6 Inter s ecti ons Conflict Type Constant A Constant B 1. left-turn, Same d i re ction 0.00000 0.00000 2. Slow vehic le, Same difection 0.06926 16.93258 3. Lane change, Same direction 0.07180 0.10526 4. Right-turn, Same d ire c t i on 0.00741 0.06046 5 Left-tum, Oppos ing d i rection 0.02579 0.20388 6. LefHvrn-homleft. Cross t raffic 0 .00000 0 .00000 7 Through, Cross traffic from left 0 .00000 0.00000 8. Rightturn. Cross t raffi c f rom left 0 .00000 0.00000 9. leftturn, C r o s s traffic f rom right 0.06011 0.02915 10. Through Cross traflic from right 0.00000 0 .00000 11 Right t u tn, C ros s traffi c from right 0.00301 0.00122 12. Right tum on red Opposing d i rection 0.00000 0 .00000 13. Confl icts other than 1 t hrough 12 0.09948 1.71402 1 through 4, Same d i rectio n 0 .00005 0 .00003 7 plus 10, Thr ough, Cross traffic 0.00000 0.00000 87 Constant C 0.00110 0.00283 0.01104 0 .00146 0.05618 0.00000 0.00000 0.00000 0.00000 0.00000 0 .00028 0 .00000 0.06245 0.00000 0.00000 Constant C 0.00000 0.00912 0.00740 0.00010 0.00325 0 .00000 0.00000 0.00000 0.01788 0 .00000 0.00010 0 .00000 0.03874 0 .00000 0.00000

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Table E.9 Florida-Based Crash/Conflict Ratio Table For Signalized, 3-Legged, 4x4 Intersections Conflict Type Constant A Consta nt B 1. Lett-turn. Same direction 0 .01067 0.40741 2. Slow vehicle, Same direction 0.06773 19.63668 3 Lane change. Same d irection 0.1 8 137 0.17549 4. Same d i rection 0.03691 1. 77881 5. Left-turn, Opposiog d irection 0.06512 0.09815 6. Leftturn-from-teft. Cross traffic 0.00000 0.00000 7 Through, Cross traff i c from l eft 0.00000 0.00000 8. R i ght-tum, Cross traffic from lett 0.00000 0.00000 9. Leftturn. Cross traffic from r ight 0 .00000 0 .00000 10. Through, Cross traffic from right 0.00000 0.00000 11. Right turn. Ctoss traff ic from right 0.03306 0.01967 12. Right-t u rn on red. Opposing d i rection 0.00551 0 .00147 13. Co nflicts other than 1 through 1 2 0.06612 0.01013 1 t h r ough 4, Same direction 0.00008 0.00005 7 plus 10. Through, Cross traffic 0.00000 0.00000 Tab l e E 10 Florida-Based Crash/Conflict Rat i o Table For Unsignalized, 4 Legged. 2x2 Intersections Confl i c t Type Constant A Constant 8 1. Leftt orn, Same d i rection 0.00000 0.00000 2. Slow vehi c l e. Same d irection 0.00207 0 .01349 3. Lane change, Same direction 0.00000 0.00000 4 Right-turn, Same direction 0.00000 0.00000 5. leftturn, Opposing direct i on 0 .00000 0.00000 6. left turn-from-left, Cross traffic 0 .00000 0.00000 7. Through, Cross traffic from left 0.07714 0.05293 8 Right-tum Cross traffic from left 0.00000 0.00000 9 Lett-turn, Cross traffic from right 0.00344 0.00186 10. Through, Cross traffi c from right 0.00689 0 .00147 11. Rightturn, Cross tr affic from right 0.00000 0 .00000 13. Confii ets Other than 1 through 12 0.00000 0 .00000 1 through 4, Same direction 0.00000 0.00000 7 p lus 10, Through, Cross traff i c 0.00000 0.00000 88 Constant C 0.00075 O.Q1868 0.07637 0.00908 0.01385 0.00000 0.00000 0.00000 0.00000 0 .00000 0.01093 0.00036 0 .02186 0 .00000 0 .00000 Constant C 0.00000 0 .00003 0.00000 0.00000 0.00000 0.00000 0.01974 0.00000 0.00014 0.00067 0 .00000 0.00000 0.00000 0.00000

