Algorithms to Convert Basic Safety Messages into Traffic Measures (2022)

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2022 N A T I O N A L C O O P E R A T I V E H I G H W A Y R E S E A R C H P R O G R A M NCHRP RESEARCH REPORT 997 Algorithms to Convert Basic Safety Messages into Trafc Measures Meenakshy Vasudevan James O’Hara Haley Townsend Sampson Asare Syihan Muhammad Noblis, Inc. Washington, DC Kaan Ozbay Di Yang Jingqin Gao Abdullah Kurkcu Fan Zuo New York University Brooklyn, NY Subscriber Categories Operations and Trafc Management • Transportation, General • Vehicles and Equipment Research sponsored by the American Association of State Highway and Transportation Ofcials in cooperation with the Federal Highway Administration

NATIONAL COOPERATIVE HIGHWAY RESEARCH PROGRAM Systematic, well-designed, and implementable research is the most effective way to solve many problems facing state departments of trans- portation (DOTs) administrators and engineers. Often, highway prob- lems 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 pro- gram of cooperative research. Recognizing this need, the leadership of the American Association of State Highway and Transportation Officials (AASHTO) in 1962 ini- tiated an objective national highway research program using modern scientific techniques—the National Cooperative Highway Research Program (NCHRP). 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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 AUTHOR ACKNOWLEDGMENTS The research reported herein was performed under NCHRP Project 03-137 by Noblis, Inc., and New York University (NYU). Noblis was the contractor for this study. Dr. Meenakshy Vasudevan, Senior Principal at Noblis, was the Principal Investigator. The other authors of this report from Noblis are James O’Hara (Software Developer/Autonomy Lab Manager); Haley Townsend (Data Scientist); Dr. Sampson Asare (Senior Trans- portation Engineer); and Syihan Muhammed (Programmer). The other authors from NYU are Dr. Kaan Ozbay (Professor in the Department of Civil and Urban Engineering and the Center for Urban Sciences and Director of NYU C2SMART); Di Yang (Research Assistant and PhD Candidate); Dr. Jingqin Gao (Senior Research Associate); Dr. Abdullah Kurkcu (Lead Traffic Modeler at Ulteig, previously with NYU); and Fan Zuo (Research Assistant and PhD Candidate). The authors would like to thank the volunteer Expert Stake- holders who helped identify gaps in research for estimating traffic measures that could benefit from using elements contained within the basic safety messages and who provided feedback on traffic measures that should be developed as part of this project. The volunteer Expert Stakeholders included Professor Mecit Cetin, Old Dominion University; Professor Mohammed Hadi, Florida Inter- national University; Professor John Hourdos, University of Minnesota; Professor Asad Khattak, University of Tennessee; Assistant Professor Kun Xie, Old Dominion University; Dr. Michail Xyntarakis, Cambridge Systematics; and Professor Yunlong Zhang, Texas A&M University. The authors would also like to thank Dr. Karl Wunderlich, Noblis (Director of Surface Transportation), Dr. Bekir Bartin (NYU C2SMART), Yubin Shen (NYU C2SMART), and Di Sha (NYU) for their review and feedback. CRP STAFF FOR NCHRP RESEARCH REPORT 997 Christopher J. Hedges, Director, Cooperative Research Programs Waseem Dekelbab, Deputy Director, Cooperative Research Programs, and Manager, National Cooperative Highway Research Program Sid Mohan, Associate Program Manager, Implementation and Technology Transfer, National Cooperative Highway Research Program Camille Crichton-Sumners, Senior Program Officer Tyler Smith, Senior Program Assistant Natalie Barnes, Director of Publications Heather DiAngelis, Associate Director of Publications NCHRP PROJECT 03-137 PANEL Field of Traffic—Area of Operations and Control Mo Zhao, Virginia Transportation Research Council, Charlottesville, VA (Chair) Matthew W. Bond, Virginia Department of Transportation, Staunton, VA Marco Cameron, Texas Department of Transportation, Austin, TX Nikola Ivanov, University of Maryland, College Park, Grandville, MI Taylor Li, University of Texas, Arlington, Arlington, TX Ray Starr, Minnesota Department of Transportation, Roseville, MN Xianding Tao, District Department of Transportation, Washington, DC Jon T. Obenberger, FHWA Liaison

