Secure CheckoutPersonal information is secured with SSL technology.
Free ShippingFree global shipping
No minimum order.
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.
- 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
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
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:
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.
Zachry Department of Civil and Environmental Engineering, Texas A&M University, College Station, USA
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.
University of Wisconsin‐Milwaukee, Department of Civil and Environmental Engineering, Milwaukee, WI, USA
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.
Texas A&M University, Texas A&M Transportation Institute, College Station, TX, USA
Elsevier.com visitor survey
We are always looking for ways to improve customer experience on Elsevier.com.
We would like to ask you for a moment of your time to fill in a short questionnaire, at the end of your visit.
If you decide to participate, a new browser tab will open so you can complete the survey after you have completed your visit to this website.
Thanks in advance for your time.