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Highway Safety Analytics and Modeling - 1st Edition - ISBN: 9780128168189

Highway Safety Analytics and Modeling

1st Edition

Authors: Dominique Lord Xiao Qin Srinivas R. Geedipally
Paperback ISBN: 9780128168189
Imprint: Elsevier
Published Date: 1st March 2021
Page Count: 360
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Highway Safety Analytics and Modeling covers the key elements needed for making effective transportation engineering and policy decisions based on highway crash data analysis. It covers all aspects of the decision-making process, from collecting and assembling data to making decisions based on the results of the analyses. The book discusses the challenges with crash and naturalistic data, identifying problems and proposing best methods to solving them. It examines the nuances associated with crash data analysis, showing how to develop countermeasures, policies, and programs to reduce the frequency and severity of traffic crashes.

Key Features

  • Complements the Highway Safety Manual by the American Association of State Highway and Transportation Officials, which can be challenging for students and working professionals to use
  • Provides examples and case studies for each model and method
  • Includes learning aids such as online data, examples and solution to problems


Transportation safety researchers, graduate students, engineers, analysts, and designers

Table of Contents

1. Introduction

2. Fundamentals and Data Collection
3. Crash-Frequency Modeling
4. Crash-Severity Modeling

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

11. Surrogate Safety Measures
12. Data Mining and Machine Learning Techniques

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


No. of pages:
© Elsevier 2021
1st March 2021
Paperback ISBN:

About the Authors

Dominique Lord

Dominique Lord is Professor of Civil 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 peer-reviewed journals and presents his work regularly at international conferences.

Affiliations and Expertise

Zachry Department of Civil and Environmental Engineering, Texas A&M University, College Station, USA

Xiao Qin

Xiao Qin is Professor of Civil and Environmental Engineering at the University of Wisconsin-Milwaukee and a registered Professional Engineer. He is 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.

Affiliations and Expertise

University of Wisconsin‐Milwaukee, Department of Civil and Environmental Engineering, Milwaukee, WI, USA

Srinivas R. Geedipally

Srinivas R. Geedipally received his doctorate from Texas A&M University and has been with Texas A&M Transportation Institute since 2005. He is currently the Associate Research Engineer in the Center for Transportation Safety and a registered Professional Engineer in the state of Texas. He has more than sixty papers published in high-standard international journals and conferences. Dr. Geedipally has participated in numerous traffic safety research projects with state and federal governments and international sponsors. 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.

Affiliations and Expertise

Texas A&M University, Texas A&M Transportation Institute, College Station, TX, USA

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