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Path Planning with Information on Travel Time Reliability

机译:具有行进时间可靠性信息的路径规划

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The shortest path under a given on-time arrival probability is valuable to travelers wishing to save time and avoid traffic uncertainty. Conventional reliable shortest path methods often assume that travel time follows normal distribution, but substantial evidence shows that travel time in peak periods follows lognormal distribution. This paper proposes a reliable shortest path method under the assumption that travel time in peak periods follows lognormal distribution. Due to the character of bi-objective optimization, first-order stochastic dominance was conducted to compare the priority of a set of paths. Then, an improved RSPP-LC algorithm that simplifies the path-correcting procedure was constructed and applied to a small network in Shenzhen. The computational result indicates that RSPP-LC algorithm performs well in a small-scale network.
机译:在给定的准时到达概率下,最短路径对于希望节省时间并避免交通不确定性的旅行者来说很有价值。常规可靠的最短路径方法通常假定行进时间遵循正态分布,但是大量证据表明,高峰时段的行进时间遵循对数正态分布。在高峰时段的旅行时间服从对数正态分布的假设下,本文提出了一种可靠的最短路径方法。由于具有双目标优化的特性,因此进行了一阶随机控制来比较一组路径的优先级。然后,构建了一种简化了路径校正过程的改进型RSPP-LC算法,并将其应用于深圳的一个小型网络。计算结果表明,RSPP-LC算法在小型网络中表现良好。

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