Estimating Effectiveness of Safety Treatments in the Absence of Crash Data: A Guide (2023)

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N AT I O N A L C O O P E R AT I V E H I G H W AY R E S E A R C H P R O G R A M NCHRP RESEARCH REPORT 1069 Estimating Effectiveness of Safety Treatments in the Absence of Crash Data A GUIDE R.J. Porter Kristin Kersavage Vikash Gayah Michael Dunn Kim Eccles VHB Raleigh, NC Bhagwant Persaud Toronto, ON Juan Medina University of Utah Salt Lake City, UT Subscriber Categories Operations and Traffic Management • Safety and Human Factors Research sponsored by the American Association of State Highway and Transportation Officials in cooperation with the Federal Highway Administration 2023 

NATIONAL COOPERATIVE HIGHWAY NCHRP RESEARCH REPORT 1069 RESEARCH PROGRAM Systematic, well-designed, and implementable research is the most Project 17-86 effective way to solve many problems facing state departments of ISSN 2572-3766 (Print) transportation (DOTs) administrators and engineers. Often, highway ISSN 2572-3774 (Online) problems are of local or regional interest and can best be studied by ISBN 978-0-309-69918-1 state DOTs individually or in cooperation with their state universities Library of Congress Control Number 2023945746 and others. However, the accelerating growth of highway transporta- © 2023 by the National Academy of Sciences. National Academies of tion results in increasingly complex problems of wide interest to high- Sciences, Engineering, and Medicine and the graphical logo are trade- way authorities. These problems are best studied through a coordinated marks of the National Academy of Sciences. All rights reserved. program of cooperative research. 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COOPERATIVE RESEARCH PROGRAMS CRP STAFF FOR NCHRP RESEARCH REPORT 1069 Waseem Dekelbab, Deputy Director, Cooperative Research Programs, and Manager, National Cooperative Highway Research Program David Jared, Senior Program Officer Mazen Alsharif, Senior Program Assistant Natalie Barnes, Director of Publications Heather DiAngelis, Associate Director of Publications Brendan Foht, Senior Editor NCHRP PROJECT 17-86 PANEL Field of Traffic—Area of Safety Bonnie S. Polin, Massachusetts Department of Transportation, Boston, MA (Chair) Paramvir S. Bhalia, Washington State Department of Transportation, Lacey, WA Kimberli R. Craft, Hoboken, NJ Matthew T. Enders, Washington State Department of Transportation, Olympia, WA Peter P. Hsu, Florida Department of Transportation, Tampa, FL Mohammad Jalayer, Rowan University, Glassboro, NJ Scott Neidert, Delaware Department of Transportation, Smyrna, DE Xiao Qin, University of Wisconsin, Milwaukee, Milwaukee, WI Shyam L. Sharma, Oregon Department of Transportation, Camas, WA Carol H. Tan, FHWA Liaison Kelly K. Hardy, AASHTO Liaison Bernardo B. Kleiner, TRB Liaison 

