Optimization of urban traffic network signal scheduling based on vehicle delay and arterial green wave

Abstract

Urban traffic congestion has become increasingly severe due to the rapid growth of vehicle demand, making efficient signal control a critical challenge. Existing traffic signal optimization methods typically focus on either isolated intersections or arterial coordination, lacking a unified framework that balances network-wide efficiency and structured traffic flow. To address this issue, this paper proposes a bi-objective optimization algorithm based on the total delay of vehicles in the road network and the arterial green-wave index to coordinate and optimize all intersections in the road network. Experiments are conducted on a real-world urban road network in Guangzhou Province, China. Results show that the proposed method achieves comparable delay performance to state-of-the-art approaches while significantly improving arterial coordination. Finally, simulation results based on SUMO demonstrate that the proposed method outperforms baseline approaches in terms of average delay, queue length, and number of stops, validating its effectiveness in realistic traffic scenarios.