CRASH DATA ANALYSIS REPORT. Working Paper 6

Transcription

1 CRASH DATA ANALYSIS REPORT Working Paper 6 NOTICE: This report is being furnished to the traffic engineering community at the direction of NCHRP so to supply information about this research project and its findings. This report documents findings of the research project as of September This Working Paper was updated in September 2002 to reflect minor modifications due to study locations in Cupertino, CA. Prepared for: National Cooperative Highway Research Program Project Panel Members September 1999 Updated September 2002 Prepared by: KITTELSON & ASSOCIATES, INC. TEXAS TRANSPORTATION INSTITUTE 610 SW Alder Street, Ste 700 Texas A&M University System Portland, Oregon College Station, TX (503) (503) (409) , FAX (409) H:\PROJFILE\2036\YEAR 2002 WORK\WP6 UPDATE\WP6REVISED_CUPERTINO.DOC

2 Crash Data Analysis Working Paper 6 September 2002 Page 2 CRASH DATA ANALYSIS Introduction The analysis of crash data has been used to identify safety improvements and how better to operate and maintain the nation s transportation facilities. Historically, many agencies use crash data to identify their top 25 highest crash locations and based upon that list allocate significant budget towards mitigating those crash prone locations. Researchers and practitioners use crash data to evaluate the safety of various traffic control devices, including traffic signal phasing. The analysis of left-turn crash data also can be used as an effective method in evaluating the relative safety performance of various PPLT displays. In the context of this study, the crash analysis provides a historical perspective of crash experience at a given PPLT intersection under study and is intended to be a means by which a pattern or repeatability of specific types of events may be identified. Due to the extensive use of crash data in many past studies in the evaluation of left-turn control, the research team conducted a limited study of crash history related to the unique displays used in PPLT control. The research panel members and research team recognized that current crash reporting techniques do not adequately document causes of a crash as they relate to traffic signal operation, much less the particular signal display. To overcome this short coming, the research team identified a search plan that would compare the various PPLT control displays against one another and make judgements to whether a particular display was more or less prone to increased crash occurrence. Objective The objective of the crash analysis was to determine and compare left-turn crash rates associated with various PPLT signal displays. The details of the crash data analysis are described in the following sections.

3 Crash Data Analysis Working Paper 6 September 2002 Page 3 Methodology To accomplish the objective of the crash data analysis, several tasks were conducted. Those tasks are listed below: perform a literature review to provide background information on crash data analysis procedures and to review the results of previous studies; obtain traffic volumes, geometric design, signal display information, and three years of crash data for the study intersections (The same intersections studied in the operational study and the conflict study were evaluated in the crash analysis. In addition, crash data was sought on a voluntary basis from agencies around the U.S. and for those intersections in the JHK study.); reduce the data and analyze the results. Definitions/Nominclatures Within this working paper there are several abbreviations that are used for simplification reasons, and those are identified below. Display GB Green ball FYB Flashing yellow ball FRB Flashing red ball Display Arrangement H - Horizontal V - Vertical C - Cluster FRA Flashing red arrow Literature Review Since the mid s, Over 40 reports have been published on the use and operational impacts related to the protected/permissive left-turn signal control treatment. A select bibliography appears

4 Crash Data Analysis Working Paper 6 September 2002 Page 4 in Appendix A. Many of these reports were spurred from the increase in the use of PPLT phasing. In general, many of these reports identified trends in vehicle delay, vehicle conflicts, and vehicle crashes. Further, these studies related the affects of PPLT phasing to geometric and physical conditions, such as traffic volume, number of opposing lanes, signal displays, and the use of supplemental signing. Over 30 percent of the reports listed in Appendix A are focused on warrants or guidelines related to the use of PPLT phasing. The purpose of the literature review was to identify how crash data were evaluated and what crash statistic should be used for this study. The following literature review is selective in that not all reports related to PPLT phasing is identified. Certainly, there are many good reports available as a resource. The literature review identified below is key to this study because of the significance related to their findings and/or the strict focus related to PPLT phasing. Specifically some reports focus on the PPLT indications, display arrangement, and/or display location- all of which are study factors for this NCHRP study. Hummer (1) used crash data to evaluate the relative safety of intersections with leading left-turn sequences and similar intersections with lagging signal sequences. This study evaluated multiple intersection approaches (approximately 15 intersections each) using the two types of signal phase sequences. The crash analysis identified that intersections with leading left-turn signal phasing were more prone to a higher number of crashes than were similar intersections with lagging leftturn signal phasing. This finding was based upon general observation of trends in the data because the difference between leading and lagging sequences was not large for left-turn crashes per leftturn vehicle or left-turn crashes per total vehicles entering the intersection. Hummer stressed the use of extreme caution in basing left-turn sequence policy on such small differences in crash rates between small samples of relatively homogeneous intersections. Hummer found no significant relationship between crash variables such as pavement conditions and light conditions at intersections with leading and lagging phase sequences. Upchurch (2) used crash data to compare the relative safety of different types of left-turn phasing, which were: permissive; leading protected/permissive; lagging protected/permissive; leading

5 Crash Data Analysis Working Paper 6 September 2002 Page 5 protected; and lagging protected. A gross crash statistic comparison identified the following trends: Leading protected phasing has the lowest left-turn crash rate. When there are two opposing lanes, lagging protected/permissive has the worst crash rate. When there are three opposing lanes, leading protected/permissive has the worst crash rate. For two opposing lanes, the order of safety (from best to worst) is leading protected, permissive, leading protected/permissive, and lagging protected/permissive. It was noted that there were small differences in the crash rate among the last three types of phasing. For three opposing lanes, the order of safety (from best to worst) is leading protected, lagging protected/permissive, permissive, and leading protected/permissive. Upchurch also evaluated crash statistics for conditions that were stratified by both left-turn volume and opposing volume at the same time. Upchurch concluded that the choice of left-turn phasing type at a signalized intersection affects the left-turn crash rate. Further, the number of opposing lanes of traffic, left-turn volume, and the volume of opposing traffic also influences the crash rate. Hauer, et al (3) identified also that there is a relationship between crash frequency and traffic demand is nonlinear. Bonneson and McCoy (4) evaluated five PPLT signal designs considering both safety and operational performance measures. The safety evaluation included an examination of left-turn crash history, whereas the operational evaluation included measures of driver recognition and comprehensive of the PPLT design display. The analysis of crash frequency focussed on the two predominant types of left-turn crashes found at intersections approaches that have PPLT signal designs: collisions between left-turning and opposing through vehicles, and rear-end collisions between left-turn vehicles.