FOREWORD By David Jared Staff Officer Transportation Research Board NCHRP Research Report 1069: Estimating Effectiveness of Safety Treatments in the Absence of Crash Data: A Guide presents a guide for using alternative, or surrogate, measures of safety for developing crash modification factors (CMFs) and other quantifiable measures of safety performance. The guide establishes a vision for using surrogate safety measures in practice and provides information on a range of surrogate measures, including surrogate measure defi- nitions and applications, data collection methods, and study design principles. The guide includes six case studies and supports informed decision-making by state departments of transportation (DOTs) on whether to implement treatments evaluated with surrogate measures during project planning, project development, and other road safety management activities. CMFs and functions are developed from historical crash data and help safety professionals estimate the expected safety impacts of specific roadway treatments. There has been a significant amount of research to develop CMFs for common safety strategies, and many are included in the American Association of State and Highway Transportation Officials (AASHTO) Highway Safety Manual and Federal Highway Administration CMF Clearing- house. However, there are instances in which developing reliable CMFs with conventional crash-based evaluations may not be practical or possible. For example, using crash data to evaluate innovative intersection designs or new traffic control strategies requires multiple years of data collection to accumulate enough installations and crash history. Additionally, countermeasures that improve safety for crash types, such as bicycle, pedestrian, or other vulnerable road user crashes, are often lacking in quality CMFs because crash data is limited or not available. Research was needed to develop and apply new methods for developing CMFs or other quantifiable measures of safety for these cases, such as conflicts, speed changes, and lane deviations. Under NCHRP Project 17-86, “Estimating Effectiveness of Safety Treatments in the Absence of Crash Data,” VHB was asked to develop a guide for using alternative measures of safety for developing CMFs and functions and other quantifiable measures in the absence of crash data. The new measures were evaluated against established crash-based measures and spanned a range of site conditions, crash types, and crash severity. The guide describes various types of surrogate measures and offers a framework for organizing the surrogates, outlines options for collecting and measuring these surrogates, identifies treatments that could benefit from surrogate-based evaluations, and provides case study examples. 

In addition to NCHRP Research Report 1069, two deliverables are not included in the pub- lished report but are available on the National Academies Press website (nap.nationalacademies .org) by searching for NCHRP Research Report 1069. The deliverables are as follows: • A conduct of research report summarizing the entire effort, available as NCHRP Web-Only Document 369: Estimating Effectiveness of Safety Treatments in the Absence of Crash Data. • A memo that identifies mechanisms and channels for communicating and implementing this research. 

CONTENTS 1 Chapter 1 Introduction 4 Chapter 2  Vision for Surrogate Use in Practice 4 2.1  Treatment and Application Context 4 2.2  Selection of Surrogate Measures and Data Collection Approach 5 2.3  Assessing Quantitative Surrogate-Crash Linkages 7 2.4  Conduct Surrogate Evaluation 8 Chapter 3  Surrogate Measure Definitions 8 3.1  Surrogates That Identify Potential Conflicts Between Users 12 3.2  Surrogates That Measure Collision Avoidance Behaviors 14 3.3  Surrogates Obtained from Macroscopic Traffic-Level Measures 15 3.4  Surrogates That Measure User Attention, Choices, and Behavior 19 Chapter 4 Types of Data Collection Technologies for Surrogate Measurement 19 4.1  Video Cameras 20 4.2  Vehicle Detectors 21 4.3 Lidar 22 4.4  Probe Vehicles 22 4.5  Naturalistic Driving Studies 23 4.6  Microscopic Traffic Simulation 23 4.7  Test Track/Closed Course Studies 24 4.8  Laboratory-Based Simulators 24 4.9  Field Observations 25 4.10  Crash Simulation 26 Chapter 5  Study Design and Statistical Analysis Considerations 26 5.1  Evaluating Treatments with Surrogates 32 5.2  Establishing and Applying Surrogate-Crash Linkages 34 5.3  Transferability of Surrogate Findings 36 Chapter 6 Types of Treatments for Evaluation with Surrogate Measures 36 6.1 How to Determine if a Treatment is a Strong Candidate for a Surrogate- Based Evaluation 37 6.2  What Treatments Can Benefit from Surrogate Measures of Safety? 40 Chapter 7  Case Studies 40 7.1  Leading Pedestrian Interval (LPI) Evaluation in Bellevue, Washington 43 7.2  Traffic Signal Coordination Evaluation in Salt Lake City, Utah 47 7.3 Surrogate-Based Evaluation of Sequential Flashing Chevron Signs on Rural, Two-lane Highways 

50 7.4  Surrogate Measures as Crash Precursors 52 7.5  Effect of Geometric Design Consistency on Road Safety 55 7.6 Crash and Crash-Surrogate Events: Exploratory Modeling with Naturalistic Driving Data 57 Chapter 8  Summary and Recommendations for Future Work 59 References 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.