EFFECTIVENESS OF COUNTDOWN PEDESTRIAN SYSTEMS IN DOWNTOWN SAN DIEGO. A Thesis. Presented to the. Faculty of. San Diego State University

EFFECTIVENESS OF COUNTDOWN PEDESTRIAN SYSTEMS IN DOWNTOWN SAN DIEGO A Thesis Presented to the Faculty of San Diego State University In Partial Fulfillment of the Requirements for the Degree Master of Science in Civil Engineering by Vinay Verma Spring 2012

iii Copyright 2012 by Vinay Verma All Rights Reserved

iv DEDICATION. To My Sister Kavita Verma

v ABSTRACT OF THE THESIS Effectiveness of Countdown Pedestrian Systems in Downtown San Diego by Vinay Verma Master of Science in Civil Engineering San Diego State University, 2012 In California, 6,957 pedestrians were killed during 2000 to 2009, resulting in a fatality rate of 2.0 deaths per 100,000 residents. Approximately one quarter of all fatalities occurs at urban intersections, and the main cause of fatalities is improper crossing. Pedestrians misunderstanding of pedestrian signal indications at crossings is identified in the literature as a contributing factor to improper crossings. To address this problem and potentially increase the safety at signalized intersection crossings, pedestrian countdown signals were created by incorporating a countdown timer that is displayed simultaneously during the flashing DON T WALK (FDW) interval. Countdown pedestrian signals (CPS) are increasingly used as a device for improving safety at signalized intersections the timer counts down the number of seconds remaining until the display of the solid DON T WALK (DW) interval. It has been assumed that this signal design leads to a higher level of pedestrian safety by enabling pedestrians to make better crossing decisions with the added information. That prompted a research project reported in this thesis. A before study was performed on an intersection in downtown San Diego in 2005. An after study of the same pedestrian countdown signal was conducted. That intersection had high pedestrian and vehicular traffic volumes. Pedestrian population was diversified, giving an opportunity to look closer at those groups who are most likely to violate the established crossing rules. The data was collected from August10, 2009 to August 27, 2009, using a videotaping that simultaneously captured pedestrian and the corresponding traffic signal indications. Over the course of the study, a total of 5,504 pedestrians were observed. Major violators are younger males, runners and bicyclists and they together committing 58.6% Violations of total pedestrian violations. The runners and bicyclists are committing Violation Type 4 (illegal entry, illegal exit) in 38.2% of all their crossing episodes and Violation Type 2 (illegal entry, legal exit) in 16.1% of their crossing episodes. Auto traffic does effect the pedestrian violations. On 2nd avenue (short crossing) with higher auto-gap, more violations were recorded as compared to long crossing with lower auto-gap. Another factor influencing the relatively high violation rate on the short crossing is the problematic designs of the deficient length of flashing don t walk on that approach. More violations were recorded during peak official hours than during the next off-peak hour, but the difference was not statistically significant. Violations on short crossing with less auto traffic are consistent. Pedestrian adjust their speed to be on safe side to finish crossing by observing countdown timer on long crossing with higher auto traffic as compared to short crossing with lower auto traffic.

Countdown pedestrian signals appear less effective in places where there is small crossing distance and high auto-gap. After the comparison of results from previous before and after study (3), Violation Type 4 (illegal entry, illegal exit) increased for short crossing (from 12.5% to 20.5%). But Violation Type 4 (illegal entry, illegal exit) for long crossing decreased (from 21.4% to 5.6%). Pedestrians adjusted their speed to be on Violation Type 2 (illegal entry) to avoid Violation Type 4 (illegal entry, illegal exit). vi

vii TABLE OF CONTENTS PAGE ABSTRACT...v LIST OF TABLES... ix LIST OF FIGURES...x ACKNOWLEDGEMENTS... xi CHAPTER 1 INTRODUCTION...1 1.1 Background of the Study...1 1.2 Overview of Pedestrian Signal Systems...1 1.3 Objective of this Study...3 1.4 Organization of this Document...5 2 LITERATURE REVIEW...6 3 SITE DESCRIPTION AND DATA COLLECTION...15 3.1 Site Description...15 3.2 Data Collection...16 3.3 Pedestrian Behavior Observations...18 3.3.1 Data Extraction...18 3.3.2 Definition of Pedestrian Categories...18 3.3.3 Description of Pedestrian Crossing Situations...18 3.3.4 Description of Legal and Illegal Terms for the Intersection...18 3.4 Intersection Geometry...18 3.5 Signal Characteristics...20 3.6 Terms for Individual Crossing Episodes...21 3.7 Data Organization...21 3.8 Exclusion of Violation Type 3...22 4 ANALYSIS AND RESULTS...26 4.1 Performance Measures...26 4.2 Comparison of Violation Proportions (12 Pedestrian Categories)...27

viii 4.2.1 Z-Statistics (Comparison of Proportions)...27 4.2.2 Violation Type 4 Results...28 4.2.3 Violation Type 2 Results...30 4.3 Introduction of New Categories...32 4.4 Chi-Square Analysis...33 4.5 Analysis of Variance (ANOVA)...35 4.6 Analysis of Walking Behavior...39 4.6.1 Identification of Pedestrian Who Adjusted Their Speed...39 4.6.2 Long Crossing Pedestrians Speed Adjustment...39 4.6.3 Short Crossing Pedestrians Speed Adjustment...40 4.7 Auto Gap on 2 nd Avenue...40 4.8 Platooning...41 5 CONCLUSIONS AND FUTURE RECOMMENDATIONS...42 5.1 Summary of Findings...42 5.2 General Conclusions and Recommendations for Further Studies...43 REFERENCES...45 APPENDIX A DATA COLLECTION SAMPLE...47

ix LIST OF TABLES PAGE Table 3.1. Data Collection Days, Time Duration and Crosswalks Directions...17 Table 3.2. Pedestrian Category Definition...19 Table 3.3. Situation Description...19 Table 3.4. Situations Definitions...19 Table 3.5. Crosswalk Lengths...20 Table 3.6. Cycle Length-Broadway...20 Table 3.7. Cycle Length-2 nd Avenue...20 Table 3.8. Description of t 0, t 1, t 2...21 Table 3.9. Example of Data Organization...21 Table 3.10. Example of Data Reduction, Week 1, Monday...22 Table 3.11. Example of Data Reduction, Week 1, Week 2, and Week 3...23 Table 3.12. Example of Data Reduction, Peak/Off-Peak...24 Table 3.13. Example of Data Reduction, Long Crossing and Short Crossing...25 Table 4.1. Summary of Violation Type 4 Results...28 Table 4.2. Table Summary of Violation Type 2 Results...30 Table 4.3. New Categories...33 Table 4.4. Summary of Chi-Square Analysis Results...34 Table 4.5. Summary of Violation Type 4 Results for ANOVA...36 Table 4.6. Summary of Violation Type 2 Results for ANOVA...37 Table 4.7. Violation Type 4 ANOVA Significance Summary...37 Table 4.8. Violation Type 2 ANOVA Significance Summary...38 Table 4.9. Speed Adjustment by Pedestrians on Long Crossings...40 Table 4.10. Speed Adjustments by Pedestrians on Short Crossings...40 Table 4.11. Auto-Gaps on 2 nd Avenue...41

