Real-timefastest path algorithm using bidirectional point-to-point search on a Fuzzy Time-Dependent transportation network

M. Laarabi, A. Boulmakoul, A. Mabrouk, R. Sacile, E. Garbolino
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引用次数: 9

Abstract

Nowadays management of information systems within the transport industry for effective and efficient decision making requires the use of latest technological development such real-time monitoring and traffic simulation. This will lead to the development of methods and algorithms, for instance, of fleet management, routing within a specified time windows and risk assessment. In this paper we will focus on proposing a method for finding itineraries that has the fastest travel-time on a time-dependent transportation network. It is modelled as a weighted graph, whose weight are time duration that depends on the time at which the road segment is traversed. This problem can be solved in polynomial time with a Single-Source algorithm, by the definition of some restrictions on the edge weights. However, its application on a graph with several millions nodes and edges is highly memory and time consuming. Alternatively, a bidirectional Point-to-Point path search, using A-star, offers far better performance. The novelty of the proposed approach is based on the modelling of an appropriate degree of dynamics of a real-world network by considering the fuzzy nature of the travel-time using Zadeh's fuzzy concept. In addition, we speed-up search by integrating a pre-computation phase, which consists in network partitioning using network Voronoi diagrams with implicit calculation of the lower-bound travel-time label for each node-to-border, border-to-border and border-to-node. Those labels should never overestimate the travel-time at any moment, to ensure the reliability of the suggested heuristic cost function.
基于双向点对点搜索的模糊时变交通网络实时最快路径算法
如今,为了有效和高效的决策,运输行业内的信息系统管理需要使用最新的技术发展,如实时监控和交通模拟。这将导致方法和算法的发展,例如,车队管理,指定时间窗口内的路线和风险评估。在本文中,我们将重点提出一种在时间依赖的交通网络中寻找旅行时间最快的路线的方法。它被建模为一个加权图,其权重是时间持续时间,这取决于路段通过的时间。通过对边缘权值的限制,可以在多项式时间内用单源算法求解该问题。然而,它在具有数百万个节点和边的图上的应用是高度内存和耗时的。另外,使用a -star的双向点对点路径搜索提供了更好的性能。该方法的新颖之处在于利用Zadeh的模糊概念,通过考虑旅行时间的模糊性,对现实世界网络进行了适当程度的动态建模。此外,我们通过集成预计算阶段来加快搜索速度,该阶段包括使用网络Voronoi图进行网络划分,并隐式计算每个节点到边界、边界到边界和边界到节点的下界旅行时间标签。这些标签在任何时刻都不应该高估旅行时间,以确保建议的启发式成本函数的可靠性。
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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