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首页> 外文期刊>Procedia - Social and Behavioral Sciences >Unscented Kalman filter for urban network travel time estimation
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Unscented Kalman filter for urban network travel time estimation

机译:Unscented卡尔曼滤波器用于城市网络旅行时间估计

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To estimate urban network travel time, the classical analytical procedure uses cumulative counts at upstream and downstream locations of links. This procedure is vulnerable in urban networks mainly due to significant flow to and from mid-link sinks and sources. Moreover, most urban network links are only equipped with detectors at their end. Therefore without information on the percentage of turning movement at crossroads, the classical analytical procedure is not applicable. The algorithm proposed and validated in this research estimates urban links travel times based on an unscented Kalman filter (UKF). This algorithm integrates stochastically the vehicle count data from underground loop detectors at the end of every link and the travel times from probe vehicles. The proposed methodology can be used for estimating travel time in real-time. Moreover, with this methodology the number of upstream vehicles as well as the number of mid-link sink/source vehicles is estimated for each link.
机译:为了估算城市网络的旅行时间,经典分析程序使用链路上游和下游位置的累积计数。该过程在城市网络中很容易受到攻击,这主要是由于大量流入和流出中间链路汇和源。而且,大多数城市网络链路的末端仅装有检测器。因此,如果没有有关十字路口转弯运动百分比的信息,则经典分析程序将不适用。本研究中提出并验证的算法基于无味卡尔曼滤波器(UKF)估算城市路段旅行时间。该算法随机地集成了每个链路末端的地下环路检测器的车辆计数数据和探测车辆的行驶时间。所提出的方法可以用于实时估计旅行时间。而且,利用这种方法,估计每个链路的上游车辆的数量以及中间链路宿/源车辆的数量。

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