The book provides a broad overview of the challenges and recent developments in the field of smart mobility and transportation, including technical, algorithmic and social aspects of smart mobility and transportation. It reviews new ideas for services and platforms for future mobility. New concepts of artificial intelligence and the implementation in new hardware architecture are discussed. In the context of artificial intelligence, new challenges of machine learning for autonomous vehicles and fleets are investigated. The book also investigates human factors and social questions of future mobility concepts. The goal of this book is to provide a holistic approach towards smart transportation. The book reviews new technologies such as the cloud, machine learning and communication for fully atomatized transport, catering to the needs of citizens. This will lead to complete change of concepts in transportion.

Emphasizing a sustainable and green approach, this new book presents an overview of state-of-the-art AI strategies for solving transportation challenges around the world, with a focus on traffic management, traffic safety, public transportation, urban mobility, and pollution mitigation. The book examines modern AI technologies such as IoT, cloud computing, machine learning, and neural networking in the context of fully automated transportation that meets current requirements. The volume provides an informative review of the difficulties and recent developments in smart mobility and transportation, encompassing technical, algorithmic, and social elements. The volume examines innovative service and platform concepts for future mobility. Artificial intelligence principles are examined as well as their implementation in modern hardware architecture. New machine learning issues for autonomous vehicles and fleets are investigated in the framework of artificial intelligence. In addition, the book investigates the human dynamics and social implications of future mobility concepts. Highlighting the research directions in this field, Artificial Intelligence for Future Intelligent Transportation: Smarter and Greener Infrastructure Design will be of value for researchers in cybersecurity, machine learning, data analysis, and artificial intelligence. Ethical hackers, students, and faculty will find useful information here as well.

The Future of Intelligent Transport Systems considers ITS from three perspectives: users, business models and regulation/policy. Topics cover in-vehicle applications, such as autonomous driving, vehicle-to-vehicle/vehicle-to-infrastructure communication, and related applications, such as personalized mobility. The book also examines ITS technology enablers, such as sensing technologies, wireless communication, computational technology, user behavior as part of the transportation chain, financial models that influence ITS, regulations, policies and standards affecting ITS, and the future of ITS applications. Users will find a holistic approach to the most recent technological advances and the future spectrum of mobility.

New technologies and computing methodologies are now used to address the existing issues of urban traffic systems. The development of computational intelligence methods such as machine learning and deep learning, enables engineers to find innovative solutions to guide traffic in order to reduce transportation and mobility problems in urban areas. This volume, Computational Intelligence for Sustainable Transportation and Mobility, presents several computing models for intelligent transportation systems, which may hold the key to achieving sustainable development goals by optimizing traffic flow and minimizing associated risks. The book begins with the basic computational Intelligence techniques for traffic systems and explains its applications in vehicular traffic prediction, model optimization, behavior analysis, traffic density estimation, and more. The main objectives of this book are to present novel techniques developed, new technologies and computational intelligence for sustainable mobility and transportation solutions, as well as giving an understanding of some Industry 4.0 trends. Readers will learn how to apply computational intelligence techniques such as multiagent systems (MAS), whale optimization, artificial Intelligence (AI), deep neural networks (DNNs) so that they can to develop algorithms, models, and approaches for sustainable transportation operations. Key Features: - Provides an overview of machine learning models and their optimization for intelligent transportation systems in urban areas - Covers classification of traffic behavior - Demonstrates the application of artificial immune system algorithms for traffic prediction - Covers traffic density estimation using deep learning models - Covers Fog and edge computing for intelligent transportation systems - Gives an IoT and Industry 4.0 perspective about intelligent transportation systems to readers - Presents a current perspective on an urban hyperloop system for India

Editor Biography:Gaetano Fusco is Associate Professor of Transport at the Faculty of Engineering of the University of Roma "La Sapienza", where he teaches "Traffic Engineering and Intelligent Transportation Systems". From 1992 to 2005 he has been Assistant professor. On 2014 he has been qualified as Full Professor.He is a scientific expert of the Italian Ministry of University and Research and reviewer of several Research and Development projects funded by the Ministry of University and Research and by the Ministry o the Industry. He has been the Principal investigator of several research projects funded by the Faculty of Engineering and was participating in various national and international research projects. His research activity, reported in more than 80 papers published on the national and international scientific literature, has tackled numerous issues of the transport systems engineering, as demand and supply models, methods and regulation for public transit planning and design. Nevertheless, it has been addressed mainly to Intelligent Transportation Systems, in particular: models and methods for traffic signal coordination, traveler information systems design, modeling and detection of traffic incidents, traffic state forecasting.Book Description:Intelligent Transport Systems (ITS): Past, Present and Future Directions introduces the reader to the fundamentals of the ITS. It provides an overview of their evolution, starting from the earliest experiments on the route guidance systems in the 70s to their current deployment, and discusses the main challenges to face for their future development.Target Audience:The target audience for this book is represented by graduate students, practitioners, and researchers interested in having a general overview of the fundamentals of the Intelligent Transportation Systems and of their evolution, starting from the earliest experiments on route guidance systems up to the current deployment and the perspectives for their future development.

These proceedings collect selected papers from the 8th International Conference on Green Intelligent Transportation Systems and Safety held in Changchun on July 1-2, 2017. The selected works, which include state-of-the-art studies, are intended to promote the development of green mobility and intelligent transportation technology to achieve interconnectivity, resource sharing, flexibility and higher efficiency. They offer valuable insights for researchers and engineers in the fields of Transportation Technology and Traffic Engineering, Automotive and Mechanical Engineering, Industrial and Systems Engineering, and Electrical Engineering.

This book is a selection of the best and peer-reviewed articles presented at the CUPUM (Computers in Urban Planning and Urban Management) conference, held in the second week of July 2015 at MIT in Boston, USA. The contributions provide state-of the art overview of the availability and application of Planning Support Systems (PSS) in the framework of Smart Cities.