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A Novel Metaheuristic for Adaptive Signal Timing Optimization Considering Emergency Vehicle Preemption and Tram Priority

机译:考虑紧急车辆抢占和电车优先级的自适应信号时序优化的新型成分型

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摘要

In this article, a novel hybrid metaheuristic based on passing vehicle search (PVS) cultural algorithm (CA) is proposed. This contribution has a twofold aim: First is to present the new hybrid PVS-CA. Second is to prove the effectiveness of the proposed algorithm for adaptive signal timing optimization. For this, a system that can adapt efficiently to the real-time traffic situation based on priority signal control is developed. Hence, Transit Signal Priority (TSP) techniques have been used to adjust signal phasing in order to serve emergency vehicles (EVs) and manage the tram priority in a coordinated tram intersection. The system used in this study provides cyclic signal operation based on a real-time control approach, including an optimization process and a database to manage the sensor data from detectors for real-time predictions of EV and tram arrival time. Then, a simulation model is developed using Arena Simulation Software to evaluate best timing plans at the intersection.
机译:在本文中,提出了一种基于通过车辆搜索(PVS)文化算法(CA)的新型混合成群化。 这一贡献具有双重目标:首先是介绍新的混合PVS-CA。 其次是为了证明所提出的自适应信号定时优化算法的有效性。 为此,开发了一种可以高效地适应基于优先级信号控制的实时业务情况的系统。 因此,已经使用过渡信号优先级(TSP)技术来调整信号相位,以便为应急车辆(EVS)提供服务,并在协调的电车交叉路口管理电流优先级。 本研究中使用的系统基于实时控制方法提供循环信号操作,包括优化过程和数据库,用于管理来自检测器的传感器数据,以便进行EV和电车到达时间的实时预测。 然后,使用竞技场仿真软件开发了模拟模型,以评估交叉路口的最佳时间计划。

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