Pareto optimality control of traffic signal and vehicle speed considering mixed traffic stream at isolated intersection

Abstract

Most existing research on the cooperative control of traffic signals and vehicle speed encounters challenges in achieving a balance between traffic efficiency and vehicle fuel consumption at intersections. The pareto optimality control of traffic signal and vehicle speed is proposed to solve this balance problem considering mixed traffic stream at isolated intersection. This control method encompasses three main components: a multi-criteria signal control method, a vehicle speed trajectories multi-objective optimization model based on Pareto optimality, and a macro control strategy. Multi-criteria signal control method is designed based on multiple criteria to divide vehicles into groups optimally. The proposed vehicle speed trajectories multi-objective optimization model is solved by NSGA-II (Non-dominated Sorting Genetic Algorithm II) method to obtain pareto optimality. In order to illustrate the efficiency, this control method is tested in SUMO software compared with ASC (Adaptive Signal Control) method and bilevel optimization method. Average delay and average fuel consumption of this control method are reduced by 44.49% and 25.31% compared with ASC method. On the other hand, this control method also shows obvious balance effect compared with bilevel optimization method under different penetration level and demand level. Furthermore, average delay and average fuel consumption of this control method are reduced simultaneously under 250veh· l^–1·h^–1 level and 40% penetration level, 100% penetration level and 250veh· l^–1·h^-1 level. Experimental results illustrate the effectiveness of the proposed Pareto optimality-based control of traffic signals and vehicle speed.