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Real-time estimation of lane-based queue lengths at isolated signalized junctions

机译:实时估计隔离信号交叉口处基于车道的队列长度

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In this study, we develop a real-time estimation approach for lane-based queue lengths. Our aim is to determine the numbers of queued vehicles in each lane, based on detector information at isolated signalized junctions. The challenges involved in this task are to identify whether there is a residual queue at the start time of each cycle and to determine the proportions of lane-to-lane traffic volumes in each lane. Discriminant models are developed based on time occupancy rates and impulse memories, as calculated by the detector and signal information from a set of upstream and downstream detectors. To determine the proportions of total traffic volume in each lane, the downstream arrivals for each cycle are estimated by using the Kalman filter, which is based on upstream arrivals and downstream discharges collected during the previous cycle. Both the computer simulations and the case study of real-world traffic show that the proposed method is robust and accurate for the estimation of lane-based queue lengths in real time under a wide range of traffic conditions. Calibrated discriminant models play a significant role in determining whether there are residual queued vehicles in each lane at the start time of each cycle. In addition, downstream arrivals estimated by the Kalman filter enhance the accuracy of the estimates by minimizing any error terms caused by lane-changing behavior. (C) 2015 Elsevier Ltd. All rights reserved.
机译:在这项研究中,我们针对基于车道的队列长度开发了一种实时估计方法。我们的目标是根据孤立的信号交叉口处的检测器信息,确定每个车道中排队的车辆数量。这项任务涉及的挑战是确定每个循环的开始时间是否有剩余队列,并确定每个车道中车道到车流量的比例。基于时间占用率和脉冲存储器(由检测器计算得出)和来自一组上游和下游检测器的信号信息来开发判别模型。为了确定每个车道中总交通量的比例,使用卡尔曼滤波器估算每个周期的下游到达,该滤波器基于前一周期收集的上游到达和下游排放量。计算机仿真和实际交通案例研究均表明,该方法对于在各种交通条件下实时估计基于车道的队列长度是可靠且准确的。校准的判别模型在确定每个周期的开始时间每个车道上是否有剩余排队的车辆方面起着重要作用。此外,通过最小化由车道变换行为引起的任何误差项,由卡尔曼滤波器估计的下游到达提高了估计的准确性。 (C)2015 Elsevier Ltd.保留所有权利。

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