Analysis of Spatiotemporal Dependencies in Two-Dimensional Traffic Flow in Large-Scale Urban Area with Probe Vehicle Data
Analysis of Spatiotemporal Dependencies in Two-Dimensional Traffic Flow in Large-Scale Urban Area with Probe Vehicle Data
复制标题
利用探测车数据分析大型城区二维交通流时空依赖性
DOI：
10.11175/easts.12.1676
复制
发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Y.
中科院分区：
文献类型：
--
作者：
Lykov;S.;Seo;T.;and Asakura;Y.
由于网络的复杂性、关于车辆运动的可用信息的有限性以及影响交通状况的众多不同因素，理解和描述大规模网络中的交通动态是一个困难和具有挑战性的过程。为了解决这些问题，目前的研究将大规模的城市区域用连续介质代替，将交通流视为其上的二维流。利用大尺度探测车实测数据，研究了该二维流场的时空特征。具体来说，使用了从东京地区行驶一个月的车辆中取样的探测车辆数据。经过数据预处理和转换，分析了整个区域以及小区域的时空依赖关系。结果显示，根据不同的空间位置、时间间隔和区域特征（如是否存在高速公路或主干道程度高），该区域呈现出不同的格局。这些结果表明，该方法适用于利用探测车辆数据分析和描述二维交通流中的依赖关系。
Understanding and description of traffic dynamics in large-scale networks is difficult and challenging procedure due to complexity of the network, limited amount of available information regarding vehicle movements and great number of different factors which affect traffic conditions. To deal with these issues, in current study large-scale urban areas is substituted by a continuous medium, and traffic flows are treated as two-dimensional flow on it. Spatiotemporal characteristics of this two-dimensional flow were investigated with the help of actual large-scale probe vehicle data. Specifically, probe vehicle data, sampled from the vehicles travelled in Tokyo area for one month period were used. After data preprocessing and transformation, spatiotemporal dependencies in the whole area, as well as in smaller regions were examined. The results showed distinct patterns according to different spatial locations, temporal intervals and local features, such as existence of highways or high degree of arterials roads. These results suggested the applicability of proposed approach in order to analyze and describe dependencies in two-dimensional traffic flow by means of probe vehicle data.