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Table E.11 Florida-Based Crash/Conflict Ratio Table For Unsignallzed, 4-Legged 2x4 Intersections Conflict Type Constant A Constant B l Lett-turn, Same direction 0.00000 0 .00000 2. Slow vehicle, same direction 0.00948 0.13956 3. Lane change. Same direction 0.01211 0 .02500 4 RighHurn, Same direction 0.00509 0.01038 5. Left-turn, Opposing d i rection 0.04670 0.22031 6 left turn-from left, Cross traff i c 0.00000 0.00000 7. Through, Cross traffic f rom left 0.11020 0 .13414 8. Right-turn, Cross traffic from left 0 .00000 0.00000 9. LefHurn, Cross traffic f rom right 0.06011 0.01213 10. Through, Cross traffic f rom right 0.09367 0.03018 1 1. R i ght-turn, Cross traffic from right 0.01907 0.00744 13 Conflicts other than 1 through 12 0.00000 0.00000 1 throug h 4, Same direction 0.00001 0.00000 7 plus 10, Throug h Cross traffic 0.00040 0.00000 Table E.12 Florida-Based Crash/Conflict Ratio Table For Unslgnalized. 4-Legged, 2x6 Intersections C<>nflict Type Constant A Cons tant 8 1. Leftturn. Same direction 0.00730 0.12304 2. Slow vehicle, Same d irec tio n 0.03755 6.62903 3. Lane change. Same direction 0.04602 0.17346 4, RighHurn, Same direct i on 0 .00929 0 .11680 5. Left-tum, Opposing direction 0.18283 1.70214 6. Left tum f r o m-lett, Cross traffic 0.16530 0.13058 7. Throug h C ross traffic from left 0.00000 0.00000 8 RighHurn. Cross t"'ffic from left 0.00000 0.00000 9. Left-turn, Cross traffi c hom right 0.01837 0.03766 10. Thr ough Cross traffic from right 0.19285 0 .07458 11. Right turn, Cross traffic f rom righ t 0.08014 0.51069 13. Conflicts other than 1 t hrough 12 0.01458 0.79436 1 through 4, Same d i rection 0 .00003 0.00000 7 plus 10, Through, Cross traffic 0 .00071 0.00000 89 Constant C 0.00000 0.00037 0.00104 0.00034 0.01182 0.00000 0.03415 0.00000 0.01788 0.01892 0.00245 0.00000 0.00000 0.00000 Constant C 0.00027 0 .00230 0.00511 0.00017 0 .10994 0.06245 0.00000 0.00000 0.00304 0.04827 0.04151 0.00095 0.00000 0.00000

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Table E.13 Florida-Based Crash/Conflict Ratio Table For Unsignallzed, 3-Legged, 2x2 Intersections Conflict Type Constant A Constant B 1. LefNurn, Same direction 0.00000 0.00000 2. Slow vehicle, Same direct i on 0.01360 0.23727 3. Lane change, Same direction 0.00000 0 .00000 4. Righttorn, Same direction 0.00000 0.00000 5. Left-turn. Opposing direction 0.00000 0.00000 6. left-turn-fromleft, Cross traffic 0.00689 0.00207 7. Through, Cross traffi c f rom left 0.00000 0.00000 8. Right-turn, Cross traffic f rom left 0 .00000 0.00000 9. Leftturn, Cross traffic from right 0.00501 0.00090 10. Through, Cross from right 0 .00000 0.00000 11 Right t urn. Cross traffic from right 0.00000 0 .00000 1 3 Conflicts other tha n 1 through 12 0.00394 0.00082 1 t hrough 4, Same d i rectio n 0.00001 0.00000 7 plus 10, Through, Cross traffic 0.00000 0.00000 Table E.14 Florida-Based Crash/Conflict Ratio Table For Unsigna l ized, 3-Legged, 2x4 Intersections Conflict Type Constant A Constant B 1 Left turn. Same d irection 0.03306 0.11418 2. Slow vehicle, Same direction 0.07530 4.59659 3. Lane change. Same direction 0.03444 0.02375 4. Right-tum, Same direction 0.02755 0.08402 5 Leftturn, Opposing direction 0.04132 0.00314 6. Left turn.ftoml eft, Cross traffic 0.00000 0 .00000 7. Through, Cross traffic from left 0.00000 0.00000 8. Right-turn, Cross traffic from left 0.00000 0 .00000 9 LefHurn Cross traffic from right 0.03673 0.00327 10 Through, Cross traffic from right 0 .03673 0 .00112 11. R ight-turn, Cross traffic from right 0.00000 0 .00000 13. Conflicts other than 1 through 12 0.00000 o.ooooo 1 through 4, Sarne direction 0 .00014 0 .00002 7 plus 10, Through, Cross traff i c 0.00006 0.00000 90 Constant C 0.00000 0.00103 0.00000 0.00000 0.00000 0.00057 0.00000 0.00000 0.00028 0.00000 0.00000 0.00019 0 .00000 0.00000 Constant C 0.00984 0.03570 0.00926 0.00911 0.01366 0 .00000 0.00000 0 .00000 0.01214 0.01214 0.00000 0.00000 0.00000 0.00000

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Table E.15 Florida-Based Crash/Conflict Ratio Table For Unsignalized, 3-Legged, 2x6 Intersect ions Conflict Type Constant A Constant 8 1. Left-tum, Same direction 0.00000 0 .00000 2. Slow vehicle. Same direction 0.04287 5.62256 3. Lane change, Same direct ion 0 .03062 0.14237 4 Right-turn, Same direction 0.00000 0.00000 5. left-tur n, Opposing direction 0.03936 0 1 S990 6. Leftturnfrom-leh, Cross traffi c 0.02543 0 .05253 7. Thr ough Cross traffic f r om left 0.00000 0.00000 8. Right-tum. Cross traffic hom left 0.00000 0.00000 9. Left -tur n, Cross traffic from right 0.10018 0 .04732 10. Through, Cross uatfic from r i gh t 0.00000 0.00000 11. Rightturn, Cross ttaffie from right 0 .03306 0.08912 13. Conflicts otht!'r than 1 t h rou gh 12 0 .00907 0.08803 1 through 4, Same direct ion 0.00001 0.00000 7 p lus 10, Through, Cross traffic 0.00007 0.00000 91 Constant C 0.00000 0.00792 0.00237 0.00000 0.00886 0.00841 0.00000 0.00000 0.04482 0.00000 0.00914 0.00067 0.00000 0.00000