Improving traffic signal control effect of multiagent reinforcement learning with information collaboration

Jing Wei; Cailin Yue; Siqi Chen; Jixiang Wang

doi:10.1117/12.3045681

30 September 2024 Improving traffic signal control effect of multiagent reinforcement learning with information collaboration

Jing Wei, Cailin Yue, Siqi Chen, Jixiang Wang

Author Affiliations +

Proceedings Volume 13286, Third International Conference on Electronics Technology and Artificial Intelligence (ETAI 2024); 132861B (2024) https://doi.org/10.1117/12.3045681
Event: Third International Conference on Electronics Technology and Artificial Intelligence (ETAI 2024), 2024, Guangzhou, China

Abstract

In order to study the parameter selection of the information collaboration, this paper analyzes the model control effect and model complexity under these two kinds of information synergy representations by constructing the traffic state-aware interaction and reward information synergy experiments, and finally selects the optimal model information synergy parameters according to the experimental results, which provides a certain research basis for the subsequent parameter settings.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jing Wei, Cailin Yue, Siqi Chen, and Jixiang Wang "Improving traffic signal control effect of multiagent reinforcement learning with information collaboration", Proc. SPIE 13286, Third International Conference on Electronics Technology and Artificial Intelligence (ETAI 2024), 132861B (30 September 2024); https://doi.org/10.1117/12.3045681

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