Highway Safety Analytics and Modeling

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

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