x LIST OF FIGURES PAGE Figure 1.1. Conventional pedestrian signal indications. From left: Steady DW and WALK. The clearance interval is indicated by the flashing UPRAISED HAND or flashing DON T WALK....2 Figure 1.2. Pedestrian countdown signal indications. From left: WALK, FDW and DW. The clearance interval displays the countdown timer concurrent with Flashing UPRAISED HAND or Flashing DON T WALK....4 Figure 1.3. Broadway and 2 nd Avenue intersection traffic signal....5 Figure 3.1. Satellite view of intersection (Google Earth)....15 Figure 3.2. Street view of intersection....16 Figure 3.3. Video-camera locations for video-taping, adapted from Google Earth....17 Figure 4.1. Example of violation Type 4- short crossing (2 nd Avenue)....29 Figure 4.2. Example of violation Type 2- long crossing (Broadway)....31

xi ACKNOWLEDGEMENTS I would like to extend my sincere thanks to Dr. Janusz Supernak, Professor of Civil, Construction and Environmental Engineering and my Thesis Committee Chair for his constant support and encouragement towards the successful completion of my thesis research work. It is with his guidance, experience, kindness, patience and wisdom that have helped me to successfully overcome any difficulties that rose during my research work. He has been an excellent mentor right from the day I joined his research group and has given me valuable advice not only in my research work but has also helped me in shaping my academic and professional career. I would also like to sincerely thank my other thesis committee members Dr. Barbara Bailey from the Department of Mathematics and Statistics and Dr.Robert Dowell from the Department of Civil, Construction and Environmental Engineering for contributing their time for reviewing my thesis and providing valuable advice. I am also thankful to my friends Preetam Borah and Ronak Patel for their timely help during my research work.

1 CHAPTER 1 INTRODUCTION 1.1 BACKGROUND OF THE STUDY According to Statistics from Transportation of America, from 2000 to 2009, 47,700 pedestrians were killed in the United States, the equivalent of a Jumbo jet full of passengers crashing roughly every month (Transportation for America 2012). And in state of California, between 2000 and 2009, 6,957 people were killed while walking in California, which cost the state $29.92 billion. Reducing pedestrian fatalities just by 10% would have saved California $2991.51 million over 10 years. California s overall Pedestrian Danger Index (PDI) is 71, which ranks 16 th out of 50 states, resulting in a fatality rate of 2.0 deaths per 100,000 residents. But the fatality rate for pedestrians within the state population as a whole provides a limited picture about the relative danger for pedestrians in one location compared to another. One of the strategies aimed at improving pedestrian safety at the intersections is introduction of the Countdown Pedestrian Signals (CPS). It could be reasonably expected that display information about the number of seconds remaining for a safe crossing should help pedestrians to make a correct decision whether to start crossing or to wait for the next green signal. It could also help pedestrians to speed up their walking to complete their crossing maneuver in time. Availability of CPS systems created an incentive to study their effectiveness using a specific location in the City of San Diego. This is a purpose of this thesis. 1.2 OVERVIEW OF PEDESTRIAN SIGNAL SYSTEMS A pedestrian signal is a of traffic control signal that allocates the right-of-way for the safe passage of pedestrians at signalized intersections and other locations where pedestrians and vehicular traffic is in conflict. According to the Manual on Uniform Traffic Control Devices (MUTCD), pedestrian signals provide a dedicated phase during which the pedestrian can enter the street on the steady WALK interval and complete crossing the street during

2 the flashing DON T WALK or steady DON T WALK indications (State of California Business, Transportation and Housing Agency, Department of Transportation 2012). These signals may be automatic or activated by pedestrian detectors and manual switches (push buttons). The display consists of a pre-programmed timed sequence of steady WALK, flashing DON T WALK and steady DON T WALK indications. Conventional Pedestrian Signal is shown in Figure 1.1 (State of California Business, Transportation and Housing Agency, Department of Transportation 2012). Figure 1.1. Conventional pedestrian signal indications. From left: Steady DW and WALK. The clearance interval is indicated by the flashing UPRAISED HAND or flashing DON T WALK. Source: State of California Business, Transportation and Housing Agency, Department of Transportation. California Manual on Uniform Traffic Control Devices [MUTCD]. Sacramento: State of California, Department of Transportation, 2012. Countdown pedestrian signals (CPS) provide a flashing display of the reducing number of seconds remaining until the end of the pedestrian change interval. They are being used to as an addition to conventional pedestrian signals. The main idea behind the CPS is that by providing pedestrians with a measure of how much time is available for crossing an intersection; they will be better able to judge whether to cross safely or to delay the crossing decision until the next signal cycle. Theoretically one could expect that the valuable message displayed by CPS should help pedestrians to exit the intersection in time. Prior to the incorporation of the guidelines on CPS into the 2003 MUTCD, the use of CPS had been limited in the United States (State of California Business, Transportation and Housing Agency, Department of Transportation 2012). Since then, information gathered from 35 states, (including the District of Columbia) by Federal Highway Administration

3 Specialists Safety Division in late 2004, indicated that over half of the states surveyed use CPS on state projects, while over two thirds of them permit CPS on local projects. CPS is also used abroad: e.g., in the Netherlands, Germany, Canada and Japan. In some of these countries, a dynamic pedestrian signal is also used to advise pedestrians to walk faster as the remaining pedestrian clearance interval diminishes. The 2003 MUTCD provides the national standards on the use of CPS. The standards became available after several jurisdictions across the United States had already been exploring the value of CPS (State of California Business, Transportation and Housing Agency, Department of Transportation 2012). California and Maryland, for example, trigger their countdown display at the start of the flashing DON T WALK in conformance with the MUTCD. Massachusetts and the District of Columbia begin the countdown on the start of the steady WALK indication. Generally, literature reviewed revealed that variety of approaches have been used to evaluate the CPS, and that those evaluations had diversified objectives. For the most part, however, the emphasis has been on pedestrian behavior due to the CPS and pedestrian acceptance of the CPS. Generally literature suggests that CPS is liked by the public. On the other hand, the Literature is not unanimously conclusive on the positive impact of the CPS on pedestrian Behavior. Countdown pedestrian signals (CPS) are increasingly being used as an added strategy for improving safety at signalized intersections. There are basically two types of applications used in adjacent states and across the USA: 1. Triggering the countdown on the start of the WALK indication, 2. Actuating the countdown only during the flashing DON T WALK indication. There is no consensus on the preferred practice, although the latter is more common and recommended. Countdown Pedestrian signal is shown in Figure 1.2. 1.3 OBJECTIVE OF THIS STUDY Countdown systems are relatively new and research related to their performance is still limited. This prompted an interest for the research reported in this thesis. Generally this research is intended to examine, in a detailed way, the performance of the very first CPS system installed in downtown San Diego. A study was performed on Broadway and 2 nd Avenue. The objective of this study was to evaluate the effect of pedestrian countdown signals on several performance measures, such

