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NCHRP Web-Only Document 394 Evaluation of Change and Clearance Intervals Prior to the Flashing Yellow Arrow Permissive Left-Turn Indication David A. Noyce Andrea R. Bill Boris R. Claros Madhav V. Chitturi University of Wisconsin-Madison Madison, WI Michael K nodler, J r. Francis Tainter University of Massachusetts Amherst Amherst, MA David S. Hurwitz Oregon State University Corvallis, OR Peter K oonce Peter K oonce Consulting Portland, OR Christopher L. Brehmer K ittelson & Associates Inc. Portland, OR Conduct of Research Report for NCHRP Project 03-125 Submitted August 2023 © 2024 by the National Academy of Sciences. National Academies of Sciences, Engineering, and Medicine and the graphical logo are trademarks of the National Academy of Sciences. All rights reserved. NATIONAL COOPERATIVE HIGHWAY RESEARCH PROGRAM Systematic, well-designed, and implementable research is the most effective way to solve many problems facing state departments of transportation (DOTs) administrators and engineers. Often, highway problems are of local or regional interest and can best be studied by state DOTs individually or in cooperation with their state universities and others. However, the accelerating growth of highway transportation results in increasingly complex problems of wide interest to highway authorities. These problems are best studied through a coordinated program of cooperative research. Recognizing this need, the leadership of the American Association of State Highway and Transportation Officials (AASHTO) in 1962 initiated an objective national highway research program using modern scientific techniquesâ the National Cooperative Highway Research Program (NCHRP). NCHRP is supported on a continuing basis by funds from participating member states of AASHTO and receives the full cooperation and support of the Federal Highway Administration (FHWA), United States Department of Transportation, under Agreement No. 693J J 31950003. COPYRIGHT INFORMATION Authors herein are responsible for the authenticity of their materials and for obtaining written permissions from publishers or persons who own the copyright to any previously published or copyrighted material used herein. Cooperative Research Programs (CRP) grants permission to reproduce material in this publication for classroom and not-for-profit purposes. Permission is given with the understanding that none of the material will be used to imply TRB, AASHTO, APTA, FAA, FHWA, FTA, GHSA, or NHTSA endorsement of a particular product, method, or practice. It is expected that those reproducing the material in this document for educational and not-for-profit uses will give appropriate acknowledgment of the source of any reprinted or reproduced material. For other uses of the material, request permission from CRP. DISCLAIMER The opinions and conclusions expressed or implied in this report are those of the researchers who performed the research. They are not necessarily those of the Transportation Research Board; the National Academies of Sciences, Engineering, and Medicine; the FHWA; or the program sponsors. The Transportation Research Board does not develop, issue, or publish standards or specifications. The Transportation Research Board manages applied research projects which provide the scientific foundation that may be used by Transportation Research Board sponsors, industry associations, or other organizations as the basis for revised practices, procedures, or specifications. The Transportation Research Board, the National Academies, and the sponsors of the National Cooperative Highway Research Program do not endorse products or manufacturers. Trade or manufacturersâ names appear herein solely because they are considered essential to the object of the report. The information contained in this document was taken directly from the submission of the author(s). This material has not been edited by TRB.
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C O O P E R A T I V E R E S E A R C H P R O G R A M S CRP STAFF FOR NCHRP WEB-ONLY DOCUMENT 394 Waseem Dekelbab, Deputy Director, Cooperative Research Programs, and Manager, National Cooperative Highway Research Program Christopher T. McKenney, Senior Program Officer Sheila A. Moore, Program Associate Natalie Barnes, Director of Publications Heather DiAngelis, Associate Director of Publications Jennifer J. Weeks, Publishing Projects Manager NCHRP PROJECT 03-125 PANEL Field of TrafficâArea of Operations and Control Randall K. Laninga, Peoria, IL (Chair) Norman Baculinao, Ventura, CA George L. Butzer, HyperSphere Technologies, Inc., New Albany, OH Michael Jason Oldham, Virginia Department of Transportation, Fairfax, VA Mitsuru Saito, Brigham Young University, Provo, UT Ida Van Schalkwyk, Washington State Department of Transportation, Olympia, WA Raghu K. Veturi, Gunda Corporation, LLC, Houston, TX Ann H. Do, FHWA Liaison Richard A. Cunard, TRB Liaison (retired) AUTHOR ACKNOWLEDGMENTS The research team is grateful to the National Cooperative Highway Research Program and the NCHRP 03-125 Project Panel for supporting this research effort. Research team acknowledges the support from agencies and individuals who responded to the Survey and supported the field data collection .
