Reprint
Intelligent Transportation Systems (ITS)
Edited by
April 2021
270 pages
- ISBN978-3-0365-0506-0 (Hardback)
- ISBN978-3-0365-0507-7 (PDF)
This book is a reprint of the Special Issue Intelligent Transportation Systems (ITS) that was published in
Computer Science & Mathematics
Engineering
Physical Sciences
Summary
This book presents collective works published in the recent Special Issue (SI) entitled " Intelligent Transportation Systems (ITS)". These works address problems of mobility, environmental pollution, and road safety, as well as their related applications. The presented problems are complex and involve a large number of research areas and many advanced technologies, such as communication, sensing, and control, which are used for managing a large amount of information. The applications vary and include fleet management, driving behavior, traffic control, trajectory planning, connected vehicles, and energy consumption efficiency. Recent advances in communication technologies are becoming fundamental for the development of new advances in fleet management, traffic control, and connected vehicles. This works collected in this Special Issue propose solution methodologies to address such challenges, analyze the proposed methodologies, and evaluate their performance. This book brings together a collection of multidisciplinary works applied to ITS applications in a coherent manner.
Format
- Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
driving behavior; car-following; truncated Gaussian Mixture model; Hidden Markov model; vehicle type identification; naturalistic driving study; lane change; decision-making system; vehicular communication; deep reinforcement learning; collision avoidance; connected and automated vehicle; intelligent transportation systems (ITSs); multiple conditional constraints for ITS; automated guided vehicle; greenhouse environment; spraying systems; deep leaning; intelligent transportation; vectorization coding; BRNN; traffic forecast; autonomous driving; behavioral decision; planning features; deep reinforcement learning; trajectory planning; simulation; parallel; multi-core; public transport; mass transit; OpenCL; open-pit mine; driving style recognition; K-means clustering; random forest; adaptive traffic signals; Intelligent Transportation Systems; Floating Car Data; traffic management; connected and autonomous vehicles; cooperative automated vehicles (CAV); cooperation; communication; V2X; C-ITS; ITS-G5; LTE 5G; maneuver planning; variable speed limit; traffic control; travel time; intelligent transportation system; mobility-on-demand; fleet-management; taxi; predictive strategies; RHC; Intelligent Transportation Systems; ITS architecture; fleet management; transit vehicles; ITS enabling technologies