A Method for Exploring and Analyzing Spatiotemporal Patterns of Traffic Congestion in Expressway Networks Based on Origin-Destination Data
A Method for Exploring and Analyzing Spatiotemporal Patterns of Traffic Congestion in Expressway Networks Based on Origin-Destination Data
复制标题
DOI：
10.3390/ijgi10050288
复制
发表时间：
2021-05
期刊：
影响因子：
--
通讯作者：
Hong Gao;Zhenjun Yan;Xu Hu;Zhaoyuan Yu;Wen Luo;Linwang Yuan;Ji-yi Zhang
中科院分区：
文献类型：
--
作者：
Hong Gao;Zhenjun Yan;Xu Hu;Zhaoyuan Yu;Wen Luo;Linwang Yuan;Ji-yi Zhang
高速公路网的交通拥堵对区域发展有很大的负面影响。了解高速公路网交通拥挤的时空格局，对于改善区域生产中的产品交换，促进区域经济发展具有重要意义。然而，现有的研究较少关注这些时空模式的交通拥堵。考虑到起点-目的地（OD）数据可用于记录的车辆在高速公路上的空间运动，本研究提出了一种方法，该方法可以探索在区域高速公路网络的路段，驾驶行为的主流，和交通法规的水平上的交通拥堵。提出了分析高速公路网交通拥堵空间差异和时间变化的方法。实验结果表明，该方法能够检测出发生交通拥堵的路段，进而揭示出多个拥堵位置的时间模式和频繁拥堵路段的空间模式。这些交通拥堵的时空分布模式与实际情况雅阁。该研究为基于低成本数据的高速公路网交通拥堵研究提供了新的思路，有助于优化高速公路网规划，促进区域均衡发展。
Traffic congestion in expressway networks has a strong negative influence on regional development. Understanding the spatiotemporal patterns of traffic congestion in expressway networks is critical for improving the exchange of products in regional production and promoting regional economic development. Nevertheless, existing studies pay less attention to these spatiotemporal patterns of traffic congestion. Considering that Origin–Destination (OD) data are available for the recorded spatial movements of vehicles in expressways, this study proposes a method with which to explore traffic congestion at the level of road segments in the regional expressway network, the mainstream of driving behaviors, and traffic regulations. Methods for analyzing spatial disparity and temporal changes in traffic congestion in expressway networks are also put forward in this paper. The empirical results show that the proposed methods could detect road segments where traffic congestion happens, and then uncover temporal patterns of several congested locations and spatial patterns of road segments with frequent congestion. These spatiotemporal patterns of traffic congestion could be in accord with the actual situation. This study provides a new approach to investigating traffic congestion in expressway networks based on low-cost data, which might be helpful for optimizing expressway network planning and promoting balanced regional development.