Modelling and simulation of urban traffic systems: present and future

Abstract

The conflict of supply and demand in urban traffic system causes serious problems nowadays owing to rapid urbanisation worldwide, including traffic congestion, air pollution, etc. In this paper, the recent development of modelling and simulation of urban traffic systems is briefly overviewed, where the macro-, micro-and meso-scopic simulation models, especially the microscopic models are discussed. Three widely used microscopic traffic simulation models are analysed and the new generation traffic simulation technologies for Intelligent Transportation Systems (ITS) are discussed from the perspectives of software technology, hardware technology, and methodologies. The existing problems and challenges in modelling and simulation of urban traffic systems are evaluated and the latest trends and the potential solutions are suggested. Keywords: modelling and simulation; urban traffic system; present and future; ITS; intelligent transportation system. 2 F. Qiao et al. Reference to this paper should be made as follows: Qiao, F., Liu, T., Sun, H., Guo, L. and Chen, Y. (2021) 'Modelling and simulation of urban traffic systems: present and future', Int.. His research interests include modelling and simulation, intelligent computation, control theory and application. Currently, he is acting as the EiC of the International Journal of Simulation and Process Modelling, an EB member of the International Journal of Modelling, Identification and Control, and he serves on many international conferences as IPC and OPC members. Tao Liu is a master's degree student of the Faculty of Information and Control Engineering, SJZU and he completed his Bachelor's degree in Automation at SJZU in July 2018. His research interests include modelling and simulation, intelligent traffic systems and optimisation. Haochen Sun is currently a Doctoral candidate in 2016 and 2019, respectively; and he was appointed as the General Secretary of ISSPM 2018. His research interests include modelling and simulation for complex systems, optimisation theory and application, machine learning, artificial intelligence and energy management for hybrid electric vehicles. Lingzhong Guo obtained his PhD degree in Control Engineering from Bristol Robotics Laboratory (BRL), UWE in 2003. Currently, he is a Lecturer at the Department of Automatic Control and Systems Engineering, the University of Sheffield, UK. His research interest covers the modelling, identification, and simulation of complex systems, adaptive and intelligent control, and analysis and control of PDEs. Yifan Chen is a master's degree student of the Faculty of Information and Control Engineering, SJZU and she completed her Bachelor's degree in Intelligent Systems and Automation at SJZU in July 2018. Her research interests include modelling and simulation, intelligent traffic systems and optimisation.