Dominique Lord, Xiao Qin, Srinivas R. Geedipally

Highway Safety Analytics and Modeling

• Broschiertes Buch

Produktbeschreibung

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.

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Produktdetails

• Verlag: Elsevier / Elsevier Science & Technology
• Artikelnr. des Verlages: C2018-0-00207-8
• Seitenzahl: 500
• Erscheinungstermin: 25. Februar 2021
• Englisch
• Abmessung: 153mm x 231mm x 28mm
• Gewicht: 880g
• ISBN-13: 9780128168189
• ISBN-10: 0128168188
• Artikelnr.: 59412996

Autorenporträt

Dr. Dominique Lord is a professor and holder of the A.P. and Florence Wiley Faculty Fellowship in the Zachry Department of Civil and Environmental Engineering at Texas A&M University. Over the last 27 years, Dr. Lord has conducted numerous research studies in the United States, Canada, and across the world in highway design and safety. Dr. Lord's primary interests are conducting fundamental research on accident analysis methodology, new and innovative statistical methods for modeling motor vehicle collisions, and before-after evaluation techniques. He has extensive experience in data analysis techniques and developed new tools that have been used by engineers and scientists across the world. His other research interests include problems associated with the crash data collection process, safety audits, and traffic flow theory. He has had more than 150 papers published in peer-reviewed journals and more than 140 papers presented at international conferences with a peer-reviewed process.

Inhaltsangabe

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

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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