Research Centre for Integrated Transport Innovation (rCITI), School of Civil and Environmental Engineering, University of New South Wales (UNSW), Sydney, NSW, 2032, Australia.
Department of Civil Engineering, Institute of Transport Studies, Monash University, Melbourne, VIC, 3800, Australia.
Nat Commun. 2020 Apr 7;11(1):1616. doi: 10.1038/s41467-020-15353-2.
The spread of traffic jams in urban networks has long been viewed as a complex spatio-temporal phenomenon that often requires computationally intensive microscopic models for analysis purposes. In this study, we present a framework to describe the dynamics of congestion propagation and dissipation of traffic in cities using a simple contagion process, inspired by those used to model infectious disease spread in a population. We introduce two macroscopic characteristics for network traffic dynamics, namely congestion propagation rate β and congestion dissipation rate μ. We describe the dynamics of congestion spread using these new parameters embedded within a system of ordinary differential equations, similar to the well-known susceptible-infected-recovered (SIR) model. The proposed contagion-based dynamics are verified through an empirical multi-city analysis, and can be used to monitor, predict and control the fraction of congested links in the network over time.
交通拥堵在城市网络中的传播一直被视为一种复杂的时空现象，通常需要计算密集型的微观模型来进行分析。在本研究中，我们提出了一个使用简单的传染病传播过程来描述城市交通拥堵传播和消散动态的框架，该过程受到用于模拟人群中传染病传播的过程的启发。我们引入了两个用于网络交通动力学的宏观特征，即拥堵传播率β和拥堵消散率μ。我们使用这些嵌入在常微分方程组中的新参数来描述拥堵传播的动态，类似于著名的易感-感染-恢复（SIR）模型。基于传染病的动力学通过多城市的经验分析得到了验证，并可用于实时监测、预测和控制网络中拥塞链路的比例。