6 Crash Data Analysis Working Paper 6 September 2002 Page 6 The five PPLT signal designs evaluated by Bonneson and McCoy were: 1) Exclusive horizontal PPLT display centered on the left-turn lane. The red ball and green arrow were not illuminated at the same time. 2) Exclusive cluster PPLT display centered on the left turn lane. The red ball and green arrow were illuminated at the same time. 3) Exclusive vertical PPLT display centered on the left turn lane. The red ball and green arrow were illuminated at the same time. 4) Shared cluster PPLT display centered between the left-turn lane and the adjacent through lane. There were two 3-section vertical displays for the through movements. The red ball and green arrow were illuminated at the same time. 5) Shared horizontal PPLT display centered between the left-turn lane and the adjacent through lane. There were two 3-section horizontal displays for the through movement. The red ball and green arrow were illuminated at the same time. Crash histories of 16 intersections, representing 53 study approaches, were evaluated by calculating the average crash rate by the display design. Crash frequency was balanced against the degree of exposure using the following equation: 4 10^6 LeftTurn crashes Average Crash Rate = 365 years total approaches studied total entering ADT ) EQ 1 Using this equation, the authors evaluated the exposure to PPLT-related crashes at an intersection to the number of approaches with PPLT designs, the number of years, the left-turn traffic demand, and the conflicting demand. This ratio was expressed in terms of left-turn crashes per million vehicles entering the intersection. The roadway ADT ranged from 5,600 to 30,500. The average crash rate was computed for each of the five PPLT signal displays. The crash rate ranged from 0.28 to 0.61.

7 Crash Data Analysis Working Paper 6 September 2002 Page 7 This study concluded that there were no significant differences in crash frequency among the various PPLT design types. The Washington Section of ITE conducted a comprehensive evaluation of the flashing yellow ball display and reported the results in a 1985 study report (5). Ron Cameron, the Traffic Engineer for the City of Everett, WA. chaired the Washington State Flashing Yellow Protected/Permissive Signal Evaluation Committee. The Committee supported the flashing yellow ball indication because it provided warning message to the motorist and to proceed with caution. The flashing yellow indication was different in color (from the green ball) and operation. The visual difference between the flashing yellow and circular green removed the chance of an approaching motorist not distinguishing between the adjacent green arrow and circular green. The Washington Section ITE study was conducted with the assistance from more than 50 Washington State traffic engineers evaluating crash and conflict studies and motorist questionnaires. The before and after crash study of left turning traffic (20 intersections) representing intersections converted from green arrow protected/permissive green ball to green arrow/flashing yellow ball permissive. The study reported a 34 percent decrease in total left-turn crashes. The ITE study also analyzed 32 intersections using a crash statistic which computed the number of left turn crashes divided by the left-turn and opposing through and right turning traffic volume (in millions). Crash rates for 19 green ball protected/permissive intersections and 13 flashing yellow protected/permissive intersections were calculated to be: 0.89 for the green ball PPLT 0.49 for the flashing yellow PPLT The ITE Committee concluded based upon the above reported results and other study results (survey, etc.) that the flashing yellow ball display used for the PPLT phasing resulted in substantial reduction in motorist delay and fuel. Further, the study showed that the flashing yellow display was safer than the standard green ball permissive indication because of its yellow color warning

8 Crash Data Analysis Working Paper 6 September 2002 Page 8 motorists that the right-of-way has changed, and the flashing operation to clearly distinguish it from the green arrow. Kenneth Agent has conducted several studies over the past 23 years related to the permissive and protected/permissive left turn control (6, 7, 8, 9). His earlier work (6) developed warrants for leftturn phasing. The warrants were based upon crash experience, delay, vehicle volumes and traffic conflicts. In 1979 (7), Agent evaluated protected/permissive left-turn phasing in before and after conditions. The use of PPLT phasing resulted in a 50-percent reduction in left-turn delay and a 24-percent reduction in total delay compared to protected-only phasing. PPLT phasing resulted in an increase in left-turn accidents. In 1985 (8), Agent developed guidelines for the use of PPLT phasing. The 1985 research was based upon traffic speed, number of through lanes, crash history and sight distance. In 1995 (9), Agent published his latest study related to PPLT phasing. The 1995 report identified updated guidelines for the installation of left-turn phasing with emphasis on high-speed areas. Variables considered crash history, traffic volume and delay, traffic speed, number of left-turn lanes, number of opposing lanes, sight distance, intersection geometrics, leftturn volume and opposing volume. In the development of the guidelines, Agent evaluated several crash statistics, including 1) average left-turn crashes per year, 2) average left-turn crashes per 100 left-turn volume, and 3) average left-turn crashes per 100,000 left-turn x opposing through volume. The best relationships were found using the product of left-turn and opposing traffic. JHK (10) studied signal displays for left-turn control in the mid 1980s. This study was designed to be the most comprehensive study of its kind. The JHK was an ambitious effort to determine if there exists a measurable difference in safety under alternative left-turn control strategies, and more specifically the research effort was focused on the safety associated with the PPLT control. The safety was measured by analyzing historical crash records for a large sample of intersections (360 intersections from across the country) and comparing the differences in accidents with intersections using other forms of left-turn control. The JHK study evaluated intersections in Dallas, Maryland, Montgomery County, Phoenix, Washington, and Michigan. The JHK study focused on answering seven hypotheses related to PPLT phasing, which were:

