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Highway Safety Analytics and Modeling Summary

Highway Safety Analytics and Modeling by Dominique Lord (Zachry Department of Civil and Environmental Engineering, Texas A&M University, College Station, USA)

Highway Safety Analytics and Modeling comprehensively covers the key elements needed to make effective transportation engineering and policy decisions based on highway safety data analysis in a single. reference. The book includes all aspects of the decision-making process, from collecting and assembling data to developing models and evaluating analysis results. It discusses the challenges of working with crash and naturalistic data, identifies problems and proposes well-researched methods to solve them. Finally, the book examines the nuances associated with safety data analysis and shows how to best use the information to develop countermeasures, policies, and programs to reduce the frequency and severity of traffic crashes.

About Dominique Lord (Zachry Department of Civil and Environmental Engineering, Texas A&M University, College Station, USA)

Dominique Lord is a Professor and A.P. and Florence Wiley Faculty Fellow in the Zachry Department of Civil and Environmental Engineering at Texas A&M University. His highway safety research has led to the development of new and innovative methodologies for analyzing crash data and has been used by researchers across the world in medicine, accounting, mathematics, statistics, biology, and engineering. He's been published extensively in peer-reviewed journals and presents his work regularly at international conferences. He is the recipient of numerous university, national and international awards. Xiao Qin is a Professor of Civil and Environmental Engineering, the Director of the University of Wisconsin-Milwaukee's Institute for Physical Infrastructure and Transportation (IPIT), and a licensed professional engineer in Civil Engineering. He chairs the Transportation Research Board (TRB) ACS20(1) Subcommittee on Safety Analytical Methods. He is the Editor of Transportation Research Record and Journal of Transportation Safety & Security, and an Advisory Board Member of Accident Analysis and Prevention. He has authored numerous journal articles, conference papers, and technical reports in highway safety and traffic operations, and a recipient of many best paper awards. Srinivas R. Geedipally is a Research Engineer in the Center for Transportation Safety at Texas A&M Transportation (TTI) and a registered Professional Engineer in the state of Texas. He received his doctorate from Texas A&M University and has been with TTI since 2005. He has participated in numerous traffic safety research projects with state and federal governments and international sponsors. Dr. Geedipally is an Advisory Board Member of Analytic Methods in Accident Research and has numerous papers published in high-standard international journals and conferences. He has been a key contributor in the development of the Highway Safety Manual, a two-time recipient of the Young Researcher Award, and a Fred Burggraf award winner from the Transportation Research Board.

Table of Contents

1. Introduction Part 1: THEORY AND BACKBROUND 2. Fundamentals and Data Collection 3. Crash-Frequency Modeling 4. Crash-Severity Modeling Part 2: HIGHWAY SAFETY ANALYSES 5. Exploratory Analysis of Safety Data 6. Cross-sectional and Panel Studies in Safety 7. Before-After Studies in Highway Safety 8. Identification of Hazardous Sites 9. Models for Spatial Data 10. Capacity, Mobility, and Safety Part 3: ALTERNATIVE SAFETY ANALYSES 11. Surrogate Safety Measures 12. Data Mining and Machine Learning Techniques Appendix A. Negative Binomial Regression Models and Estimation Methods B. Summary of Crash-Frequency and Crash-Severity Models in Highway Safety C. Computing Codes D. List of Exercise Data

Additional information

NGR9780128168189
9780128168189
0128168188
Highway Safety Analytics and Modeling by Dominique Lord (Zachry Department of Civil and Environmental Engineering, Texas A&M University, College Station, USA)
New
Paperback
Elsevier Science Publishing Co Inc
2021-02-25
500
N/A
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