4 Figure 1.2. Pedestrian countdown signal indications. From left: WALK, FDW and DW. The clearance interval displays the countdown timer concurrent with Flashing UPRAISED HAND or Flashing DON T WALK. as pedestrians compliance with the pedestrian signal indications and the proportions of pedestrians entering during Walk, FDW, and DW and exit the crosswalk during the DW interval. The following tasks were conducted in support of this objective: A literature review was performed as the basis for comparison of similar studies and findings, A Specific study site was selected because of the fact that the Broadway and 2 nd Avenue intersection was already subject of an earlier study conducted just before and soon after introduction of CPS there (Supernak and Chavez 2005). Figure 1.3 shows traffic signal with countdown timer on Broadway and 2 nd Avenue intersection, Data collection was conducted using video camera, The data were reduced from the video tapes and coded into a spreadsheet format so that results could be summarized and analyzed; and, The data were analyzed using statistical methods to determine whether the CPS systems have the ability to improve safety of various groups of pedestrians and to answer the following questions: 3. How common are violations of each kind? 4. Who are the violators? 5. Where do the violations happen? 6. When do the violations happen? 7. Are violations consistent over time? 8. Do the countdown pedestrian signals reduce the most dangerous violation type 4 (illegal entry and illegal exit)? 9. Do pedestrians adjust their walking behavior to complete their intersection crossing in time?

5 Figure 1.3. Broadway and 2 nd Avenue intersection traffic signal. 1.4 ORGANIZATION OF THIS DOCUMENT The remainder of this thesis is organized as follows: Chapter 2 consists of a literature review of regulations applicable to pedestrian signals as well as a comprehensive review of studies that investigate the applications and influences of both conventional pedestrian signals and countdown signals on pedestrian behavior as well as understanding of the signal indications. Chapter 3 presents the research approach and description of the study, including detailed site descriptions and the methodology for data collection and data reduction. Chapter 4 discusses the Data Analysis for evaluation of the effectiveness of pedestrian countdown signals, the statistical analysis performed and the results obtained. Chapter 5 summarizes the findings and conclusions, and offers recommendations for further study.

6 CHAPTER 2 LITERATURE REVIEW A document that regulates design of both conventional and countdown pedestrian signal in California is Manual of Uniform Traffic Control Devices (MUTCD) (State of California Business, Transportation and Housing Agency, Department of Transportation 2012). According to the 2012 Edition of the California MUTCD (MUTCD 2009 Adoption), Section 4E.04; Federal Highway Administration, 12/16/2009, the conventional pedestrian signal should be compliant with the following sequence of displays: Steady WALK(W), signified by a white silhouette of a person, means that a pedestrian Facing the signal indication is permitted to start to cross the roadway in the direction of the signal indication, possibly in conflict with turning vehicles. Flashing DON T WALK (FDW), signified by a Portland orange flashing upraised hand, means that a pedestrian shall not start to cross the roadway in the direction of the signal indication, but that any pedestrian who has already started to cross on a steady WALKING person (symbolizing WALK) signal indication shall proceed out of the traveled way. Steady DON T WALK (DW), signified by a Portland orange steady upraised hand, Means that a pedestrian shall not enter the roadway in the direction of the signal indication. Depending on the geometry of the intersection, the minimum length of WALK interval may be at least 7 seconds long and need not be sufficient for pedestrians to cross the entire roadway. The WALK interval is computed based on the geometry of the intersection and pedestrian walking speed. At locations where a large number of pedestrians cross an intersection, a longer WALK interval may be used. The pedestrian clearance time consists of the pedestrian change time (FDW indication), the yellow time and the all-red time. The duration of the clearance interval is based on the street width divided by an average walking speed of 3.5 feet per second. Countdown pedestrian signals provide a visual display of the amount of time remaining for pedestrians at signalized intersections to cross a roadway at a crosswalk. A walking speed of up to 4 feet per second may be used to evaluate the sufficiency of the

7 pedestrian clearance time at locations where an extended pushbutton press function has been installed to provide slower pedestrians an opportunity to request and receive a longer pedestrian clearance time. Passive pedestrian detection may also be used to automatically adjust the pedestrian clearance time based on the pedestrian s actual walking speed or actual clearance of the crosswalk. The additional time provided by an extended pushbutton press to satisfy pedestrian clearance time needs may be added to either the walk interval or the pedestrian change interval. According to the 2012 Edition of the MUTCD (Section 4E.07), the Countdown Pedestrian Signal (CPS) shall display the number of seconds remaining until the termination of the pedestrian change interval (State of California Business, Transportation and Housing Agency, Department of Transportation 2012). The Manual also states that the countdown display shall neither be used during the walk interval nor during the yellow change interval of a concurrent vehicular phase. In practice, the choice of the interval to start the countdown display is largely dependent on the jurisdictional preferences. For example, in Montgomery County, MD, Minneapolis, St. Paul, MN, Las Vegas, NV, and San Jose, CA, the countdown display starts with the FDW. However, in the District of Columbia and Cambridge and Boston, MA, the countdown involves the total time for the WALK and the FDW intervals. In July, 2005, a before and after study was performed on Euclid-Guymon and Broadway-2nd Avenue in San Diego by Supernak and Chavez (2005) for City of San Diego for the traditional and countdown pedestrian signal systems. Both intersections were videotaped for several days before and after CPS implementation. The study refined the definitions of the violation scenarios: (1) legal entry, legal exit, (2) illegal entry, legal exit, (3) legal entry, illegal exit, (4) illegal entry, illegal exit. The study found that illegal entries were more common after the countdown introductions but the difference was not statistically significant. The CPS proved successful in reducing the percentage of illegal exits, the result was statistically significant. As the current research also analyzes the Broadway 2 nd Avenue intersection, there are useful opportunities for comparison of results between those two studies. Studies of the CPS systems in the US started in 1990ties when those systems were originally installed. The most representative studies were reviewed, and the summary of the most relevant findings is presented below.

