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AN OPTIMIZATION-BASED APPROACH TO SPECIAL-EVENTS TRAFFIC SIGNAL TIMING CONTROL

机译:一种基于优化的特殊事件交通信号时序控制方法

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摘要

A sudden traffic surge immediately after special events (e.g., conventions, sporting events, concerts) can create substantial traffic congestion in the area where the events are held. One desirable solution is to develop a short-term traffic signal timing adjustment for the high-volume traffic movements associated with special events so that progression is as efficient as possible. In this paper, we present a case study of special-events traffic signal timing control for a small-scale network. A neural network (NN) is used as a signal controller with its weights determined via the Simultaneous Perturbation Stochastic Approximation (SPSA) method. The SPSA optimization is conducted by minimizing a chosen tolerance index as our performance criterion. The timing plans are developed, and the performance evaluations using the existing signal timing and the one generated by the proposed algorithm are also investigated. Our study shows the advantage and potential of using the NN-based SPSA optimization approach to special-events traffic signal timing control. Although this paper presents a case study, the results can be easily modified and applied to large-scale events traffic control.
机译:特殊事件(例如,大会,体育赛事,音乐会)之后,流量突然激增,会在举办活动的地区造成严重的交通拥堵。一种理想的解决方案是为与特殊事件相关的大流量交通发展短期交通信号定时调整,以使行进尽可能有效。本文以小型网络特殊事件交通信号时序控制为例。神经网络(NN)用作信号控制器,其权重通过同时摄动随机近似(SPSA)方法确定。通过将选择的公差指数作为我们的性能标准来进行SPSA优化。制定了时序计划,并研究了使用现有信号时序的性能评估以及所提出算法产生的性能评估。我们的研究显示了使用基于NN的SPSA优化方法进行特殊事件交通信号定时控制的优势和潜力。尽管本文提供了一个案例研究,但可以轻松修改结果并将其应用于大规模事件交通控制。

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