An Unscented Kalman Filter-Based Method for Reconstructing Vehicle Trajectories at Signalized Intersections
An Unscented Kalman Filter-Based Method for Reconstructing Vehicle Trajectories at Signalized Intersections
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DOI：
10.1155/2021/6181242
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发表时间：
2021-12
影响因子：
2.3
通讯作者：
Jiantao Mu;Yin Han;Cheng Zhang;Jiao Yao;Jing Zhao
中科院分区：
文献类型：
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作者：
Jiantao Mu;Yin Han;Cheng Zhang;Jiao Yao;Jing Zhao
检测车辆的车载数据对于城市道路交通运行的管理和交通状况的估计起着至关重要的作用。不幸的是，由于技术和隐私问题的限制，检测到的车辆数据的采样频率较低，覆盖范围也有限。无法获得连续的车辆轨迹。为了克服上述问题，本文提出了一种基于无迹卡尔曼滤波器（UKF）的方法，利用车辆的稀疏探测数据重建信号交叉口的轨迹。我们首先将交叉路口划分为多个路段，并使用二次规划问题来估计每个路段的行驶时间。单独计算每个初始可能轨迹的权重，并使用无迹卡尔曼滤波器（UKF）更新轨迹；那么，两次更新之间的轨迹也相应地得到。最后，将该方法应用到NGSIM数据提供的实际场景中，并与真实轨迹进行比较。采用平均绝对误差（MAE）来评估所提出的轨迹重建的准确性。提供了灵敏度分析，以提供该方法下获得高精度重建车辆轨迹的采样频率要求。结果证明了该技术对信号交叉口的适用性。因此，该方法使我们能够获得更丰富、更准确的轨迹数据信息，为未来城市道路交通管理以及学者利用轨迹数据进行各种研究提供强有力的先验基础。
On-board data of detected vehicles play a critical role in the management of urban road traffic operation and the estimation of traffic status. Unfortunately, due to limitations of technology and privacy issues, the sampling frequency of the detected vehicle data is low and the coverage is also limited. Continuous vehicle trajectories cannot be obtained. To overcome the above problems, this paper proposes an unscented Kalman filter (UKF)-based method to reconstruct the trajectories at signalized intersections using sparse probe data of vehicles. We first divide the intersection into multiple road sections and use a quadratic programming problem to estimate the travel time of each section. The weight of each initial possible trajectory is calculated separately, and the trajectory is updated using the unscented Kalman filter (UKF); then, the trajectory between two updates is also obtained accordingly. Finally, the method is applied to the actual scenario provided by the NGSIM data and compared with the real trajectory. The mean absolute error (MAE) is adopted to evaluate the accuracy of the proposed trajectory reconstruction. Sensitivity analysis is provided in order to provide the requirement of sampling frequency to obtain highly accurate reconstructed vehicle trajectories under this method. The results demonstrate the applicability of the technique to the signalized intersection. Therefore, the method enables us to obtain richer and more accurate trajectory data information, providing a strong prior basis for future urban road traffic management and scholars using trajectory data for various studies.