Texas A&M Transportation Institute (TTI) Associate Research Scientist Subasish Das will publish the book Artificial Intelligence in Highway Safety (1st edition) September 29, 2022, with CRC Press/Routledge, part of the Taylor & Francis Group. In this book, Das discusses advances in the highway safety field that involve artificial intelligence (AI) technologies. He specifically addresses how AI’s predictive powers can help safety professionals, policymakers and practitioners solve complex problems to make highways safer for the public and other road users.
Artificial Intelligence in Highway Safety is suitable for everyone with an interest in highway safety and AI — already a fast-growing research trend in the transportation industry. The book covers both theoretical and practical elements of highway safety, making it accessible for a variety of readers from researchers, legislators and students to safety planners, managers and employees. Each chapter includes theory, relevant information, and real-world examples to equip readers for their next step — whether that’s writing a research paper, managing a safety planning project or installing equipment at a roadside. The book’s chapters include:
- highway safety and AI basics,
- supervised and unsupervised learning, and
- disruptive and emerging technologies in highway safety.
Recognized as a highway safety expert, Das works in TTI’s Roadway Safety Division. He is the author or co-author of more than 110 technical papers or research reports. He earned his M.S. and Ph.D. in civil engineering from the University of Louisiana at Lafayette. His research interests include roadway safety, roadway design, and operational issues and solutions of both fields. Das is an expert in database management, statistical analysis and machine learning, spatial analysis with geographic information system tools, interactive data visualization, and deep learning for connected and autonomous vehicles.
“I was contacted by CRC Press in 2019 about a book proposal on applications of AI in highway safety,” says Das. “After giving it some thought, I accepted the offer. This book has been designed for learners at all levels who have interest in both AI and highway safety. Each chapter contains case studies and research problems with data and codes, which can be very helpful for all learners. The book also contains several appendices with practical research problems and solutions. The final chapter of the book provides a future outlook of applying AI in highway safety including the U.S. Department of Transportation adopted Safe System approach and its future directions. The open-source version of the book (currently a repository development has been ongoing) will be regularly updated with newer research problems and solutions.”