9 Crash Data Analysis Working Paper 6 September 2002 Page 9 Intersections having PPLT control have more accidents than those that do not. There does not exist a threshold ratio of left-turn to opposing traffic that would indicate the applicability of protected/permissive control. There is no difference in the safety performance for the various signal display configurations. Differences in regional traffic control practices do not affect the performance of the various types of left-turn control. Intersection type has no influence on the performance of protected/permissive left-turn controls. Approach speeds have no influence on the performance of intersections operating under the various forms of left-turn control. Volume is not a factor which influences the safety performance of intersections operating under different forms of left-turn control. The results of the JHK study identified that protected left-turn are the safest for of control, and protected/permissive control is less safe that protected control, but safer than permissive left-turn control. The JHK study made note that their findings support similar findings in the literature, but were significant in that they were derived from an analysis which was considerably larger, more complex (Multiway Contingency Analysis), covering a far greater variety of left-turn control applications (displays) and locations. The JHK study identified several factors that influenced safety, those were 1) the jurisdiction where the intersection was located, the type of left-turn control, the approach volume, and the presence or absence of supplemental signing. Specifically, it was noted that approaches with any form of supplemental signing for left-turn control experience greater crashes than those without

10 Crash Data Analysis Working Paper 6 September 2002 Page 10 such signs; and approaches with traffic volumes greater than 2000 vph experience more crashes than those with fewer than 2000 vph. The JHK study was not successful in identifying which PPLT display used among the various jurisdictions were more or less safe than in other locations, or whether there were geographic influences on the safety of various forms of left-turn control The select literature review identified several key findings related to PPLT phasing, and those are: Hummer (1) identified that the crash frequency is higher for PPLT intersections with leading left-turns compared with lagging left-turns. However, Upchurch (2) identified this was true for intersections with three opposing lanes of traffic. Upchurch identified that the lagging PPLT had the worst crash record when there was two opposing lanes of traffic. Almost all literature shows that the leading protected left-turn phasing has the lowest crash rate (2, 10). Upchurch (2) and Hauer, et al (3) both identified that crash frequency relationship to traffic demand is nonlinear. Bonneson and McCoy (4)identified that there was no statistical difference in crash frequency among the most common PPLT display arrangements. The Washington Section of ITE (5) identified that the flashing yellow ball display was safer than the green ball display. Agent (6, 7, 8) identified that the use of PPLT phasing can reduce left-turn delay by 50 percent and total delay by 24 percent compared to protected-only phasing. While not all reports agree with one another, the general findings related to the use in PPLT phasing, in aggregate, suggest the following: 1) vehicle delay decreases, fuel usage decreases, vehicle progression is improved, and vehicle crashes increase. The use in

11 Crash Data Analysis Working Paper 6 September 2002 Page 11 PPLT phasing should be applied on a case-by-case basis because not all intersections [approaches] are candidates for PPLT phasing. Crash Data Analysis The following sections detail the development of the crash data analysis, including site selection, data sources, and reduction of the crash data. Study Intersection Selection For the purpose of this study, the Research Team identified three sources of crash data for analysis. First, crash data were obtained from the same three intersections studied in the operational and conflict studies, yielding 24 PPLT study site intersections. Specifically, crash data was obtained for each of the following eight geographic regions of the U.S.: College Station and Dallas, Texas; Portland, Oregon; Seattle, Washington; Detroit, Michigan; Cupertino, California; Dover, Delaware; and Orlando, Florida. The crash data was requested for the most recent three years. The second source of crash data was from the network of volunteers identified through the Agency Survey. Without exception, this data represented the green ball permissive display allowed in the MUTCD. For the third source of crash data, the Research Team evaluated the database created by JHK Associates in 1988 as part of a previous study of PPLT displays. This third source of data was identified as a potential source of historical data in that some of those intersections were thought to still be in operation as they were in The Research Team intended to use the information in the database as additional analysis locations and thus as new data points or for comparative analysis. Appendix B provides a list of the intersections from the JHK database as identified in the after condition of the study. To successfully use the JHK database, a given intersection needed to 1) still be using the same PPLT display, and 2) remain unchanged geometrically. Based on a review of the JHK database and

12 Crash Data Analysis Working Paper 6 September 2002 Page 12 discussions with transportation engineers in the respective study intersections, none of the intersections in the JHK database were found to be both using the same PPLT display and the same intersection geometry. Because these two criteria were not met, no further analysis of the JHK database was conducted. Method of Analysis PPLT Crash Data Worksheet Each agency that supplied crash data for this study completed the PPLT Crash Data Worksheet that was supplied by the Research Team (Appendix C). The data supplied in the Worksheet identified key information related to the study intersection including the location, the date which PPLT was installed, the intersection ADT, and the dates for which crash data were being furnished. The Worksheet identified by intersection approach the peak hour volume, lane width, number of lanes, whether the lane is shared. This information was furnished for both the left-turn lane and the through lanes. The Worksheet identified the number of left-turn related accidents, the permitted signal indication, the PPLT display design, whether the traffic signal is actuated or pretimed, and the posted speed limit. This information was provided by intersection approach. Crash Statistic The literature does not support one single method of analyzing crash data. Researchers such as Hummer and Upchurch have used crashes per million left turn vehicles, Williams based his study crash totals, and the JHK study evaluated total crashes using the odd ratio. When crash data is used as a predictor, the literature (6, 7, 8, 9, 11) supports the use of left-turn accidents per 100,000 left-turn and opposing volume vehicles. Bonneson developed a unique way of calculating the average crash rate based upon on the following equation ^6 LeftTurn crashes Average Crash Rate = 365 years total approaches studied total entering ADT ) Eq: 1