8 In 1997, a CPS was installed and studied at the intersection of Florida State Route 535 and Hotel Plaza Boulevard in Orlando, Florida (Chester and Hammond 1998). The purpose of the study was to evaluate pedestrian understanding of the CPS through field interviews. Surveys were conducted at random among local citizens and visitors. The selected crosswalk traversed eight lanes and measures about 140 feet in length. The countdown was applied to the entire WALK and FDW intervals. A total of 50 pedestrians were surveyed and the results indicated that 88% understood the functions of new countdown signals. From the responses from US residents and visitors, 91% of the former comprehended the meaning of the signals while to 81% of the visitors understood the functions of the CPS. A before and after pedestrian survey was conducted by the Minnesota Department of Transportation (Mn/DOT) in 1999 at six intersections within the metropolitan area of Minneapolis and St. Paul (Cook Research & Consulting, Inc. 1999). Pedestrians were interviewed before and after the countdown signals were installed. Field observations of pedestrian behavior were also made during the two periods. The countdown display was applied during the FDW interval. Overall, 78% of the respondents felt that the CPS was easier to understand than the conventional signal, while only 6% felt that it was more difficult to understand. The research showed that the numerical countdown, displayed during the FDW interval, was intuitively understood and used successfully by pedestrians. However, the study recommended that CPS should not become a standard signal component since the need is not always present. Situations recommended for CPS includes long pedestrian crossing distances, crossing to medians and intersections predominantly used by pedestrians with disabilities and elderly individuals. In 1999, in Monterey, California, investigators reported an increase in pedestrian walking speeds at locations where CPS were installed (Leonard, Juckes, and Clement 1999). Pedestrians were also found to be more likely to wait at a mid-crossing median for the next WALK phase. The CPS did not appear to have any adverse effect on motorist behavior. In 2000, Huang and Zegeer (2000) conducted an observational study of CPS effectiveness in Lake Buena Vista, Florida. Five intersections were observed: two with CPS and three control sites without CPS. The countdown at the two treatment sites began with the WALK interval. Since data was not collected at the intersections before the CPS installation, potential differences between individual sites were not fully accounted for. At

9 each intersection, a single crosswalk was observed for the study. It was found from the analysis that significantly fewer pedestrians began crossing during the WALK signal at CPS locations (47%) than at those with the conventional signal locations (59%). Thus, pedestrians were more likely to begin crossing during the pedestrian change interval rather than wait for the next WALK indication. In addition, contrary to expectations, slightly more pedestrians who could not complete crossing the intersection before the SDW were found at the intersections with CPS (10.5%) than those with the conventional signals (7.7%). The report also reported fewer instances of pedestrians running at locations with CPS (3.4%) than at locations with conventional pedestrian signals (10.4%). In early 2001, the San Francisco Department of Parking and Traffic installed and studied countdown signals at 14 intersections. The countdown display was active only in the FDW interval (DKS Associates 2001). The study found that the percentage of pedestrians in the crosswalk after the signal turned green for the conflicting vehicular traffic was significantly reduced. There was also a significant decrease in the percentage of pedestrians who started during the FDW as well as a decrease in the percentages of pedestrians running and aborting. The percentage of pedestrian-vehicle conflicts was also reduced. On the basis of these findings, San Francisco proposed to expand its installations of CPS to additional intersections where the crosswalks were at least 40 feet long. Noted exceptions were locations with relatively low pedestrian 10 volumes (under 10 per hour) even during special events and seasonal peaks. It was also found from this study that the pedestrians increased their walking speeds to complete crossing before the end of the pedestrian change interval. In 2001, the City of San Jose, California installed CPS at 5 intersections for testing (Botha et al. 2002). The study was conducted by the San Jose State University and consisted of a before (installation of the countdown signals) and after evaluation. The countdown started at the same time as the FDW. Among the variables studied were the proportion of pedestrians who arrived during the FDW and waited for the WALK before crossing, the proportion of pedestrians that entered during the WALK, FDW and DW intervals as well as running, baulking and hesitation of pedestrians. An additional survey was also conducted to determine how well pedestrians interpreted the meaning of the FDW indication. From the results, 59% of pedestrians gave the wrong interpretation of the FDW signals. Simple frequency analyses of the data was conducted and showed that the differences between the

10 before and after results were not considerably significant, although the number of motorist-pedestrian conflicts decreased. In a study conducted by Botha, et al. (2002) in the City of San Jose, CA little difference in walking speed, unusual behaviors, or motorist behavior between the CPS and the conventional pedestrian signal was observed. Substantial decreases were reported in the frequency of pedestrians running or aborting crossing attempts as well as the frequency of pedestrian/vehicle conflicts. A study was conducted by Mahach, et al. in 2002 to compare pedestrian signal preference among a set of seven signals. These included a conventional pedestrian signal and a CPS which had the countdown staring at the beginning of the steady WALK interval. Nearly 60% of the participants selected the CPS as their favorite. In 2002, the Rutgers Voorhees Transportation Policy Institute (RVTPI) examined the standards for traffic signals and pavement striping in New Jersey where CPS timing begins with the steady WALK interval. Based on its study of a CPS installation near a senior citizen complex, RVTPI concluded that CPS seemed more beneficial to the vehicular traffic than to pedestrians, particularly the elderly. RVTPI recommended that other measures be used at intersections where the elderly pedestrian is high, before resorting to the use of CPS. In 2002, Montgomery County, MD conducted a pedestrian survey at locations with CPS to determine the effect of the pedestrian countdown signal at five intersections (Eccles 2003). The County applied the countdown only to the FDW interval. Comparisons were made between behavioral changes of pedestrians at the same location during daylight hours and in good weather. A survey of 107 pedestrians was conducted to determine their perception of CPS. Observations of pedestrian compliance with the signal and pedestrianvehicle conflicts were also made. A simple t-test was used to analyze the data. At 3 of the 5 intersections evaluated, there were statistically significant decreases in the number of pedestrians remaining in the crosswalk when conflicting traffic received the green indication. The majority of the pedestrians surveyed correctly explained what the countdown signal phases meant. There was also a significant reduction in the frequency of pedestrian-vehicle conflicts as a result of the installation of the CPS. In 2003, the Transportation Research Center of University of Nevada conducted an evaluation of the effectiveness of countdown pedestrian signals deployed at 14 intersections

