Autorentext

K.V.R. Ravi Shankar is working as Associate Professor in the Department of Civil Engineering, NIT Warangal, Telangana, India. Prof. Ravi Shankar received his Ph.D. from IIT Bombay in the year 2011. He is having 20 Years of Experience in the field of teaching and research. His research interests centre on Innovative road safety strategies, Machine learning application for traffic management and Road Safety, Pedestrian behavioural analysis and modelling, Crowd behaviour modelling. Prof. Ravi Shankar guided 08 Ph.D. thesis works and 04 more are in progress. He also guided 64 M.Tech. project works. He is the author of about 90 publications in leading international journals and conferences. He was awarded the Young Researcher [Engineering] Award in the year 2020 by NIT Warangal Alumni Association. He is a recipient of research grants from SPARC, Department of Science and Technology and MoRTH and has a collaboration with Lund University, Sweden and UNSW, Australia. He worked on consultancy projects related to development of toolkits, traffic management planning, Intersection design and Road safety improvement. He is a reviewer of several transportation related journals and a prominent invited expert on road safety related topics.

Bhadradri Raghuram Kadali, currently working as Assistant Professor, in the Department of Civil Engineering, at National Institute of Technology, Warangal (NITW). Prof. Raghuram obtained his PhD degree from the IIT Bombay in 2017 and Masters in Transportation Engineering from NIT Warangal. He has 8 years of teaching and research experience. He has guided 01 Ph.D., 20 M.Tech dissertations, 05 B.Tech project works, and currently 3 research scholars are pursuing their Ph.D. Dr. Raghuram has successfully completed three externally funded R&D projects as principal investigator and associated with another 2 projects as co-principal investigator. He is currently working in traffic safety, pedestrian travel behavior and transportation planning. He has published 50 papers in reputed journals and international conferences

Klappentext

This book provides a comprehensive understanding of accident data collection, analysis, and the use of surrogate safety measures (SSMs) from both vehicular and pedestrian perspectives. It discusses the application of simulation tools for surrogate safety analysis, with an emphasis on risk estimation and the integration of machine learning techniques. This book also explores the use of augmented and virtual reality for road user training and assessment, as well as safety concerns related to automated and connected vehicles. Field case studies offer a realistic view of on-site assessments, safety implications, and measures for safety enhancement.

• Explores surrogate safety methods in detail, including the identification of surrogate measures and their applications.
• Examines various SSMs, such as Post-Encroachment Time and Time-to-Collision, and identifies suitable SSMs for mixed traffic conditions, highlighting their strengths and weaknesses.
• Discusses international codes and standards at appropriate points in each chapter.
• Covers statistical methods, including Support Vector Machines, binary logit models, and ordered logit models, for estimating severity levels.
• Includes worked examples and numerical problems for practical understanding. This book is intended for senior undergraduate and graduate students in road safety engineering, transportation, and civil engineering.

Inhalt

1. Introduction to Road Safety 2. Road Safety Scenario and Influencing Factors 3. Methods of Accident Data Collection 4. Methods of Accident Analysis 5. Surrogate Safety Measures 6. Surrogate Methods of Road Safety 7. Simulation and Surrogate Safety 8. Pedestrian Surrogate Safety Procedures 9. AI and ML applications for Surrogate Road Safety Analysis 10. Augmented and Virtual Reality in Road Safety 11. Automated Vehicle Safety and Future Scope