13 Crash Data Analysis Working Paper 6 September 2002 Page 13 Equation 1 computes the average annual left-turn accident rate per million vehicles entering the intersection. This rate represents the overall average accident rate for the PPLT design type, calculated as the average of the intersection accident rates. In the context of study, the exposure to PPLT-related crashes at an intersection can be related to the number of approaches with PPLT designs, the number of years, the left-turn traffic demand, and the conflicting demand. After careful evaluation of methods used in the literature and discussions with many of those authors 1, it was determined that the best method to use would be a multiple methodologies to see if the same trend becomes apparent. Analysis would also be conducted to identify relationships with the conflict analysis results. NCHRP 3-54 Study Intersection Data The crash data from each of the 24 PPLT study sites were compiled into a spreadsheet database. Depending on the availability of data, the database contained multiple study site parameters related to signal display arrangement, placement, traffic volume, operating speeds, PPLT installation date, crash reporting thresholds, etc.. A summary of the 24 PPLT study intersections data is shown in Appendix D. Crash Data Analysis The crash frequency at a given intersection was first analyzed using Bonneson s method (shown as Equation 1). This approach balances crash frequency against the degree of exposure to crashes to make comparisons among the various PPLT displays. This relative comparison compares the extent of safety, or risk, for each PPLT display. The exposure to PPLT related crashes at an intersection was related to the number of approaches considered with specific PPLT signal displays, the number of years of crash data, the left-turn traffic demand, and the opposing traffic. Tables 1 and 2 present a summary of the left-turn crash locations, traffic volumes, and crash data. 1 Charley Zegeer, Kenneth Agent, and James Bonneson

14 September 2002 Page 14 City Dallas, TX Dover, DE Oakland County, MI College Station, TX Seattle, WA Portland, OR Intersection Table 1 Summary of Study Locations and Crash Data PPLT Display Type 1 PPLT Approaches Left-turn Crashes North-South ADT East-West ADT Average Crash Rate 2 Lovers Skillman Ave. 5-Vertical NB, SB, EB, WB 23 50,600 24, Mockingbird Skillman Ave. 5-Horizontal NB, SB, EB, WB 15 20,500 35, Buckner Garland Rd. 5-Horizontal NB, SB, EB, WB 36 36,200 38, Highway Court Street 4-Cluster NB, SB, EB, WB 13 22,380 7, Highway East Landing Rd. 4-Cluster NB, SB 6 27,360 14, Highway Little Creek Rd. 4-Cluster WB, SB 4 30,220 5, Maple Orchard Lake Rd. 3-Vertical NB, SB, EB, WB 51 52,290 28, Mile Orchard Lake Rd. 3-Vertical NB, SB, EB, WB 8 39,250 28, Mile Orchard Lake Rd. 3-Vertical NB, SB, EB, WB 46 43,800 21, University College Ave. 5-Horizontal EB, WB 25 11,900 81, Southwest Texas Ave. 5-Horizontal NB, SB, EB, WB 36 14,800 10, Southwest Southwood Dr. 5-Cluster WB, NB , South Lander 1 st Ave. 4-Vertical NB, SB 11 17,800 3, South Lander 4 th Ave. 4-Vertical NB, SB 4 21,130 9, Fairview Republican Street 4-Vertical NB, SB ** 16, ** Oleson Vermont Street 5-Cluster NB, SB 2 9,300 4, NW Murray Science Park 5-Cluster NB, SB 10 21,550 1, La Bonita 72 nd Street 5-Cluster NB, SB, EB, WB 13 14,780 10, Cupertino, CA Orlando, FL Stevens Creek Torre Drive 4-Vertical EB, WB 4 2,580 26, Stevens Creek Portal Ave. 4-Vertical EB, WB 6 3,550 31, Orange Blossom Princeton 5-Cluster SB 14 32,390 17, Orange Kaley Street 5-Cluster NB, SB, EB 8 36,670 15, Orange Michigan Street 5-Cluster NB, SB, EB, WB 23 40,280 42, Number of signal display sections (3, 4, or 5) - arrangement (Horizontal, Vertical, or Cluster) Table Updated 9/10/ Average annual left-turn crash rate per million vehicles entering the intersection. Crash Rate = [4 10^6 LT Crashes] / [365 years total approaches total entering ADT] **Note: Crash data not yet available due to computer problems at the Washington State Highway Patrol, additional information pending.

15 September 2002 Page 15 City Portland Seattle Dallas Table 2 Summary of Average Crash Rate College Station Orlando Dover Oakland County Cupertino Display Type 5C GB 4V FYB 5H & 5V 5H & 5C 5C GB 4C FRA 3V FRB 4V FRA Crash Rate Range Lowest Highest Average Standard Dev Table Note: Average Crash Rate as shown at the bottom of Table 1. Figure 1 graphically illustrates the data contained in Table 1 by city. Figure 2 then illustrates the same data by display type. Figure 1 Average Crash Rate by Location at NCHRP 3-54 Study Intersections 1.40 Crash Rate at NCHRP 3-54 Study Intersections Crash Rate Portland Seattle Dallas College Station Study City Orlando Dover Detroit Cupertino - Denotes Average

16 September 2002 Page 16 Figure 2 Average Crash Rate By Display Type At NCHRP 3-54 Study Intersections C GB 4V FYB 5V 5H 4C FRA 3V FRB 4V FRA Crash Rate Display Type - Denotes Average Figure 2 shows that the 4-section vertical flashing red arrow display (located in Cupertino, California) had the lowest average crash rate among the study intersections and the five-section horizontal had the highest average crash rate. While the data in Figure 2 suggest a relationship between crashes and display type, a comparison of the mean crash rates for each display type using a t-statistic determined that there was no statistically significant difference between the results at a 95 percent level of confidence. Alternative Crash Analysis The research team also analyzed the crash data using methods established by Kenneth Agent (6, 7, 8, 9). Agent calculated crash rates based on the number of left-turn crashes per 100,000 left-turn vehicles multiplied by the opposing flow. The equation used by Agent is: Average Crash Rate = Left-turn Crashes per 100,000 left-turns opposing flow EQ: 2

17 September 2002 Page 17 Results The results of the crash data analysis using the methodology employed by Agent are shown in Table 3. As indicated in the table, the analysis results using Agent s method (9) yield a different outcome than what was identified using Bonneson s methodology. The data in Table 3 shows that the flashing yellow ball used in Seattle yields the lowest crash statistic and the green ball display used in College Station has the highest. A rank order is shown in Table 4.