11 in the Las Vegas, Nevada downtown area (Pulugurtha and Nambisan 2004). The research methodology was one of a treatment and control type. Among the 14 intersections, 10 were treated with CPS and the remaining 4 control sites operated with the conventional pedestrian signals. The countdown display was applied to the FDW phase. The key variables investigated included pedestrian compliance with pedestrian signals, pedestrian vehicle conflicts, and pedestrians who ran out of time and thus were trapped in the crosswalk. Data collection was conducted with a video recorder. The results indicated that the CPS improved pedestrian compliance with the WALK, FDW and the SDW indications by 29%, 75% and 11% respectively. There was also a substantial reduction in pedestrian-vehicle conflicts, in comparison to the control intersections. Field interviews were conducted to receive feedback from pedestrians with regards to their understanding of the countdown signals and the FDW symbol. The results indicated that over 90% understood the general functions of the CPS and the FDW phase. The researchers believed that the CPS had a positive effect on pedestrian crossing behavior, and by inference, countdown signals could mitigate pedestrian crashes. The Technical Committee of the New England Section of the Institute of Transportation Engineers conducted a study on the CPS that was installed at three intersections in Boston, Massachusetts in 2004 (Petraglia 2004). The countdown display of the signals was active for the entire WALK and FDW intervals, similar to the practice in the District of Columbia. A before and after study was conducted. The measures of effectiveness investigated were the number of pedestrians starting on WALK, the number of pedestrians starting on FDW, the number of pedestrians finishing during the DW, the number of pedestrians running or aborting, and the number of pedestrian-vehicle conflicts. The research concluded that countdown signals did not cause any significant improvement in the mentioned variables and in some instances actually degraded pedestrian safety. In 2005, a study, Evaluation of the effectiveness of Pedestrian Countdown Signal by Deborah Lindoro Leistner (2005) in City of Gainesville, Florida was performed and a total of 7,639 pedestrians were observed before and 6,339 pedestrians were observed after the installation of the CPS. The results for each performance measure were analyzed using a test for difference in population proportions to evaluate if a significant difference between the before and after measurements can be attributed to the installation of the pedestrian

12 countdown signals, Five study sites were selected and the video cameras were mounted on signal poles at a specific location at each intersection. The data collection system used in this study is capable of simultaneously capturing pedestrian and vehicular movements with a video camera and the corresponding traffic signal indications. Same as this study videotaping was used but each pedestrian was observed under certain category for legal and illegal (entry and exit) situations. Countdown Pedestrian Signal had positive effect on pedestrian behavior. Two studies were performed by Singer and Lerner in 2004 (Ott and Longnecker 2001). The project consisted of two studies conducted to determine the effects of replacing the standard CPS with an alternative configuration that does not include the flashing upraised hand during the pedestrian change interval. Study 1 was a laboratory study to investigate comprehension of the experimental CPS relative to standard and nonstandard pedestrian signals. Study 2 was a field observational study to determine the effects of the experimental CPS on pedestrian behavior relative to the standard CPS. The comparison of CPS type involved observing pedestrian behavior at crosswalks with one of the two CPSs. Variables of interest include pedestrian compliance and crossing success as well as key behaviors (e.g., running, aborted crossings) and pedestrian/vehicle conflicts. There was no overall increase in the number of pedestrians completing crossing during the steady DON T WALK phase (SDW), although pedestrians were more likely to finish crossing later in the SDW. A study from HNTB Corporation was performed in 2008 and the results were that there was slight increase in overall percentage of pedestrians entering intersection during walk signal (W) and percentage of pedestrians crossing the crosswalk during FDW was decreased. But the percentage of the pedestrians entering the intersection during DW was also increased. Overall the successful crossing percentage was increased. Studies conducted on pedestrian satisfaction and signal preference indicates that pedestrians overwhelmingly approve of the CPS and typically prefer them to the conventional signals. Most of such studies were elements of a larger survey that included all the discussions above. For example in San Francisco, 78% of the pedestrians surveyed reported that CPS are 12 very helpful, with only 34% for conventional signals. In the same study, 92% of the pedestrians expressed a preference for the CPS (Cook Research & Consulting, Inc. 1999).

In another study conducted in Minneapolis, MN in 1999, a noteworthy age difference in CPS satisfaction was found, where satisfaction was highest among teens and lowest among older pedestrians. It was suggested by the investigators that age differences such as this warrant additional investigation. Although there are some inconsistencies and variations in the measurements of effectiveness, data collection procedures and statistical analyses used in most of the research conducted thus far, some conclusions can be drawn from the literature on the CPS. The variations in the results of the studies may be due to site factors, pedestrian characteristics and the type of CPS application. The general consensus of the literature suggests that the CPS do provide pedestrians with additional information that helps them to cross intersections more successfully. Although there were reductions in the frequencies of some of the undesirable events such as pedestrian-vehicle conflicts, pedestrian running and aborted crossing, some of these reductions were not statistically significant. The literature also suggests that pedestrians overwhelmingly prefer CPS to conventional signals. The review of available literature revealed the following opportunities for original research presented in this document: The existing studies did not address the issue of heterogeneity of the population of pedestrians. Videotaped episodes of intersection crossing of a large number of individuals creates a unique opportunity to examine the anatomy of crossing violations (who is doing it, and to what extent). There is an opportunity to systematically study the impact of age, gender, handicap on violation frequency. As videotaping can be extended over a few weeks, time consistency of findings can be examined. Videotape records can be done for the middle of the peak (8-9 am) and also for the peak shoulders (9-10 am) with the opportunity to examine whether rushing to work would increase the frequency of crossing violations. Unique geometry and vehicular traffic patterns of the Broadway/2 nd Avenue intersection in San Diego (Broadway has much more vehicular traffic and is significantly wider than the 2 nd Avenue) gives an opportunity to study the impact of those factors on violation frequency at the same intersection. Careful record of times (t 1 and t 2 ) of crossing episodes from the start to the median and from the median to the end opens an interesting opportunity to examine hypothesis that pedestrians can and will adjust their speed to complete their intersection crossing in time. 13

14 Particular emphases can be placed on statistical analysis of all variables potentially able to explain various cases of violations. Whenever possible multivariate analysis can be performed to identify explanatory power of variables when examined jointly.

15 CHAPTER 3 SITE DESCRIPTION AND DATA COLLECTION 3.1 SITE DESCRIPTION A single intersection in the City of San Diego, California, was selected for the study of countdown pedestrian signals. The selected intersection is located in the downtown (CBD) area and nearby civic center light-rail trolley station. The user population at such intersections is representative of the City s population, and the tourists. The selected intersection is: Broadway and 2 nd Avenue. Satellite view of intersection is shown in Figure 3.1 and street view of intersection is shown in Figure 3.2. Figure 3.1. Satellite view of intersection (Google Earth). The advantage of this selection is the fact that the same intersection was evaluated in 2005 using data shortly before and shortly after the CPS introduction there. The new videotape was completed some 4-5 years later, giving an opportunity for comparisons of results. Above intersections have high pedestrian traffic volumes during the day. Pedestrian

