Intelligent Transportation Related Complex Systems and Sensors

Abstract

Building around innovative services related to different modes of transport and traffic management, intelligent transport systems (ITSs) are being widely adopted world- wide to improve the efficiency and safety of the transportation system. They enable users to be better informed and make safer, more coordinated, and smarter decisions on the use of transport networks. Current ITSs are complex systems, made up of several components/sub-systems characterized by time-dependent interactions among themselves. Some examples of these transportation-related complex systems include road traffic sensors, autonomous/automated cars, smart cities, smart sensors, virtual sensors, traffic control systems, smart roads, logistics systems, smart mobility systems, and many others that are emerging from niche areas. The efficient operation of these complex systems require (i) efficient solutions to the issues of sensors/actuators used to capture and control the physical parameters of these systems as well as the quality of data collected from these systems; (ii) tackling complexities using simulations and analytical modelling techniques; (iii) applying optimization techniques to improve the performance of these systems. This book out of the Special Issue on Intelligent Transportation Related Complex Systems and Sensors emerges as a result of the crucial need for improving transportation support in different domains and parts of the world by finding solutions to the rich yet non-trial and unexpected behaviour resulting from the complexity of ITS. It includes twenty-four papers, which cover scientific concepts, frameworks, architectures, and various other ideas on analytics, trends, and applications of transportation related data. The 24 papers/chapters contained in this book propose solutions to various issues and broadly grouped into four classes/parts, namely, the following ones: 1. Traffic safety and security. 2. Autonomy and path planning. 3. Traffic density. 4. Traffic analytics and prediction.