交通燈外文翻譯2-交通線路-在線瀏覽
2025-03-24 00:17本頁面
【正文】 re are several models for traffic simulation. In our research we focus on microscopicmodels that model the behavior of individual vehicles, and thereby can simulate dynamics of groups of vehicles. Research has shown that such models yield realistic behavior[Nagel and Schreckenberg, 1992, Wahle and Schreckenberg, 2021]. Cars in urban traffic can experience long travel times due to inefficient traffic light control. Optimal control of traffic lights using sophisticated sensors and intelligent optimizationalgorithms might therefore bevery beneficial. Optimization of traffic light switching increasesroad capacity and traffic flow, and can prevent tra?c congestions. Traffic light control is aplex optimization problem and several intelligent algorithms, such as fuzzy logic, evolutionary algorithms, and reinforcement learning (RL) have already been used in attemptsto solve it. In this paper we describe a modelbased, multiagent reinforcement learningalgorithm for controlling traffic lights. In our approach, reinforcement learning [Sutton and Barto, 1998, Kaelbling et al., 1996]with roaduserbased value functions [Wiering, 2021] is used to determine optimal decisionsfor each
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