NCHRP Research Report 997 provides state departments of transportation (DOTs) with a summary of key findings and recommendations for practitioners on the use of basic safety messages (BSMs) using algorithmic methods. This information is intended to supplement traditional estimation approaches to be used for performance monitoring, traffic management, and traveler information. Use of these findings and recommendations will contribute to increased situational awareness for drivers, pedestrians, and system operators. Basic safety message (BSM) data are used in connected vehicles to communicate safety and mobility information with nearby vehicles, personal communications devices, and trans- portation infrastructure equipment. Initially intended to support safety applications, BSMs provide data such as a vehicle’s speed, position, size, and brake system status. These attributes cannot be measured using traditional surveillance technology. There is an opportunity to use BSM data for managing traffic on arterials and freeways, in work zones, and in systemwide surface transportation systems. Expanding the use of BSM data will allow state DOTs to increase the geographic area these systems monitor and reduce reliance on expensive infra- structure sensors. BSMs could be used for performance monitoring, traffic management, and traveler information, contributing to a more resilient transportation system and better situational awareness for drivers, pedestrians, and system operators. Under NCHRP Project 03-137, “Algorithms to Convert Basic Safety Messages into Traffic Measures,” Noblis, Inc., developed, tested, and validated algorithms for seven traffic measures. The resulting research report (NCHRP Research Report 997) documents the methodology, literature review, gaps in traffic measures research, and findings from the project. The report also documents the process for selecting the following seven traffic measures: travel time, space mean speed, queue length/count, mean time to detect and verify incidents, hard braking, deceleration rate to avoid collision, and time-to-collision with disturbance. For each measure, the report includes a discussion of the requirements; algorithmic approach; data used for algorithm development, testing, and validation; test and validation plans; and results. The algorithms were validated using simulation and field data for various market penetrations of connected vehicle technology and for various use cases. Final deliverables include validated algorithms, source code, and supporting software documentation for seven high-priority measures. Guidance and tips for customizing the algorithms for specific conditions are provided to allow other researchers to adapt the algorithms as needed. NCHRP Research Report 997 and the final PowerPoint presentation provide state transportation agencies with tools and techniques to integrate safety into traditional transportation planning and to measure the effectiveness and success of their integration efforts. Access to these deliverables along with the research report and the Power- Point presentation can be obtained by searching the National Academies Press website (nap. nationalacademies.org) for NCHRP Research Report 997. F O R E W O R D By Camille Crichton-Sumners Staff Officer Transportation Research Board

Note: Photographs, figures, and tables in this report may have been converted from color to grayscale for printing. The electronic version of the report (posted on the web at nap.nationalacademies.org) retains the color versions. 1 Summary 3 Chapter 1 Introduction 3 1.1 Background 3 1.2 Research Objective 4 1.3 Purpose of the Report 4 1.4 Summary Review of Literature 14 1.5 Organization of Report 15 Chapter 2 Data for Developing Algorithms to Convert BSMs into Traffic Measures 15 2.1 Data Used for Algorithm Development, Testing, and Validation 21 2.2 Approach to Generate Synthetic BSMs Using TCA 22 2.3 Lessons Learned from Data Preparation and Fusion 24 Chapter 3 Algorithms to Convert BSMs into Mobility Measures 24 3.1 Travel Time 29 3.2 Space Mean Speed 34 3.3 Queue Length 47 3.4 Mean Time to Detect and Verify Incidents 55 Chapter 4 Algorithms to Convert BSMs into Safety Measures 55 4.1 Hard Braking 71 4.2 Deceleration Rate to Avoid Collision 86 4.3 Time to Collision with Disturbance 99 Chapter 5 Contributions and Recommendations 99 5.1 Contributions 102 5.2 Recommendations to the Practitioners and Agencies 102 5.3 Recommendations for Future Research 104 References 109 Abbreviations A-1 Appendix A Literature Review on Algorithms to Convert Basic Safety Messages into Traffic Measures B-1 Appendix B Down-Selected High-Priority Measures C-1 Appendix C Algorithm Execution Time Analysis D-1 Appendix D Sensitivity Analysis for Time to Collision with Disturbance Distribution E-1 Appendix E Guide to Downloading Code and Data C O N T E N T S