Cooperative and Integrated Vehicle and Intersection Control for Energy Efficiency (CIVIC-E2)

• Published in: IEEE transactions on intelligent transportation systems Vol. 19; no. 7; pp. 2325 - 2337
• Main Authors: Hou, Yunfei, Seliman, Salaheldeen M. S., Wang, Enshu, Gonder, Jeffrey D., Wood, Eric, He, Qing, Sadek, Adel W., Su, Lu, Qiao, Chunming
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.07.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: ADVANCED PROPULSION SYSTEMS; Algorithms; Computer simulation; Connected vehicles; Delays; Driving conditions; Dynamic programming; Energy conservation; Energy consumption; Energy efficiency; fuel economy; Fuels; intelligent transportation systems; Power efficiency; Predictive control; Queues; Schedules; Traffic; Traffic intersections; Traffic management; Traffic signals; Traffic speed; Transportation; Transportation systems; Vehicles; Velocity control
• ISSN: 1524-9050; 1558-0016
• DOI: 10.1109/TITS.2017.2785288

Recent advances in connected vehicle technologies enable vehicles and signal controllers to cooperate and improve the traffic management at intersections. This paper explores the opportunity for cooperative and integrated vehicle and intersection control for energy efficiency (CIVIC-E 2 ) to contribute to a more sustainable transportation system. We propose a two-level approach that jointly optimizes the traffic signal timing and vehicles' approach speed, with the objective being to minimize total energy consumption for all vehicles passing through an isolated intersection. More specifically, at the intersection level, a dynamic programming algorithm is designed to find the optimal signal timing by explicitly considering the arrival time and energy profile of each vehicle. At the vehicle level, a model predictive control strategy is adopted to ensure that vehicles pass through the intersection in a timely fashion. Our simulation study has shown that the proposed CIVIC-E 2 system can significantly improve intersection performance under various traffic conditions. Compared with conventional fixed-time and actuated signal control strategies, the proposed algorithm can reduce energy consumption and queue length by up to 31% and 95%, respectively.