18 September 2002 Page 18 City Dallas, TX Dover, DE Oakland County, MI College Station, TX Seattle, WA Portland, OR Intersection Table 3 Summary of Study Locations and Crash Data PPLT Display Type 1 PPLT Approaches Left-turn Crashes Average Crash Rate 2 Lovers Skillman Ave. 5-Vertical NB, SB, EB, WB Mockingbird Skillman Ave. 5-Horizontal NB, SB, EB, WB Average Crash Rate by City Buckner Garland Rd. 5-Horizontal NB, SB, EB, WB Highway Court Street 4-Cluster NB, SB, EB, WB Highway East Landing Rd. 4-Cluster NB, SB Highway Little Creek Rd. 4-Cluster WB, SB Maple Orchard Lake Rd. 3-Vertical NB, SB, EB, WB Mile Orchard Lake Rd. 3-Vertical NB, SB, EB, WB Mile Orchard Lake Rd. 3-Vertical NB, SB, EB, WB University College Ave. 5-Horizontal EB, WB 25 * Southwest Texas Ave. 5-Horizontal NB, SB, EB, WB Southwest Southwood Dr. 5-Cluster WB, NB South Lander 1 st Ave. 4-Vertical NB, SB South Lander 4 th Ave. 4-Vertical NB, SB Fairview Republican Street 4-Vertical NB, SB ** ** 0.87 Oleson Vermont Street 5-Cluster NB, SB NW Murray Science Park 5-Cluster NB, SB La Bonita 72 nd Street 5-Cluster NB, SB, EB, WB Cupertino, CA Orlando, FL Stevens Creek Torre Drive 4-Vertical EB, WB Stevens Creek Portal Ave. 4-Vertical EB, WB Orange Blossom Princeton 5-Cluster SB 14 * Orange Kaley Street 5-Cluster NB, SB, EB Orange Michigan Street 5-Cluster NB, SB, EB, WB Number of signal display sections (3, 4, or 5) - arrangement (Horizontal, Vertical, or Cluster) 2 Crash Rate = Left-turn Crashes per 100,000 left-turns opposing flow *Note: Left-turn traffic volume data not available. **Note: Crash data not yet available due to computer problems at the Washington State Highway Patrol, additional information pending.

19 September 2002 Page 19 Table 4. Rank Order by Display Type Average Crashes per 100,000 Left-Turns Opposing Vehicles Rank Order Display Location 1 Flashing Yellow Ball Seattle 2 Flashing Red Arrow Cupertino 3 Green Ball Orlando Flashing 4 Flashing Red Ball Oakland County 5 Flashing Red Arrow Delaware 6 Green Ball Portland 7 Green Ball Dallas 8 Green Ball College Station Evaluating the data using yet another crash statistic, average left-turn crashes per year, also indicates that the flashing yellow ball used in Seattle has the lowest crash rate while the flashing red ball used in Oakland County has the highest rate. A rank order is shown in Table 5. Rank Order Table 5. Rank Order by Display Type Average Left-Turn Crashes per Year Display Location 1 Flashing Yellow Ball Seattle 2 Flashing Red Arrow Cupertino 3 Flashing Red Arrow Delaware 4 Green Ball Portland 5 Green Ball Orlando 6 Green Ball Dallas 7 Green Ball College Station 8 Flashing Red Ball Oakland County The crash data were also analyzed by calculating the average number of left-turn crashes per 100 left-turning vehicles. The rank order results of this analysis are presented in Table 6.

20 September 2002 Page 20 Table 6. Rank Order by Display Type Average Left-Turn Crashes per 100 Left-Turn Vehicles Rank Order Display Location 1 Flashing Yellow Ball Seattle 2 Green Ball Portland 3 Green Ball Orlando 4 Flashing Red Arrow Cupertino 5 Flashing Red Arrow Delaware 6 Green Ball Dallas 7 Flashing Red Ball Oakland County 8 Green Ball College Station Table 7 summarizes the findings of the four respective analysis methodologies. Table 7 suggests that no single left-turn display presents itself as having a better safety record. Further, none of the results obtained using the respective analysis procedures correspond to the results identified through the conflict study (which identified a rank order of Flashing Yellow Ball (1), Flashing Red Arrow, Flashing Red Ball, Green Ball (4)). Rank Order Table 7. Summary of Rank Order by Display Type by Analysis Method Bonneson s Method Display/Location by Analysis Method Average Crashes per 100,000 Left-Turn Opposing Vehicles Average Left-Turn Crashes per Year Average Left-Turn Crashes per 100 Left- Turn Vehicles 1 FRA Cupertino FYB Seattle FYB Seattle FYB Seattle 2 FRA Delaware FRA Cupertino FRA Cupertino GB Portland 3 GB Dallas GB Orlando Flashing FRA Delaware GB Orlando 4 FYB Seattle FRB Oakland County GB Portland FRA Cupertino 5 FRB Oakland County FRA Delaware GB Orlando FRA Delaware 6 GB Orlando Flashing GB Portland GB Dallas GB Dallas 7 GB Portland GB Dallas GB College Station FRB Oakland County 8 GB College Station GB College Station FRB Oakland County GB College Station The variability of the results presented in Table 7 demonstrates that comparing signal displays using crash data statistics is sensitive to the analysis procedure. Crash data analysis is a useful tool

