Urban traffic control optimization algorithm based on artificial intelligence

Chong Liu

doi:10.1117/12.2634429

12 May 2022 Urban traffic control optimization algorithm based on artificial intelligence

Chong Liu

Proceedings Volume 12173, International Conference on Optics and Machine Vision (ICOMV 2022); 121731B (2022) https://doi.org/10.1117/12.2634429
Event: International Conference on Optics and Machine Vision (ICOMV 2022), 2022, Guangzhou, China

Abstract

With the rapid development of urban traffic, the problem of urban traffic becomes very serious. The traditional signal lamp control method can not adaptively control the traffic signal at the intersection. The rise of reinforcement learning technologies has made traffic control and artificial intelligence closely related. This paper presents a traffic optimization algorithm and model based on SUMO simulation platform. In this model, SARSA algorithm in reinforcement learning is used to establish multi-intersection simulation model. The multi-intersection simulation model is four consecutive intersections in Guangming Road, and the experimental parameters are actually investigated. By comparing the simulation data of multiple intersections, it is found that SARSA algorithm is superior to traditional fixed timing and full induction control.

Citation Download Citation

Chong Liu "Urban traffic control optimization algorithm based on artificial intelligence", Proc. SPIE 12173, International Conference on Optics and Machine Vision (ICOMV 2022), 121731B (12 May 2022); https://doi.org/10.1117/12.2634429

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