Network-wide Traffic Signal Optimization under Connected Vehicles Environment

Abstract

Connected vehicle technology holds great promises for next generation of traffic signal control. This paper proposes a novel mixed-integer linear programming (MILP) model to optimally coordinate traffic signals at the network level under connected vehicles environment. We leveraged the combinatorial Benders decomposition method to solve this large-scaled MILP model more efficiently than the SCIP solver. Numerical experiments show that our approach can significantly improve network traffic operations compared to a benchmark signal plan in terms of vehicle delay, travel time and throughput.