21 September 2002 Page 21 in monitoring the safety record of an intersection over time and identifying how improvements affect the safety of the intersection in a before- and after comparison. The ability to effectively compare different signal displays using data from different parts of the country (and even within the same region) is more limited. No conclusions with respect to PPLT signal display type can be drawn based upon the data analyzed above. Volunteer Network Intersection Data Crash data were received from agencies across the country and resulted in representation of areas including the states of California, Georgia, North Carolina, Texas, Washington, and Wisconsin. A summary of the crash data is shown in Appendix E. Table 8 presents a summary of the left-turn crash locations, traffic volumes, and crash data that were obtained through the volunteer network as well as the associated crash rate using Bonneson s analysis methodology. Table 9 provides key statistics related to the volunteer crash data while Figure 3 illustrates the same data by display type.

22 Crash Data Analysis Working Paper 6 September 2002 Page 23 State City Intersection CA Modesto Table 8 Summary of Volunteer Crash Data PPLT Display Type 1 PPLT Approaches Left-turn Crashes North-South ADT East-West ADT Average Crash Rate 2 Orangeburg 5-Cluster NB, SB, EB, WB 31 23,420 19, Orangeburg 5-Cluster NB, SB, EB, WB 50 34,815 12, Claus Creekwood Dr 5-Cluster NB, SB, EB, WB 7 20,020 10, Tully 5-Cluster NB, SB, EB, WB 35 12,520 15, Tully 5-Cluster NB, SB, EB, WB 30 12,955 31, Prescott 5-Cluster NB, SB, EB, WB 55 15,935 30, Dale Snyder Ave 5-Cluster NB, SB, EB, WB 12 4,670 6, Oakdale Wylie Dr 5-Cluster NB 2 31,715 5, Floyd Oakdale Rd 5-Cluster NB, SB, EB, WB 84 23,890 11, Briggsmore College Ave 5-Cluster NB, SB, EB, WB 20 9,820 31, Oakdale Sylvan Ave 5-Cluster NB, SB, EB, WB 47 21,915 18, Briggsmore Coffee Rd 5-Cluster NB, SB, EB, WB 27 24,970 28, Carpenter Kansas Ave 5-Cluster NB, SB, EB, WB 65 20,680 14, Standiford Carver Rd 5-Cluster NB, SB, EB, WB 21 7,175 31, Carver Orangeburg Ave 5-Cluster NB, SB, EB, WB 8 8,570 16, Tully Orangeburg Ave 5-Cluster NB, SB, EB, WB 9 16,085 17, College Orangeburg Ave 5-Cluster NB, SB, EB, WB 13 9,870 17, Carpenter Blue Gum Ave 5-Cluster NB, SB, EB, WB 26 32,710 13, Coffee Floyd Ave 5-Cluster NB, SB, EB, WB 23 24,415 10, Coffee Rumble Rd 5-Cluster NB, SB, EB, WB 16 24,415 8, Scenic Bodem St 5-Cluster NB, SB, EB, WB 18 6,625 29, Standiford Conant Ave 5-Cluster NB, SB, EB, WB 22 3,810 25, GA Duluth Satellite Tandy Ken Ln 5-Cluster WB 2 1,105 41, GA Lawrenceville Cruse Herrington Rd 5-Cluster EB, WB 1 22,960 29, GA Lilburn Indian Trail Oakbrook Pkwy 5-Cluster NB, SB Jimmy Carter Tracy Valley Dr 5-Cluster EB, WB Singleton Thompson Pkwy 5-Cluster EB NC Cary NC House Road 5-Cluster NB, SB, EB, WB 11 Net ADT =21, Number of signal display sections (3, 4, or 5) - arrangement (Horizontal, Vertical, or Cluster) 2 Average annual left-turn crash rate per million vehicles entering the intersection. Crash Rate = [4 10^6 LT Crashes] / [365 years total approaches total entering ADT]

23 September 2002 Page 24 State City Intersection NC TX Raleigh Amarillo Table 8 (Continued) Summary of Volunteer Crash Data PPLT Display Type 1 PPLT Approaches Left-turn Crashes North-South ADT East-West ADT Average Crash Rate 2 Six Forks Newton Road 5-Cluster SB 20 Net ADT =39, Wake Forest Whitaker Mill Rd 5-Cluster NB, SB, EB, WB 56 Net ADT =34, Atlantic Wolfpack Ln 5-Cluster EB, WB 2 48,430 4, Neuse Newton Road 5-Cluster NB 8 Net ADT =23, Wolflin 5-Horizontal WB, EB 4 27,070 6, rd 5-Vertical NB, SB, EB, WB 5 13,170 8, th 5-Vertical WB, EB 4 5,830 18, TX Garland Belt Line 5-Vertical NB, SB, EB, WB 10 21,270 32, Northwest Hwy 5-Vertical NB, SB, EB, WB 12 27,925 40, Buckingham 5-Vertical NB, SB, EB, WB 9 24,000 40, WA SR 99 Jet SR 599 / S 116th 5-Cluster NB, SB 31 17,000 7, WI WI WI Fond Du Lac County Kenosha County Milwaukee County USH CTH "VVV" 5-Vertical WB 2 10,015 4, STH STH 75/83 5-Vertical WB 9 7,200 19, STH STH Vertical NB, SB, EB, WB 18 26,070 14, STH CTH "K" 5-Vertical SB 1 26,940 8, STH STH 192/CTH "H" 5-Vertical WB 13 7,835 27, STH 60 th Ave 5-Cluster EB, WB 14 5,820 26, Silver Spring PT. Washington Rd 5-Cluster SB, EB, WB 15 28,615 26, STH 181 (76 th Fond Dul Lac Ave 5-Vertical SB 13 25,815 5, STH 100 (Mayfair Watertown Plnk 5-Vertical NB, SB, EB, WB 31 37,535 18, STH STH 59 5-Vertical NB, SB, EB, WB 56 34,895 33, STH National Ave 5-Vertical EB, WB 4 34,740 20, STH STH 24 5-Vertical EB, NB 29 39,320 18, STH 36 (W. Loomis STH 100 (S. Lovers Lane Rd) 5-Vertical EB 0 9,545 10, USH 41 (27th Layton Ave 5-Vertical EB, WB 13 38,505 22, Number of signal display sections (3, 4, or 5) - arrangement (Horizontal, Vertical, or Cluster) 2 Average annual left-turn crash rate per million vehicles entering the intersection. Crash Rate = [4 10^6 LT Crashes] / [365 years total approaches total entering ADT]

