An intelligent highway tollgate queue selector for improving server utilization and vehicle waiting time

E. Magsino, I. W. Ho
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引用次数: 14

Abstract

On a highway setup, a vehicle will most probably use a tollgate server that has the shortest queue thinking that it is the fastest exit. In this paper, an intelligent highway tollgate queue selector using fuzzy logic is proposed and simulated in Matlab SimEvents. Its aim is to automatically select the most appropriate tollgate server for a vehicle to ensure the shortest waiting time while trying to balance the server's utilization. Two policies are considered in this study, namely: (1) Shortest Queue (SQ) and (2) Fuzzy Logic-Controlled Queue (FLCQ). Results indicate that the FLCQ policies reduce the average waiting time and queue length by approximately 50% of those obtained from the SQ policy while guaranteeing an equal utilization among available servers. These findings are valid for light and heavy, homogeneous and nonhomogeneous vehicle arrivals. To further improve the decision making of the fuzzy logic controller, traffic flow information collected by remote road-side units can be exploited to allow the control of various system parameters (e.g., service time) in advance.
一种提高服务器利用率和车辆等待时间的高速公路收费站智能队列选择器
在高速公路设置中,车辆很可能使用具有最短队列的收费站服务器,认为它是最快的出口。本文提出了一种基于模糊逻辑的高速公路收费站智能队列选择器,并在Matlab SimEvents中进行了仿真。它的目标是自动为车辆选择最合适的收费站服务器,以确保最短的等待时间,同时试图平衡服务器的利用率。本研究考虑两种策略:(1)最短队列(SQ)和(2)模糊逻辑控制队列(FLCQ)。结果表明,FLCQ策略使平均等待时间和队列长度比SQ策略减少了大约50%,同时保证了可用服务器之间的平均利用率。这些发现适用于轻型和重型,均匀和非均匀车辆到达。为了进一步提高模糊控制器的决策能力,可以利用远程路侧单元采集到的交通流信息,提前控制各种系统参数(如服务时间)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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