城市主干道行车时间预测

G. Jiang, Ruoqi Zhang
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引用次数: 18

摘要

基于城市路网各路段交通量的相对关系,运用统计分析技术研究了检测器的最优空间分布。在此基础上,提出了在城市道路上安装检测器的准则,并利用混合结构算法的神经网络技术,结合长春市道路网数据,对未安装检测器的路段行驶时间进行了预测和检验。该研究提供了一种解决探测器在城市主干道上的最优空间分布和利用检测到的路段交通信息预测未检测到的路段出行时间的方法。
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Travel time prediction for urban arterial road
Based on the relative relationship of the traffic volume of segments on the urban road network, we studied the optimal space distribution of detectors with statistic analysis techniques. Then we proposed the criteria of installing detectors on the urban roads, on the other hand, we predicted and checked out the non-detectors segment travel time using neural network technique of mix-structure algorithm with the data of the road network of Changchun City, China. The research gives a way to solve the optimal space distribution of detectors on urban arterial road and non-detected segment travel time prediction with detected segment traffic information.
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