24 September 2002 Page 25 State City Intersection WI Milwaukee County Table 8 (Continued) Summary of Volunteer Crash Data PPLT Display Type 1 PPLT Approaches Left-turn Crashes North- South ADT East-West ADT STH 38 (S. Howell STH 100 (Ryan Rd) 5-Vertical NB, SB, EB, 21 17,070 18, Average Crash Rate 2 STH Rawson Ave 5-Vertical EB, WB 7 17,695 20, USH 41 (W. Appleton W Hampton Ave 5-Vertical NB, SB 2 19,000 15, STH W. Burleigh St 5-Vertical EB 4 28,645 20, USH 41 (S 27th W Howard Ave 5-Vertical NB, SB, WB 22 37,785 12, STH Hampton Ave 5-Vertical WB, EB 4 12,170 20, STH Lincoln Ave 5-Vertical NB, SB, WB 24 39,415 15, STH 38 (Howell College Ave 5-Vertical NB, SB, EB, WB 24 21,790 18, USH N 91st St 5-Vertical SB 5 17,000 18, STH Drexel Ave 5-Vertical NB, SB, EB 11 25,190 9, STH W. Layton Ave 5-Vertical NB, SB, EB 19 34,820 13, Hampton Port Washington Rd 5-Vertical NB, SB, EB 15 20,345 14, STH 190 (W. Capitol N 124th St 5-Vertical NB 4 17,385 49, STH Cleveland Ave 5-Vertical NB, SB, EB, WB 20 38,785 18, STH W Center St 5-Vertical NB, SB 13 39,950 6, STH W Good Hope Rd 5-Vertical NB, SB, EB, WB 28 15,215 27, STH Theodore Trecker Rd 5-Vertical NB, SB 2 33,405 5, STH W Mill Rd 5-Vertical NB, SB, EB, WB 22 33,235 15, STH 181 (N 76th W Florist Ave 5-Vertical SB 5 33,175 4, STH 100 (W Brown Deer N 51st St 5-Vertical EB, WB 9 5,850 32, STH 57 (N Green Bay W Bender Rd 5-Vertical SB 2 19,735 6, STH W Bradley Rd 5-Vertical NB, SB, EB, WB 12 35,590 12, N Port Washington Bender Rd 5-Vertical NB, EB 11 17,220 7, STH 100 (W Brown Deer Northridge Driveway 5-Vertical EB, WB 20 7,430 33, STH 100 (W Brown Deer 85th St 5-Vertical EB, WB 15 7,420 36, STH 181 (N 76 W Acacia St 5-Vertical SB 8 32,260 2, STH 100 (S 108th Edgerton Ave 5-Vertical NB, SB 11 46,205 5, STH 100 (W Brown Deer N 107th St 5-Vertical WB 11 14,940 24, Number of signal display sections (3, 4, or 5) - arrangement (Horizontal, Vertical, or Cluster) STH W Dean Rd 5-Vertical NB 12 29,395 5, Average annual left-turn crash rate per million vehicles entering the intersection. Crash Rate = [4 106 LT Crashes] / [365 years total approaches total entering ADT]

25 September 2002 Page 26 State City Intersection WI WI WI Milwaukie County (continued) Ozaukee County Racine County Table 8 (Continued) Summary of Volunteer Crash Data PPLT Display Type 1 PPLT Approaches Left-turn Crashes North- South ADT East-West ADT Average Crash Rate 2 STH Deerwood Dr 5-Vertical NB, SB 19 22,065 7, STH 100 (W Brown Deer N 64th St 5-Vertical EB 1 4,220 38, STH College Ave/Industrial Loop 5-Vertical SB 2 15,325 3, STH 181 (N 176th Calumet Rd 5-Vertical NB, SB 8 40,505 4, STH Kildeer Ct 5-Vertical EB 6 3,270 30, STH STH Vertical NB, SB, EB, WB 24 20,850 26, STH STH Vertical EB, WB 13 17,550 20, STH STH 11 5-Vertical NB, SB, EB, WB 35 24,900 23, STH STH 38 5-Vertical NB, SB, EB, WB 20 12,980 16, STH CTH "C" 5-Vertical SB, EB, WB 11 25,705 14, STH 3 Mile Rd 5-Vertical NB 1 14,525 7, STH South Entrance 5-Vertical NB, SB 7 32,925 3, STH 21st St 5-Vertical EB, WB, SB 12 31,445 9, STH Oakes Rd 5-Vertical WB 6 4,510 26, WI Washington Co STH CTH "K" 5-Vertical EB, WB 2 6,300 21, WI Wiukesha Co STH Moorland Rd 5-Vertical NB, SB, EB, WB 50 40,155 20, USH Elm Grove 5-Vertical EB, WB, SB 12 7,935 35, STH Brookfield Rd 5-Vertical EB, WB 6 7,320 40, STH Sunny Slope Rd 5-Vertical WB 1 6,650 18, STH Fountain Blvd/Stanley Dr 5-Vertical EB 1 4,880 22, UH Sunny Slope 5-Vertical NB, WB 8 8,305 31, STH CTH "J" 5-Vertical NB, SB, EB, WB 17 9,255 19, USH Corporate Dr 5-Vertical EB, WB 10 5,670 52, STH 190 Capitol N 128th St 5-Vertical NB, SB, EB, WB 15 8,230 45, Number of signal display sections (3, 4, or 5) - arrangement (Horizontal, Vertical, or Cluster) 2 Average annual left-turn crash rate per million vehicles entering the intersection. Crash Rate = [4 10^6 LT Crashes] / [365 years total approaches total entering ADT]

