Artificial Intelligence in Highway Safety

Subasish Das (Texas State University)

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Paperback

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English

CRC Press
04 October 2024

Engineering: general; Automatic control engineering; Civil engineering, surveying & building; Automotive technology & trades; Artificial intelligence

Artificial Intelligence in Highway Safety provides cutting-edge advances in highway safety using AI. The author is a highway safety expert. He pursues highway safety within its contexts, while drawing attention to the predictive powers of AI techniques in solving complex problems for safety improvement. This book provides both theoretical and practical aspects of highway safety. Each chapter contains theory and its contexts in plain language with several real-life examples. It is suitable for anyone interested in highway safety and AI and it provides an illuminating and accessible introduction to this fast-growing research trend.

Material supplementing the book can be found at https://github.com/subasish/AI_in_HighwaySafety. It offers a variety of supplemental materials, including data sets and R codes.

By: Subasish Das (Texas State University)
Imprint: CRC Press
Country of Publication: United Kingdom
Dimensions: Height: 234mm, Width: 156mm,
Weight: 653g
ISBN: 9781032204734
ISBN 10: 1032204737
Pages: 338
Publication Date: 04 October 2024
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

1. Introduction 2. Highway Safety Basics 3. Artificial Intelligence Basics 4. Matrix Algebra and Probability 5. Supervised Learning 6. Unsupervised Learning 7. Deep Learning 8. Natural Language Processing 9. Explainable AI 10. Disruptive and Emerging Technologies in Highway Safety 11. Conclusions and Future Needs

Subasish Das is an associate research scientist at the Texas A&M Transportation Institute (TTI) of the Texas A&M University System. He received his M.S. and Ph.D. in Civil Engineering from the University of Louisiana at Lafayette in 2012 and 2015 respectively. His primary fields of research interest are roadway safety, roadway design, and associated operational issues. He is a systems engineer by training with hands-on experience on Six Sigma and Lean Engineering. His major areas of expertise include database management, statistical analysis and machine learning with emphasis in safety and transportation operations, spatial analysis with modern web GIS tools, interactive data visualization, and deep learning tools for CV/AV technologies. Dr. Das is the author or co-author of over 110 technical papers or research reports. The AASHTO Research Advisory Committee (RAC) awarded one of his research reports as 2014 AASHTO Sweet Sixteen High Value Research Project. He is an active member of ITE, APBP, and ASCE. He is an Eno Fellow. His other awards include 2018 TTI Young Researcher Awards, 2017 Urban Street Symposium Best Paper Award, 2014 and 2015 Gulf Region ITS Best Paper Award