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Performance Evaluation of Travel-Time Estimation Methods for Real-Time Traffic Applications

机译:实时交通应用行程时间估计方法的性能评估

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摘要

Travel time for an itinerary constitutes one of the most relevant roadway traffic metrics. Numerous studies have been conducted to estimate travel times on the basis of data from loop detectors. This article focuses on evaluating the performance of a set of estimation methods-algorithms that estimate route travel times using specific speed data from dual loop detectors for real-time applications, such as displaying travel times on changeable message signs. The travel-time estimates are evaluated against probe vehicle data obtained from FasTrak in the San Francisco Bay Area to determine the accuracy of the estimates. The study reveals that (a) the dispersion of travel time is often larger in off-peak periods than in peak periods for heavily congested freeways; (b) assessed against the same set of speed data, the evaluated algorithms have similar performance; (c) the accuracy of travel-time estimates on the basis of loop-detector data is better in off-peak periods than in peak periods; (d) lane-by-lane speeds from loop detectors may be used to improve travel time estimation; and (e) travel time estimation quality is more sensitive to actual sensor locations if sensors are sparse.
机译:行程的旅行时间是最相关的道路交通量度之一。已经进行了许多研究以基于回路检测器的数据来估计行程时间。本文重点介绍评估一组估计方法的性能,这些算法使用来自双回路检测器的特定速度数据估计路线行驶时间以进行实时应用,例如在可变消息标志上显示行驶时间。根据从旧金山湾区FasTrak获得的探测车辆数据评估行驶时间估计,以确定估计的准确性。研究表明:(a)高峰期高速公路拥堵的高峰时间通常比非高峰时间大; (b)根据同一组速度数据进行评估,所评估的算法具有相似的性能; (c)在非高峰时期,基于环路探测器数据的旅行时间估计的准确性要高于高峰时段; (d)来自环路探测器的逐车道速度可用于改善行驶时间估计; (e)如果传感器稀疏,则行程时间估计质量对实际传感器位置更加敏感。

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