26 September 2002 Page 27 Table 9 Summary of Key Crash Data Statistics From Volunteer Data Display Type 5C GB 5V GB Crash Rate Lowest 0 0 Range Highest Average Standard Dev Figure 3 Crash Rate at Volunteeer Data Intersections Crash Rate C GB Display Type 5V GB - Denotes Average The volunteer data summarized in Tables 8 and 9 and illustrated in Figure 3 suggest that the fivesection vertical display had a slightly lower average crash rate than the five-section cluster display. While the data in Table 9 and Figure 3 suggest a potential relationship between crashes and display type, a comparison of the mean crash rates for the five-section cluster and the five-section vertical displays using a z-statistic determined that there was no statistically significant difference between the results at a 95 percent level of confidence.

27 September 2002 Page 28 Limitations of Crash Analysis During the course of reviewing the crash data, concern was raised as to whether the variability in local and intersection specific conditions was affecting the analysis results, especially considering the small sample size for the study intersections. To test this concern, the data obtained from Milwaukee County, Wisconsin was analyzed to evaluate whether small sample sizes would skew the net result. This data was all collected in the same county and all of the data represent fivesection vertical PPLT displays. The Milwaukee County data was randomly subdivided into sets of seven data points to evaluate as shown in Table 10.

28 September 2002 Page 29 Intersection Table 10 Variability within Common Crash Data Silver Spring PT. Washington Rd 0.33 STH 181 (76 th Fond Dul Lac Ave 1.53 STH 100 (Mayfair Watertown Plnk 0.51 STH STH STH National Ave 0.13 STH STH Average Crash Rate 1 Average Standard Devaiation STH 36 (W. Loomis STH 100 (S. Lovers Lane Rd) USH 41 (27th Layton Ave 0.39 STH 38 (S. Howell STH 100 (Ryan Rd) 0.73 STH Rawson Ave 0.34 USH 41 (W. Appleton W Hampton Ave 0.10 STH W. Burleigh St 0.30 USH 41 (S 27th W Howard Ave 0.53 STH Hampton Ave STH Lincoln Ave 0.53 STH 38 (Howell College Ave 0.54 USH N 91st St 0.52 STH Drexel Ave 0.39 STH W. Layton Ave 0.48 Hampton Port Washington Rd 0.53 STH 190 (W. Capitol N 124th St STH Cleveland Ave 0.32 STH W Center St 0.51 STH W Good Hope Rd 0.60 STH Theodore Trecker Rd 0.09 STH W Mill Rd 0.41 STH 181 (N 76th W Florist Ave 0.48 STH 100 (W Brown Deer N 51st St STH 57 (N Green Bay W Bender Rd 0.28 STH W Bradley Rd 0.23 N Port Washington Bender Rd 0.80 STH 100 (W Brown Deer Northridge Driveway 0.89 STH 100 (W Brown Deer 85th St 0.62 STH 181 (N 76 W Acacia St 0.84 STH 100 (S 108th Edgerton Ave STH Kildeer Ct 0.65 STH 100 (W Brown Deer N 107th St 1.02 STH W Dean Rd 1.27 STH Deerwood Dr 1.19 STH 100 (W Brown Deer N 64th St 0.08 STH College Ave/Industrial Loop 0.38 STH 181 (N 176th Calumet Rd Note: (1) Crash Rate = [4x10^6 x LT Crashes]/[365xyears x total approaches x total entering ADT]

29 September 2002 Page 30 As shown in Table 6, the average crash rate for the seven-intersection subsets ranged from 0.22 to This compares to average rate of 0.52 for the full data set. Accordingly, it can be concluded that there is a great deal of variability among the data even though it is from the same general area and represents the same signal display type. Such variability among common data, in conjunction with the small sample size of the study intersection data, suggests that the crash data can provided only very limited insight into the performance of the various PPLT displays and should be evaluated accordingly. It should be further recognized that, as data is collected across the country, there are additional variables introduced. For example, multiple factors influence driver understanding of the correct right-of-way at an intersection. Local conditions and driver understanding of intersection control can be affected by the propensity of traffic signals, and, in turn familiarity with a given signal s meaning. Crash reporting thresholds can also affect the calculated crash rate. The cost at which a crash is considered reportable in a given jurisdiction was found to vary within the study data; some jurisdictions reported accidents involving $500 of damage or more while others had a minimum damage threshold of $1,000. Such threshold differences have the potential to affect the number of reported crashes and, hence, the crash rate. Differences in source data for traffic volumes also are known to affect the crash rate of the study date. For example, some of the traffic volume data that were obtained by the participating agencies was limited to peak hour counts that had to be factored to estimate ADT. Each of these dynamic factors contribute to the differences among crash data and make the determination of any one variable that affects safety (such as PPLT display type) difficult. Summary The select literature review identified several key findings related to PPLT phasing, and those are: One author identified that the crash frequency is higher for PPLT intersections with leading left-turns compared with lagging left-turns. However, other authorsidentified this was true for intersections with three opposing lanes of traffic. It was further identified that