Intelligent Transportation Systems: Theory and Practice

1. Auflage 2023
ISBN: 978-981-19-7621-6
Verlag: Springer Nature Singapore

Buch, Englisch, 391 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 863 g

Reihe: Disruptive Technologies and Digital Transformations for Society 5.0

This book provides fundamental principles of intelligent transport systems with comprehensive insight and state of the art of vehicles, vehicular technology, connecting vehicles, and intelligent vehicles/autonomous intelligent vehicles. The book discusses different approaches for multiple sensor-based multiple-objects tracking, in addition to blockchain-based solutions for building tamper-proof sensing devices. It introduces various algorithms for security, privacy, and trust for intelligent vehicles. This book countermeasures all the drawbacks and provides useful information to students, researchers, and scientific communities. It contains chapters from national and international experts and will be essential for researchers and advanced students from academia, and industry experts who are working on intelligent transportation systems.

Zielgruppe

Research

Autoren/Hrsg.

Sreenath, Niladhuri

Tyagi, Amit Kumar

Fachgebiete

• Technische Wissenschaften Verkehrstechnik | Transportgewerbe Verkehrstechnologie: Allgemeines
• Mathematik | Informatik EDV | Informatik Angewandte Informatik
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik
• Technische Wissenschaften Verkehrstechnik | Transportgewerbe Fahrzeugtechnik
• Technische Wissenschaften Bauingenieurwesen Verkehrsingenieurwesen, Verkehrsplanung

Inhaltsverzeichnis

Wired Technology.- Wireless Technologies.- Introduction, History, Standardization, Frameworks, Models of Vehicular Networks.- Vehicular Ad Hoc Networks: Architectures, Research Issues, Challenges and Trends.- Vehicular Cloud Computing – Introduction to Cloud Based Vehicles.- Autonomous Vehicles and Intelligent Transportation Systems - A Framework of Intelligent Vehicles.- Realistic Vehicular Mobility Models for AIV.- An Integrated GPS/ IMU/ etc., Positioning Approach (based on Artificial Intelligence) Vehicle Navigation Using Global Views (using Machine Learning and Deep Learning).- Machine Learning and Deep Learning Techniques Enabled Intelligent Vehicles.- Edge Computing in Navigation of Intelligent Vehicles.

Über Autor(innen)

Amit Kumar Tyagi is an Assistant Professor (Senior Grade) and Senior Researcher at Vellore Institute of Technology (VIT), Chennai, India. He received his Ph.D. Degree from Pondicherry Central University, India. He is a Member of the IEEE society. His current research focuses on machine learning with big data, blockchain technology, data science, cyber-physical systems, smart and secure computing, and privacy. He has contributed to several projects such as “AARIN” and “P3-Block” to address some of the open issues related to privacy breaches in vehicular applications (such as parking) and medical cyber-physical systems.

Niladhuri Sreenath is a Professor in the Department of Computer Science and Information Technology at Puducherry Technological University, Puducherry India. His primary research interests are WDM optical networks, privacy, and trust. He obtained his Ph.D. in Computer Science from the Indian Institute of Technology, Madras, India.