Investigating impact of the heterogeneity of trajectory data distribution on origin-destination estimation: a spatial statistics approach
Investigating impact of the heterogeneity of trajectory data distribution on origin-destination estimation: a spatial statistics approach
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研究轨迹数据分布的异质性对起点-目的地估计的影响：空间统计方法
DOI：
10.1049/iet-its.2019.0476
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发表时间：
2020
影响因子：
2.7
通讯作者：
Chen Qian
中科院分区：
文献类型：
--
作者：
Rao Wenming;Xia Jingxin;Wang Chen;Lu Zhenbo;Chen Qian
已经进行了许多研究来根据车辆轨迹数据来估计出发地-目的地（OD）需求。然而，估计精度很大程度上依赖于轨迹的时空分布，其对 OD 估计的影响仍未被揭示和低估。本研究提出了一种新方法来研究轨迹数据分布的异质性对城市道路网络 OD 估计的影响。综合场景是根据从中国昆山的真实交通网络收集的自动车牌识别数据设计的。场景设置选择测试区域、采样率、时间段、采样方式四个因素。接下来，采用基于粒子滤波器的方法使用采样的轨迹数据重建车辆轨迹，然后提取路径流和OD需求。最后，引入空间统计方法来揭示旅行生成/吸引力变化的空间自相关性，并识别出 OD 值受到显着影响的高-高聚类。测试结果表明，该方法可以有效研究轨迹分布对OD估计的异质性影响。进一步的研究表明，空间统计的结果可以应用于提高 OD 估计的准确性。
Many studies have been conducted to estimate origin‐destination (OD) demand based on vehicle trajectory data. However, the estimation accuracy heavily relies on the temporal‐spatial distribution of trajectories, and its effect on OD estimation remains unrevealed and under‐estimated. This study proposes a novel method for investigating the impact of the heterogeneity of trajectory data distribution on OD estimation at urban road networks. Synthetic scenarios are designed based on automatic license plate recognition data collected from a real‐world traffic network in Kunshan, China. Four factors: test area, sampling rate, time period, and the sampling method are selected for scenario settings. Next, a particle filter‐based method is implemented to reconstruct vehicle trajectories using the sampled trajectory data, and then the path flows and OD demands are extracted. Finally, a spatial statistics approach is introduced to reveal the spatial autocorrelation of trip generation/attraction variations, and the high‐high clusters whose OD values are significantly affected are identified. Test results show that the heterogeneity effects of trajectory distribution on OD estimation can be effectively studied by the proposed method. Further investigation shows that the findings of spatial statistics can be applied for improving OD estimation accuracy.