道路旅行时间预测。微观抽样方法

Gideon Mbiydzenyuy, M. Dahl, J. Holmgren
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引用次数: 0

摘要

为公路货物运输生成准确的旅行时间预测的能力非常重要,例如,在估计重型货车(hgv)的到达时间以规划终端活动时。提出了一种用于道路出行时间预测的微观抽样方法。该方法利用历史gps数据,以确定车辆沿着特定路线从起点到目的地的运动。该方法生成一个行程时间分布,该分布可用于获得期望行程时间和偏差概率。该方法已在一个实验中得到说明和评价,其中预测了两个终端之间运输的有效旅行时间。该实验使用了两辆hgv在两个月内记录的GPS数据。该方法的一个重要特点是,它不需要路网信息,如速度限制和车道数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Road travel time prediction - A micro-level sampling approach
The ability to generate accurate travel time predictions for road freight transport is important when, for example, estimating the arrival times for heavy goods vehicles (HGVs) in order to plan terminal activities. We present a micro-level sampling method for road travel time prediction. The method makes use of historical GPS-data in order to determine the movement of a vehicle from an origin to a destination along a specific route. The method generates a travel time distribution, which can be used to obtain the expected travel time and probabilities for deviations. The method has been illustrated and evaluated in an experiment where the effective travel time was predicted for transport between two terminals. The experiment made use of GPS data that was recorded for two HGVs during a period of two months. An important feature of the method is that it does not need road network information, such as speed limits and number of lanes.
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