Business School, Sichuan University, Chengdu, 610065, China.
NHH Norwegian School of Economics, Bergen, Norway.
Sci Rep. 2020 Jul 16;10(1):11821. doi: 10.1038/s41598-020-68810-9.
Link travel speeds in road networks are essential data for a variety of research problems in logistics, transportation, and traffic management. Real-world link travel speeds are stochastic, and highly dependent on speeds in previous time periods and neighboring road links. To understand how link travel speeds vary over space and time, we uncover their distributions, their space- and/or time-dependent correlations, as well as partial correlations, based on link travel speed datasets from an urban road network and a freeway network. We find that more than 90% (57%) of travel speeds are normally distributed in the urban road (freeway) network, and that correlations generally decrease with increased distance in time and space. We also investigate if and how different types of road links affect marginal distributions and correlations. The results show that different road link types produce quite similar marginal distributions and correlations. Finally, we study marginal distributions and correlations in a freeway network. Except that the marginal distribution and time correlation are different from the urban road network, others are similar.
道路网络中的链路行驶速度是物流、交通和交通管理中各种研究问题的重要数据。实际链路行驶速度是随机的，并且高度依赖于前一时间周期和相邻道路链路的速度。为了了解链路行驶速度如何随空间和时间变化，我们基于来自城市道路网络和高速公路网络的链路行驶速度数据集，揭示了它们的分布、时空相关关系以及偏相关关系。我们发现，超过 90%（57%）的行驶速度在城市道路（高速公路）网络中呈正态分布，并且相关性通常随着时间和空间距离的增加而减小。我们还研究了不同类型的道路链路是否以及如何影响边际分布和相关性。结果表明，不同类型的道路链路产生非常相似的边际分布和相关性。最后，我们研究了高速公路网络中的边际分布和相关性。除了边际分布和时间相关性与城市道路网络不同外，其他方面都相似。