16 Figure 3.2. Street view of intersection. counts will be presented later in the study. The vehicular traffic volumes are high on Broadway but light on the 2 nd street. The study intersection is not equipped with pedestrian push buttons. The pedestrian crossing cycles are activated once per traffic signal cycle. This intersection is located in the downtown area and is surrounded by Westgate hotel building, San Diego City Hall, 7/11convenient store, Sprint Store, City of San Diego building, NBC San Diego, Spreckels Theater and restaurants. In addition, the main civic center trolley station is adjacent to this intersection. The pedestrian population at this site is very diverse, composed of a mix of professionals, retail and restaurant employees and patrons, students, and tourists visiting downtown area and hotels. Figure 3.3 shows video camera locations for videotaping. 3.2 DATA COLLECTION As the study site was determined, the next step was to proceed with data collection. The data collection videotaping used in this study was capable of simultaneously capturing pedestrian and the corresponding traffic signal indications especially pedestrian signal. The video camera was mounted on tripod at a specific position facing crosswalk. Data was collected in the morning peak period time 8:00 to 10:00. One crosswalk was selected for one specific day. Video recording was done for 3 weeks from Monday to Thursday. Each day

17 Figure 3.3. Video-camera locations for video-taping, adapted from Google Earth. pedestrian videotape is observed carefully to code the behavior of each pedestrian on Excels spreadsheets. To assure privacy, no specific person was targeted or identified at the time of data extraction from videotaping. The data collection details are summarized in Table 3.1. Table 3.1. Data Collection Days, Time Duration and Crosswalks Directions Site Data Collection Crosswalk Time Monday NW-NE 8:00AM-10:00AM 08/10/09,08/17/09,08/24/09 Tuesday NW-SW 8:00AM-10:00AM Broadway and 2 nd Avenue 08/11/09,08/18/09,08/25/09 Wednesday NE-SE 8:00AM-10:00AM 08/12/09,08/19/09,08/26/09 Thursday 08/13/09,08/20/09,08/27/09 SE-SW 8:00AM-10:00AM Total Hours 24 Hours

3.3 PEDESTRIAN BEHAVIOR OBSERVATIONS Pedestrian behavior observations were recorded to code behavior of each pedestrian, which was initiated by data extraction. 3.3.1 Data Extraction Data for each crosswalk was recorded. Data extraction from the videotapes was performed using an Excel spreadsheet (see Appendix for a sample data collection sheet). The following events were manually collected from each videotape and recorded in the spreadsheets. Pedestrian signal indication at the time of pedestrian arrival. Phase during which the pedestrian entered the crosswalk (W, FDW or DW); Cycle at which the pedestrian entered the crosswalk. Phase during which the pedestrian exited the crosswalk (W, FDW or DW). 3.3.2 Definition of Pedestrian Categories Twelve Categories have been defined for pedestrians, and their behavior was observed regarding 4 situations. The 12 Categories are shown in Table 3.2 and the 4 Situations are shown in Table 3.3. 3.3.3 Description of Pedestrian Crossing Situations Table 3.3 presents a logical set of situations facing pedestrians in terms of their intersection crossing behavior. 3.3.4 Description of Legal and Illegal Terms for the Intersection Table 3.4 explains in detail definition of legal and illegal entries and exits in accordance with the California Code (V C Section 21456, Walk, Wait or Don t Walk) (State of California Business, Transportation and Housing Agency, Department of Transportation 2012). 18 3.4 INTERSECTION GEOMETRY Crosswalk lengths are listed in Table 3.5. Broadway Street is almost two times wider than the 2 nd Avenue.

19 Table 3.2. Pedestrian Category Definition Category Explanation 1 Children 2 Assisted Children 3 Younger Male (Below 40 Years) 4 Younger Female (Below 40 Years) 5 Older Male (40Years-65Years) 6 Older Female (40Years-65Years) 7 Elderly Male ( > 65Years)* 8 Elderly Female ( > 65 Years)* 9 Handicapped 10 Assisted Handicapped 11 Runners 12 Bicyclists *Note: Based on video information: cases when advanced age alone rather than visible physical handicap would be a factor for slower walking. Table 3.3. Situation Description Situation Non-Violation Violation Type 2 Violation Type 3 Violation Type 4 Description Legal Entry and Legal Exit Illegal Entry and Legal Exit Legal Entry and Illegal Exit Illegal Entry and Illegal Exit Table 3.4. Situations Definitions Situations Description Legal Entry Legal Exit Illegal Entry Illegal Exit Entry on Walk(W) Signal Exit on Walk(W) or Flashing Don t Walk(FDW) Signal Entry on Flashing Don t Walk(FDW) Signal or Don t Walk(DW) Signal Exit on Don t Walk(DW) Signal

20 Table 3.5. Crosswalk Lengths Crosswalk Distance(feet) Broadway NW corner SW corner 86 NE corner SE corner 86 2nd Avenue NE corner NW corner 48 SE corner SW corner 48 3.5 SIGNAL CHARACTERISTICS Cycle lengths for each crossing are presented in Table 3.6 and 3.7. They represent the timing plan in place during the videotaping in August 2009. Table 3.6. Cycle Length-Broadway Broadway Signal Walk(t w ) Flashing Don t Walk(t fdw ) Don t Walk Time(sec) 7 21 41 Table 3.7. Cycle Length-2 nd Avenue 2 nd Avenue Signal Walk(t w ) Flashing Don t Walk(t fdw ) Don t Walk Time(sec) 20 10 40 Assuming the conservative standard of 3.5ft/sec walking speed, an average pedestrian would need almost 26 seconds to cross; a pedestrian who starts crossing at the beginning of the green indication will have just 28 seconds to complete his/her crossing. If the 4.0 ft/sec speed standard was applied, the pedestrian would need 21.5 seconds to cross with 28 seconds available at the beginning. Assuming 3.5ft/sec walking speed, an average pedestrian would need almost 14 seconds to cross; a pedestrian who starts crossing at the beginning of the green indication will have 30 seconds to complete his/her crossing. If 4.0ft/sec standard was applied, the pedestrian would need 12 seconds to cross with 30 seconds available at the beginning.