iv T A B L E O F C O N T E N T S LIST OF FIGURES .......................................................................................................... v LIST OF TABLES ........................................................................................................... vii SUMMARY ...................................................................................................................... 1 CHAPTER 1 Introduction ................................................................................................ 2 CHAPTER 2 Literature Review ....................................................................................... 3 CHAPTER 3 Survey Results ......................................................................................... 12 CHAPTER 4 Field Study ............................................................................................... 28 CHAPTER 5 Simulator Study ........................................................................................ 46 CHAPTER 6 Conclusions and Suggested Research .................................................... 55 REFERENCES .............................................................................................................. 59 APPENDIX A Survey Questionnaire ............................................................................. 61
v L I S T O F F I G U R E S Figure 3-1. Public sector survey responses by state. 13 Figure 3-2. Number of signals owned/maintained by respondents. 14 Figure 3-3. References typically used by organizations for signal timing questions. 15 Figure 3-4. Organizations with documented yellow change and red clearance interval policies. 15 Figure 3-5. Reported public agency FYA and FRA indication use. 16 Figure 3-6. Percentage of PPLT movements operating with FYA indication. 16 Figure 3-7. Agency responses on plans to replace PPLT with FYA or FRA. 17 Figure 3-8. Agency responses on practice of requiring FYA or FRA indications at new signal with PPLT. 18 Figure 3-9. PPLT yellow change interval timing practice (transitioning from steady GREEN arrow to FYA/FRA). 21 Figure 3-10. PPLT red clearance interval timing practice (transitioning from steady GREEN arrow to FYA/FRA). 22 Figure 3-11. Motivation for FYA or FRA use. 23 Figure 3-12. Advanced FYA/FRA indication features used. 25 Figure 3-13. Organizations using ATSPM. 26 Figure 3-14. Firmware used by agencies. 26 Figure 4-1. Number of Data Collection Locations across the United States. 28 Figure 4-2. Screenshot of video facing left turn signal indication at E. Hampden Avenue and S. Tamarac Drive, in Denver, Colorado. 29 Figure 4-3. Screenshot of video facing opposing traffic signal indication at E. Hampden Avenue and S. Tamarac Drive, in Denver, Colorado. 29 Figure 4-4. Sequence of events for timestamps. 32 Figure 4-5. Signal violation measures as a function of change interval (SYA) duration. 35 Figure 4-6. Signal violation measures as a function of clearance interval (SRA) duration. 35 Figure 4-7. Signal violation rates as a function of change and clearance interval durations (including approaches with delayed onset of FYA). 36
vi Figure 4-8. Signal violation rates as a function of change and clearance interval durations (NOT including approaches with delayed onset of FYA). 37 Figure 4-9. Distribution of left turning vehicle arrival time observations. 38 Figure 4-10. Stacked distribution of left turning vehicle arrival time observations by decision and signal indication. 38 Figure 5-1. Scenario A in the Driving Simulator. 47 Figure 5-2. Scenario B in the Driving Simulator. 47 Figure 5-3. Typical Intersection in the Driving Simulator Scenario 48 Figure 5-4. Full-Scale Driving Simulator at the University of Wisconsin- Madison. 49 Figure 5-5. Full-Scale Driving Simulator at the University of Massachusetts- Amherst. 49 Figure 5-6. Full-Scale Driving Simulator at the Oregon State University. 50 Figure 5-7. Data Collected in the Driving Simulator. 52 Figure 5-8. Time Space Diagram for Violations. 53 Figure 5-9. Subject Speeds at the Onset of Clearance Interval (steady RED ARROW). 54
vii L I S T O F T A B L E S Table 2-1. Red clearance interval from the signal timing manual (FHWA 2015). 8 Table 3-1. Flashing yellow arrow indication signal head configuration and sequence. 19 Table 3-2. Flashing Red Arrow Indication Signal Head Configuration and Sequence 20 Table 3-3. Contextual considerations for FYA and FRA indications application. 24 Table 4-1. Data Collection Intersections and Attributes. 30 Table 4-2. Number of locations by Durations of Change (SYA) and Clearance (SRA) Intervals. 31 Table 4-3 Data and analysis by intersection approach. 34 Table 4-4 Left turn signal violation rates by bin. 36 Table 4-5 Effect of Change Interval (SYA) Duration: Logistic Regression Modeling Results. 40 Table 4-6 Effect of Change Interval (SYA): Odds Ratios for Predictor Variables. 40 Table 4-7 Effect of Clearance Interval (SRA): Logistic Regression Modeling Results. 41 Table 4-8 Effect of Clearance Interval (SRA): Odds Ratios for Predictor Variables. 41 Table 4-9 Effect of Delayed Onset of FYA indication in Oregon: Logistic Regression Modeling Results. 42 Table 4-10 Effect of Delayed Onset of FYA Indication in Oregon: Odds Ratios for Predictor Variables. 42 Table 4-11 Effect of Delayed Onset of FYA Indication in Florida: Logistic Regression Modeling Results. 42 Table 4-12 Effect of Delayed Onset of FYA Indication in Florida: Odds Ratios for Predictor Variables. 43 Table 4-13 Effect of Regional Variation: Logistic Regression Modeling Results. 43 Table 4-14 Effect of Regional Variation: Odds Ratios for Predictor Variables. 44 Table 5-1. Demographics of Subjects. 50