Online Route Replanning for Scalable System-Optimal Route Planning

R. Fitzgerald, F. Kashani
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引用次数: 1

Abstract

Route planning in transportation networks is typically performed as a single optimization at trip departure. In this paper, we consider the impact of within-trip replanning on the performance of the overall network in a fully-algorithmic route selection scenario. An experimental study of three real road networks using synthetic demand demonstrates in over 200 trials the effects of replanning with respect to the replanning rate and the adoption rate of replanning. Overall network travel times are reduced by up to 48.49% from a baseline where all drivers are assigned a single route, demonstrating the profound effect of dynamic within-trip replanning. These observations are part of our work exploring a system-optimal route planning strategy that is robust to network size and conditions.
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基于可扩展系统最优路由规划的在线路由重规划
交通网络中的路线规划通常在出行出发时作为单个优化来执行。在本文中,我们考虑了在全算法的路线选择场景下,行程内重新规划对整个网络性能的影响。一项利用综合需求对三个真实路网进行的实验研究,在200多次试验中证明了重新规划对重新规划率和重新规划采用率的影响。与所有司机被分配一条路线的基线相比,整个网络的行驶时间最多减少了48.49%,这表明动态行程重新规划的深远影响。这些观察结果是我们探索对网络规模和条件具有鲁棒性的系统最优路由规划策略的工作的一部分。
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