21 3.6 TERMS FOR INDIVIDUAL CROSSING EPISODES The following three terms: t 0, t 1, t 2 are to be recorded for each pedestrian. They will be used in analysis of the potential speed adjustment to cross the intersection in time. Table 3.8 summarizes the description of t 0, t 1, t 2. Table 3.8. Description of t 0, t 1, t 2 Time(sec) Description t 0 t 1 t 2 Time(sec) to enter the intersection* Time(sec) needed to reach the median Time(sec) needed to exit intersection from the median *Note: From the beginning of the green phase for pedestrians 3.7 DATA ORGANIZATION In order to effectively record and process the observed incidents of intersection crossing done by each individual pedestrian, the raw data was organized as shown in Table 3.9, Table 3.10, Table 3.11, Table 3.12, and Table 3.13. Table 3.9. Example of Data Organization Cycle Person Category Monday(08/10/2009) Tw (sec) Tfdw (sec) Entry t0 Tw- to (sec) (sec) legal illegal t1 (sec) t2 (sec) to+t1+t2 (tw+tfdw)- (t1- t2) total time (sec) (sec) Exit t0+t1+t2) (sec) legal illegal situation 1 1 4 20 10 0 20 Yes 5 4.5 0.5 9.5 20.5 Yes 1 2 3 20 10 1.6 18.4 Yes 4 3.8 0.2 9.4 20.6 Yes 1 3 3 20 10 1.6 18.4 Yes 4 3.8 0.2 9.4 20.6 Yes 1 4 7 20 10 2.6 17.4 Yes 7 7 0 16.6 13.4 Yes 1 5 3 20 10 3.2 16.8 Yes 5 4.7 0.3 12.9 17.1 Yes 1 6 4 20 10 7.23 12.77 Yes 5 5 0 17.23 12.77 Yes 1 7 3 20 10 8.45 11.55 Yes 4.5 4.5 0 17.45 12.55 Yes 1 8 3 20 10 20.5-0.5 Yes 4 4 0 28.5 1.5 Yes 2 9 3 20 10 21-1 Yes 5 4.5 0.5 30.5-0.5 Yes 4 10 4 20 10 21-1 Yes 6 5 1 32-2 Yes 4 11 3 20 10 22-2 Yes 5 5 0 32-2 Yes 4 2 1 3 20 10 3 17 Yes 4 3.7 0.3 10.7 19.3 Yes 1 2 3 20 10 4.5 15.5 Yes 4.5 4 0.5 13 17 Yes 1 3 3 20 10 5 15 Yes 4 4 0 13 17 Yes 1 4 3 20 10 19 1 Yes 5 5 0 29 1 Yes 1 5 3 20 10 22-2 Yes 4.5 4 0.5 30.5-0.5 Yes 4

22 Table 3.10. Example of Data Reduction, Week 1, Monday Monday 1 Situation 1 2 3 4 Total Category 1 5 0 0 0 5 2 5 0 0 0 5 3 278 60 0 58 396 4 176 41 0 40 257 5 19 9 0 10 38 6 10 3 0 3 16 7 5 0 0 1 6 8 3 0 0 0 3 9 0 0 0 0 0 10 0 0 0 0 0 11 1 1 0 3 5 12 7 0 0 3 10 Total 509 114 0 118 741 3.8 EXCLUSION OF VIOLATION TYPE 3 Violation type 3 was excluded from the study (Legal entry and illegal exit). Generally, pedestrian entering an intersection on walk (W) signal is unlikely to exit intersection on don t walk (DW) signal. Indeed, during the three weeks of videotaping, this situation was encountered in one case only. This situation would have happened if a pedestrian was walking unusually slowly because of severe handicap or similar. Eliminating a cell with virtually zero observations was also justified from the statistical representation point of view.

23 Table 3.11. Example of Data Reduction, Week 1, Week 2, and Week 3 Non-Violation Week 1 Week 2 Week 3 10 10 12 8 12 11 696 685 659 475 438 450 71 63 76 28 29 32 11 15 17 12 11 11 0 0 0 0 0 0 2 1 1 11 11 11 Violation Type 2 0 2 2 0 2 0 126 135 129 89 78 81 22 25 22 6 6 7 1 1 2 1 6 3 0 0 0 0 0 0 1 2 1 3 4 2 Violation Type 4 0 0 0 0 0 3 159 158 160 91 81 82 23 21 24 10 6 6 2 2 2 1 0 3 0 0 0 0 1 0 3 4 1 6 8 9

24 Table 3.12. Example of Data Reduction, Peak/Off- Peak Category Peak Off-Peak Non Violation 1 14 16 2 16 20 3 991 1042 4 684 682 5 121 97 6 52 34 7 22 19 8 20 16 9 0 0 10 0 0 11 2 2 12 17 15 Category Peak Off-Peak Violation Type 2 1 2 2 2 2 0 3 173 202 4 97 148 5 30 30 6 9 7 7 1 3 8 5 3 9 0 0 10 0 0 11 2 2 12 5 4 Category Peak Off-Peak Violation Type 4 1 0 0 2 3 0 3 279 233 4 134 113 5 36 29 6 16 6 7 3 4 8 2 2 9 0 0 10 1 0 11 1 7 12 12 12

25 Table 3.13. Example of Data Reduction, Long Crossing and Short Crossing Non-Violation Violation Type 2 Violation Type 4 Category Long Crossing Short Crossing 1 6 26 2 3 28 3 651 1389 4 483 880 5 85 125 6 34 55 7 17 26 8 16 18 9 0 0 10 0 0 11 2 2 12 11 22 Category Long Crossing Short Crossing 1 4 0 2 0 2 3 200 190 4 105 143 5 39 30 6 10 9 7 4 0 8 8 2 9 0 0 10 0 0 11 2 2 12 3 6 Category Long Crossing Short Crossing 1 0 0 2 0 3 3 71 405 4 20 234 5 5 63 6 2 20 7 0 6 8 0 4 9 0 0 10 0 1 11 0 8 12 1 22

26 CHAPTER 4 ANALYSIS AND RESULTS This chapter presents details of data analysis and major findings of the research. A total of 5,504 pedestrians were observed before when there were 12 categories and 5402 pedestrians were observed after the categories were reduced to six only. Combining some of the 12 original pedestrian categories into 6 new categories was done after examining representation of each category and after initial test of significance of variables used in defining those initial 12 categories. Old categories that did not demonstrate significantly different crossing behavior could be merged to also improve cell representation for statistical analysis. The results for each performance measure are analyzed using a test for difference in population proportions to evaluate if a significant difference between different categories can be attributed to the effectiveness of the pedestrian countdown signals. 4.1 PERFORMANCE MEASURES From the data, a number of performance measures were calculated for this study (for 12 categories and 6 categories), including: The proportions of pedestrians legally entering and exiting the crosswalk during each signal indication (Situation 1); The proportions of pedestrians illegally entering and legally exiting the crosswalk during each signal indication (Situation 2); The proportions of pedestrians legally entering and illegally exiting the crosswalk during each signal indication (Situation 3 eliminated for lack of data); The proportions of pedestrians illegally entering and illegally exiting the crosswalk during each signal indication (Situation 4). The three performance measures: Non-Violation 1, Violation Type 2 and Violation Type 4 needed to be examined for the following five variables: pedestrian categories; peak/off-peak: days; weeks; short/long crossing. This stratification is useful in an attempt to meet the following research objectives: 10. identifying those who are responsible for the most consequential situation, Violation Type 4 (illegal entry, illegal exit);

