Application of probe-vehicle data for real-time traffic-state estimation and short-term travel-time prediction on a freeway
Application of probe-vehicle data for real-time traffic-state estimation and short-term travel-time prediction on a freeway
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DOI：
10.3141/1855-06
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发表时间：
2003-01-01
期刊：
影响因子：
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通讯作者：
Suzuki, H
中科院分区：
文献类型：
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作者：
Nanthawichit, C;Nakatsuji, T;Suzuki, H
探测车的交通信息对于提高交通状况的估计精度具有很大的潜力，特别是在没有安装交通检测器的情况下。提出了一种将探测数据与常规检测器数据一起处理以估计交通状态的方法。将测头数据整合到卡尔曼滤波的观测方程中，其中状态方程由宏观交通流模型表示。估计的状态用来自固定探测器和探测车的信息进行了更新。使用假设数据对该方法在几种交通条件下进行了测试，与没有探测数据的估计结果相比，该方法的估计结果有了很大的改善。最后，将该方法推广应用于出行时间的估计和短期预测。行程时间是通过由所提出的方法估计或预测的速度换算而间接获得的。实验结果表明，行程时间估计或预测的性能与现有的一些方法相当。
Traffic information from probe vehicles has great potential for improving the estimation accuracy of traffic situations, especially where no traffic detector is installed. A method for dealing with probe data along with conventional detector data to estimate traffic states is proposed. The probe data were integrated into the observation equation of the Kalman filter, in which state equations are represented by a macroscopic traffic-flow model. Estimated states were updated with information from both stationary detectors and probe vehicles. The method was tested under several traffic conditions by using hypothetical data, giving considerably improved estimation results compared to those estimated without probe data. Finally, the application of the proposed method was extended to the estimation and short-term prediction of travel time. Travel times were obtained indirectly through the conversion of speeds estimated or predicted by the proposed method. Experimental results show that the performance of travel-time estimation or prediction is comparable to that of some existing methods.