This book discusses transport systems and the implementation of related public policy - a relevant topic with contemporary traffic congestion, environmental intrusion, transport safety, and budget issues. It is a resource for both experienced researchers and those new to the field.

This unique book explains how to think systematically about public transportation through the lens of physics models. The book includes aspects of system design, resource management, operations and control. It presents both, basic theories that reveal fundamental issues, and practical recipes that can be readily used for real-world applications. The principles conveyed in this book cover not only traditional transit modes such as subways, buses and taxis but also the newer mobility services that are being enabled by advances in telematics and robotics.Although the book is rigorous, it includes numerous exercises and a presentation style suitable for senior undergraduate or entry-level graduate students in engineering. The book can also serve as a reference for transportation professionals and researchers keen in this field.

Container transportation is the predominant mode of inter-continental cargo traffic. Since container ships and port terminals involve a huge capital investment and significant daily operating costs, it is of crucial importance to efficiently utilize the internal resources of container terminals and transportation systems. Today there is an ongoing trend to use automated container handling and transportation technology, in particular, in countries with high labour costs. This in turn requires highly sophisticated control strategies in order to meet the desired performance measures. The primary objective of this book is to reflect these recent developments and to present new insights and successful solutions to operational problems of automated container terminals and transportation systems. It comprises reports on the state of the art, applications of quantitative methods, as well as case studies and simulation results. Its contributions are written by leading experts from academia and business. The book addresses practitioners as well as academic researchers in logistics, transportation, and management.

The Intelligent Systems Series encompasses theoretical studies, design methods, and real-world implementations and applications. It publishes titles in three core sub-topic areas: Intelligent Automation, Intelligent Transportation Systems, and Intelligent Computing. Titles focus on professional and academic reference works and handbooks. This volume, Advances in Artificial Transportation Systems and Simulation, covers hot topics including driver assistance systems; cooperative vehicle-highway systems; collision avoidance; pedestrian protection; image, radar and lidar signal processing; and V2V and V2I communications. The readership for the series is broad, reflecting the wide range of intelligent systems interest and application, but focuses on engineering (in particular automation, control, mechatronics, robotics, transportation, automotive, aerospace), electronics and electronic design, and computer science. - Provides researchers and engineers with up to date research results and state-of-the art technologies in the area of intelligent vehicles and transportation systems - Includes case studies plus surveys of the latest research - Covers hot topics including driver assistance systems; cooperative vehicle-highway systems; collision avoidance; pedestrian protection; image, radar and lidar signal processing; V2V and V2I communications

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

"This book provides a rigorous and comprehensive coverage of transportation models and planning methods and is a must-have to anyone in the transportation community, including students, teachers, and practitioners." Moshe Ben-Akiva, Massachusetts Institute of Technology.