11. finding out which variables are most responsible for differences in crossing behavior; 12. determining whether pedestrian entering on flashing don t walk are able to avoid Violation Type 4 (exiting illegally); and 13. Performing comparisons of the frequency of violations in 2009 will be compared with the results for the earlier 2005 study (Supernak and Chavez 2005). 4.2 COMPARISON OF VIOLATION PROPORTIONS (12 PEDESTRIAN CATEGORIES) As number of actual observations varies, analysis of proportions is more meaningful than analysis of totals (or means). The starting analysis is performed for the initial 12 categories of pedestrians to identify similarities and differences among them in terms of intersection crossing behavior. 4.2.1 Z-Statistics (Comparison of Proportions) To test the significance of the results observed, a test for the difference in Category proportions was used (Ott and Longnecker 2001). This test was performed to evaluate if the performance measures between different categories a statistically significant, indicating that the pedestrian countdown signals have influenced pedestrian behavior differently for different categories. The hypothesis testing is based on the z statistic from a normal Distribution. The calculations were performed using the following formulas (4.1) and (4.2): where, Z calc = calculated test statistic, Z calc. =( ₁- ₂) / ( (1- ) (1/n+1/m)) (4.1) 27 = (p₁+p₂)/ (n+m) (4.2) Zα/ 2 = critical z value from table of normal distribution probabilities for a given confidence level, measure), = pooled estimate between two categories, p₁= estimate of category 1 population proportion (for specified performance p₂ = estimate of category 2 population proportion (for specified performance measure), n = total count of situations of category 1, and m = total count of situations of category 2

28 The null hypothesis tested in all cases is that there is no difference between the Categories, with the alternate hypothesis that there is a statistically significant difference. H₀: p₁=p₂ H a : p₁ p₂ A two-tailed z test was performed at a confidence level of 95%. The critical z value (Zα/2) obtained from the table of normal distribution probabilities for the given confidence level is 1.96. 4.2.2 Violation Type 4 Results The calculated z values for each performance measure are shown in Table 4.1 below. These values are compared to the critical z value. The null hypothesis that the proportion values observed are equal is rejected if the absolute calculated z value is higher than the critical z value. Table 4.1. Summary of Violation Type 4 Results Comparison of Proportions Category 3 Vs. Category 4 (Gender) Category 5 Vs. Category 6 (Gender) Category 3 Vs. Category 5 (Age) Category 4 Vs. Category 6 (Age) Category 7 Vs. Category 8 (Gender) Category 11 Vs. Category 12 (Type of Sport Activity) Violation Type 4 Results z-statistics Z-critical (1.96) 95% confidence level 2.61* >1.96 0.664 <1.96 1.503 <1.96 1.055 <1.96 0.50 <1.96 1.077 <1.96 Category (1 through 10) Vs. Sport (11+12) 0.577 <1.96 Regular Category (3 through 6) Vs. Sport (11+12) 2.07* >1.96 Regular (3 through 6) Vs. Assisted (1+2) 1.23 <1.96 Long Crossing Vs. Short Crossing 14.28 >1.96 Peak Vs. Off-Peak 2.94 >1.96 Monday Vs. Thursday ( Short Crossing) 1.02 <1.96 Tuesday Vs. Wednesday ( Long Crossing) 0.15 <1.96 *Note: By applying Bonferroni adjustment, not statistically significant.

29 Example of Violation Type 4 is presented in Figure 4.1 with virtually no vehicular traffic on the 2 nd Avenue, Pedestrians enter and exit intersection illegally on red (Violation Type 4). Figure 4.1. Example of violation Type 4- short crossing (2 nd Avenue). The results of the z-statistics can be summarized as follows: There is a statistically significant difference between younger males and younger females. Younger men commit Violation Type 4 more frequently than their female counterparts. There is no statistically significant difference between older male and older female for violation 4. They behave same. There is no statistically significant difference between younger males and older males. Younger men and older men are behaving same for Violation Type 4. There is no statistically significant difference between younger females and older females. Younger female and older female are behaving same for Violation Type 4. There is no statistically significant difference between male and female seniors. They behave same. There is no statistically significant difference between runners and bicyclists. There is a statistically significant difference between regular pedestrians and sports (runners, bicyclists). Runners and bicyclists commit more Violation Type 4 than their regular pedestrian counterparts.

30 There is no statistically significant difference between regular pedestrians and assisted pedestrians (children) for Violation Type 4. There is a statistically significant difference between long crossing and short crossing if no other variable is studied simultaneously. Violation Type 4 is more common between short crossings as compared to long crossing. Main reason for Violation Type 4 on short crossing is lower flashing don t walk interval, which leads to illegal exit. There is a statistically significant difference between Peak and Off-Peak if no other variable is analyzed simultaneously. There is no statistically significant difference between Monday and Thursday (Short crossing). There is no statistically significant difference between Tuesday and Wednesday (Long crossing). 4.2.3 Violation Type 2 Results The results of the z-statistics for Violation Type 2 (illegal entry but legal exit) are presented in Table 4.2. Table 4.2. Table Summary of Violation Type 2 Results Comparison of Proportions Category 3 Vs. Category 4 (Gender) Category 5 Vs. Category 6 (Gender) Category 3 Vs. Category 5 (Age) Category 4 Vs. Category 6 (Age) Category 7 Vs. Category 8 (Gender) Category 11 Vs. Category 12 (Type of Sport Activity) Violation Type 2 Results z-statistics Z-critical (1.96) 95% confidence level 0.12 <1.96 1.320 <1.96 3.270 >1.96 0.426 <1.96 0.78 <1.96 1.460 <1.96 Category (1 through 10) Vs. Sport (11+12) 0.940 <1.96 Regular Category (3 through 6) Vs. Sport (11+12) 201.96 >1.96 Regular (3 through 6) Vs. Assisted (1+2) 0.62 <1.96 Long Crossing Vs. Short Crossing 10.82 >1.96 Peak Vs. Off-Peak 3.01 >1.96 Monday Vs. Thursday ( Short Crossing) 0.46 <1.96 Tuesday Vs. Wednesday ( Long Crossing) 0.97 <1.96

31 Example of Violation Type 2 is presented in Figure 4.2 on Broadway, a man enters intersection late on flashing red, and exits the intersection legally before red (Violation Type 2). Figure 4.2. Example of violation Type 2- long crossing (Broadway). The results of the z-statistics analysis can be summarized as follows: Younger male and younger female are behaving same for Violation Type 2. Older male and older female are behaving same for Violation Type 2. There is a statistically significant difference between younger men and older men if no other variable is analyzed simultaneously. Younger men commit Violation Type 2 more frequently than their older men counterparts. Younger females and older females are behaving same for the Violation Type 2. There is a statistically significant difference in regular pedestrians and sports pedestrians (runners and bicyclists) if no other variables are analyzed simultaneously. Runners and bicyclists commit more Violation Type 2 than their regular pedestrian counterparts. Regular pedestrians and assisted pedestrians (children) are behaving same. There is a statistically significant difference in long crossing and short crossing if there are no other variables analyzed simultaneously. One likely reason for that result is the higher flashing don t walk interval, which provides enough time to illegal entered pedestrians to exit legally.