Highway Safety Analytics and Modeling - Edition 2 - By Dominique Lord, Xiao Qin and Srinivas R. Geedipally Elsevier Educate

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Highway Safety Analytics and Modeling,

Edition 2

By Dominique Lord, Xiao Qin and Srinivas R. Geedipally

Publication Date: 01 Dec 2025

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Highway Safety Analytics and Modeling, Second Edition comprehensively covers the key elements for effective transportation engineering and policy decisions based on highway safety data analysis in a single reference. It includes all aspects of the decision-making process, from collecting and assembling data to developing models and evaluating results. It discusses the challenges of working with crash and naturalistic data, identifies problems, and proposes well-researched methods to solve them. It 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.

This thoroughly updated second edition updates the material contained in the book based on the latest advancements in highway safety research as well as feedback from readers. It includes entirely new sections on topics such as digital twins as a source of data, model validation, extreme value models, temporal instability, joint crash frequency and severity modeling, sample size, quasi-induced exposure method, autonomous vehicle safety estimate, and more.

This book serves as a valuable reference for students, researchers, and practitioners alike. It provides more examples and exercises to help in using the book for courses, and it continues to complement the Highway Safety Manual (HSM) published by the American Association of State Highway and Transportation Officials (AAHSTO), thus helping in the training of engineers and practitioners to better understand the concepts and methods outlined in the forthcoming HSM.

Key Features

Offers a better understanding of the nuances associated with safety data (such as low sample mean, small sample size, and repeated measurement)
Provides examples and exercises not available in research papers as well as learning aids such as online datasets and slides
Complements the Highway Safety Manual by the American Association of State Highway and Transportation Officials

About the author

By Dominique Lord, Zachry Department of Civil and Environmental Engineering, Texas A&M University, College Station, TD, USA; Xiao Qin, University of Wisconsin-Milwaukee, Department of Civil and Environmental Engineering, Milwaukee, WI, USA and Srinivas R. Geedipally, Texas A&M Transportation Institute, Texas A&M University, Arlington, TX, USA

Section 1: Introduction Section
1. Theory and background
2. Fundamentals and data collection
3. Crash–frequency modeling
4. Crash-severity modeling

Section 2: Highway safety analyses
5. Exploratory analyses of safety data
6. Application of Models for Safety Analyses
7. Before–afterstudies in highway safety
8. Identification of hazardous sites
9. Models for spatial data
10.Capacity, mobility, and safety

Section 3: Alternative safety analyses
11. Surrogate safetymeasures
12. Data mining and machine learning techniques

Appendices:
A. Negative binomial regression models and estimation methods
B. Computing codes
C. List of exercise datasets

ISBN: 9780443300264

Page Count: 440

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Transportation safety researchers, engineers, analysts, and designers, upper undergraduate and graduate students studying highway safety

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