Improved genetic particle swarm algorithm based single intersection signal timing optimization

Jie Yan; Xiao Long Han

doi:10.1117/12.2684031

14 June 2023 Improved genetic particle swarm algorithm based single intersection signal timing optimization

Jie Yan, Xiao Long Han

Proceedings Volume 12708, 3rd International Conference on Internet of Things and Smart City (IoTSC 2023）; 127080N (2023) https://doi.org/10.1117/12.2684031
Event: 3rd International Conference on Internet of Things and Smart City (IoTSC 2023）, 2023, Chongqing, China

Abstract

Traditional signal control at intersections is mainly based on the maximum capacity as an indicator, which leads to long signal cycles at many single intersections, but instead aggravates the average delay, stopping frequency rate, and tailpipe emissions of vehicles. From the perspective of improving intersection efficiency and environmental protection, the paper establishes a multi-objective function model with the average delay, stopping frequency, capacity and exhaust emission of vehicles as the optimization indicators, and proposes an improved genetic particle swarm algorithm (GAPSO) solution for intersection timing optimization. The solved results are compared with the original timing scheme, the GA and PSO solved timing schemes, in conjunction with real-life case studies. The results show a significant optimization in terms of average vehicle delays, exhaust emissions and stopping frequency, thus demonstrating the effectiveness of the improved GAPSO for timing optimization at single intersections.

Citation Download Citation

Jie Yan and Xiao Long Han "Improved genetic particle swarm algorithm based single intersection signal timing optimization", Proc. SPIE 12708, 3rd International Conference on Internet of Things and Smart City (IoTSC 2023）, 127080N (14 June 2023); https://doi.org/10.1117/12.2684031

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