This book gathers selected papers presented at the KES International Symposium on Smart Transportation Systems (KES-STS 2021). Modern transportation systems have undergone a rapid transformation in recent years, producing a range of technological innovations such as connected vehicles, self-driving cars, electric vehicles, Hyperloop, and even flying cars, and with them, fundamental changes in transport systems around the world. The book discusses current challenges, innovations, and breakthroughs in smart transportation systems, as well as transport infrastructure modelling, safety analysis, freeway operations, intersection analysis, and other related cutting-edge topics.

This book gathers selected papers presented at the KES International Symposium on Smart Transportation Systems (KES STS 2022). Modern transportation systems have undergone a rapid transformation in recent years, producing a range of technological innovations such as connected vehicles, self-driving cars, electric vehicles, Hyperloop, and even flying cars, and with them, fundamental changes in transport systems around the world. The book discusses current challenges, innovations, and breakthroughs in smart transportation systems, as well as transport infrastructure modeling, safety analysis, freeway operations, intersection analysis, and other related cutting-edge topics.

This book gathers selected papers presented at the KES International Symposium on Smart Transportation Systems (KES STS 2023). Modern transportation systems have undergone a rapid transformation in recent years, producing a range of technological innovations such as connected vehicles, self-driving cars, electric vehicles, Hyperloop, and even flying cars, and with them, fundamental changes in transport systems around the world. The book discusses current challenges, innovations, and breakthroughs in smart transportation systems, as well as transport infrastructure modeling, safety analysis, freeway operations, intersection analysis, and other related cutting-edge topics.

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.

This book contains papers presented at the 2021 International Conference on Smart Technologies and Systems for Internet of Things, held on November 26–27, 2021, in Shanghai, China. It covers topics like distributed processing for sensor data in CPS networks, approximate reasoning and pattern recognition for CPS networks, distributed processing in mobile networking, data analytics for social media sensor data integration, data platforms for efficient integration with CPS networks, virtualized and cloud-oriented resources for data processing for CPS networks, machine learning algorithms for CPS networks, data security and privacy in CPS networks, sensor fusion algorithms, sensor signal processing, data acquisition and preprocessing technology, intelligent computing, data mining methods and algorithms, big data system solutions and tools platform, intelligent control and intelligent management, and operational situation awareness utilizing big data-driven intelligence. It caters to postgraduate students, researchers, and practitioners specializing and working in related areas.

Transportation typically entails crucial “life-death” choices, delegating crucial decisions to an AI algorithm without any explanation poses a serious threat. Hence, explainability and responsible AI is crucial in the context of intelligent transportation. In Intelligence Transportation System (ITS) implementations such as traffic management systems and autonomous driving applications, AI-based control mechanisms are gaining prominence. Explainable artificial intelligence for intelligent transportation system tackling certain challenges in the field of autonomous vehicle, traffic management system, data integration and analytics and monitor the surrounding environment. The book discusses and inform researchers on explainable Intelligent Transportation system. It also discusses prospective methods and techniques for enabling the interpretability of transportation systems. The book further focuses on ethical considerations apart from technical considerations.

This book aims to introduce big data solutions in urban sustainability applications—mainly smart transportation and healthcare systems. It focuses on machine learning techniques and data processing approaches which have the capacity to handle/process huge, live, and complex datasets in real-time transportation and healthcare applications. For this, several state-of-the-art data processing approaches including data pre-processing, classification, regression, and clustering are introduced, tested, and evaluated to highlight their benefits and constraints where data is sensitive, real-time, and/or semi-structured.

This book provides comprehensive discussion on key topics related to the usage and deployment of AI in urban transportation systems including drones. The book presents intelligent solutions to overcome the challenges of static approaches in the transportation sector to make them intelligent, adaptive, agile, and flexible. The book showcases different AI-deployment models, algorithms, and implementations related to intelligent cyber physical systems (CPS) along with their pros and cons. Even more, this book provides deep insights into the CPS specifically about the layered architecture and different planes, interfaces, and programmable network operations. The deployment models for AI-based CPS are also included with an aim towards the design of interoperable and intelligent CPS architectures by researchers in future. The authors present hands on practical implementations, deployment scenarios, and use cases related to different transportation scenarios. In the end, the design and research challenges, open issues, and future research directions are provided.