IoT-Enabled Real-Time Traffic Monitoring and Control Management for Intelligent Transportation Systems
Hongyan Dui, Songru Zhang, Meng Liu, Xinghui Dong, Guanghan Bai
Abstract
Advanced Internet of Things (IoT) technology has a profound impact on improving the intelligence level of intelligent transportation systems (ITS) and promoting the sustainable development of urban transportation. However, how to use IoT to process traffic flow and make ITS develop towards automation and global control is still a challenge. Against this backdrop, a prospective traffic controlling model is proposed for ITS based on IoT to enhance the awareness of roads and the responsiveness of transportation system. When traffic congestion events occur, ITS can provide the optimal control strategy of vehicle-to-everything supported vehicles (V2X-supported vehicles) from a macro perspective to control the traffic flow globally and improve traffic efficiency. Specially, the optimal control strategies consider the potential congested road segments caused by congestion propagation. Meanwhile, this paper explores the impact of route choice behavior of V2X-supported vehicles on system performance. The simulation results show the optimal control strategies can alleviate congestion effectively and improve transportation system performance significantly by controlling vehicles.