Variable time discretization for a time-dependent shortest path algorithm

Ye Tian, Y. Chiu, Yang Gao
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引用次数: 1

Abstract

This paper introduces a variable time discretization strategy for a time-dependent A∗ shortest path algorithm. The strategy is aimed at determining the optimal memory allocation for time-dependent travel times data in order to achieve a desirable compromise between accuracy and memory usage. The proposed strategy is based on the dispersion index of the travel times/costs over the entire analysis period, as a result, producing different intervals for each link. The links with travel times that have a higher variance and a lower mean will need to have a shorter time discretization length due to greater fluctuation in travel times. The proposed strategy is implemented in the time-dependent A∗ algorithm and tested with a numerical experiment on a Tucson, AZ, traffic network. The results show that with the same amount of computer memory usage, the proposed variable time discretization strategy achieves much higher accuracy than that of uniform time discretization.
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时变最短路径算法的变时间离散化
本文介绍了一种时变a *最短路径算法的变时间离散化策略。该策略旨在确定与时间相关的旅行时间数据的最佳内存分配,以便在准确性和内存使用之间实现理想的折衷。提议的策略是基于整个分析期间旅行时间/费用的离散指数,因此,为每个环节产生不同的间隔。由于行程时间的波动较大,具有较大方差和较低均值的行程时间链接需要具有较短的时间离散化长度。提出的策略在时间相关的A *算法中实现,并在亚利桑那州图森市的交通网络上进行了数值实验。结果表明,在计算机内存使用量相同的情况下,所提出的变时间离散化策略比均匀时间离散化策略具有更高的精度。
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