Measuring Road Safety Using Surrogate Events provides researchers and practitioners with the tools they need to quickly and effectively measure traffic safety. As traditional crash-based safety analyses are being undermined by today's growing use of intelligent vehicular and road safety technologies, crash surrogates--or near misses--can be more effectively used to measure the future risk of crashes. This book advances the idea of using these near-crash techniques to deliver quicker and more adequate measurements of safety. It explores the relationships between traffic conflicts and crashes using an extrapolation of observed events rather than post-crash data, which is significantly slower to obtain. Readers will find sound estimation methods based on rigorous scientific principles, offering compelling new tools to better equip researchers to understand road safety and its factors. - Consolidates the latest updates/ideas from disparate places into a single resource - Establishes a consistent use of key terms, definitions and concepts to help codify this emerging field - Contains numerous application-oriented case studies throughout - Includes learning aids, such as chapter objectives, a glossary, and links to data used in examples

This book increases the level of knowledge on road safety contexts, issues and challenges; shares what can currently be done to address the variety of issues; and points to what needs to be done to make further gains in road safety.

This report presents a framework for measuring safety in automated vehicles (AVs): how to define safety for AVs, how to measure safety for AVs, and how to communicate what is learned or understood about AVs.

TRB's National Cooperative Highway Research Program (NCHRP) Report 665: Identification of Vehicular Impact Conditions Associated with Serious Ran-off-Road Crashes quantifies the characteristics of ran-off-road crashes and identifies appropriate impact conditions for use in full-scale crash testing.

There are approximately 4,000 fatalities in crashes involving trucks and buses in the United States each year. Though estimates are wide-ranging, possibly 10 to 20 percent of these crashes might have involved fatigued drivers. The stresses associated with their particular jobs (irregular schedules, etc.) and the lifestyle that many truck and bus drivers lead, puts them at substantial risk for insufficient sleep and for developing short- and long-term health problems. Commercial Motor Vehicle Driver Fatigue, Long-Term Health and Highway Safety assesses the state of knowledge about the relationship of such factors as hours of driving, hours on duty, and periods of rest to the fatigue experienced by truck and bus drivers while driving and the implications for the safe operation of their vehicles. This report evaluates the relationship of these factors to drivers' health over the longer term, and identifies improvements in data and research methods that can lead to better understanding in both areas.

Data Analytics for Intelligent Transportation Systems provides in-depth coverage of data-enabled methods for analyzing intelligent transportation systems (ITS), including the tools needed to implement these methods using big data analytics and other computing techniques. The book examines the major characteristics of connected transportation systems, along with the fundamental concepts of how to analyze the data they produce. It explores collecting, archiving, processing, and distributing the data, designing data infrastructures, data management and delivery systems, and the required hardware and software technologies. It presents extensive coverage of existing and forthcoming intelligent transportation systems and data analytics technologies. All fundamentals/concepts presented in this book are explained in the context of ITS. Users will learn everything from the basics of different ITS data types and characteristics to how to evaluate alternative data analytics for different ITS applications. They will discover how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications, along with key safety and environmental applications for both commercial and passenger vehicles, data privacy and security issues, and the role of social media data in traffic planning. Data Analytics for Intelligent Transportation Systems will prepare an educated ITS workforce and tool builders to make the vision for safe, reliable, and environmentally sustainable intelligent transportation systems a reality. It serves as a primary or supplemental textbook for upper-level undergraduate and graduate ITS courses and a valuable reference for ITS practitioners. - Utilizes real ITS examples to facilitate a quicker grasp of materials presented - Contains contributors from both leading academic and commercial domains - Explains how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications - Includes exercise problems in each chapter to help readers apply and master the learned fundamentals, concepts, and techniques - New to the second edition: Two new chapters on Quantum Computing in Data Analytics and Society and Environment in ITS Data Analytics

Tiivistelmä. - Sammandrag.