Abstract
Traffic in an urban network becomes congested once there is a critical number of vehicles in the network. To improve traffic operations, develop new congestion mitigation strategies, and reduce negative traffic externalities, understanding the basic laws governing the network’s critical number of vehicles and the network’s traffic capacity is necessary. However, until now, a holistic understanding of this critical point and an empirical quantification of its driving factors has been missing. Here we show with billions of vehicle observations from more than 40 cities, how road and bus network topology explains around 90% of the empirically observed critical point variation, making it therefore predictable. Importantly, we find a sublinear relationship between network size and critical accumulation emphasizing decreasing marginal returns of infrastructure investment. As transportation networks are the lifeline of our cities, our findings have profound implications on how to build and operate our cities more efficiently.
Highlights
Traffic in an urban network becomes congested once there is a critical number of vehicles in the network
The recently formulated Macroscopic Fundamental Diagram (MFD) provides new ways to systematically analyze urban traffic at the network level[10,11,12], it is consistent with the physics of traffic, and allows to determine the boundary of traffic states of networks and the traffic capacity of urban networks
The distribution of critical accumulation in our sample is consistent with the traffic physics literature[19] that predicts that critical accumulation does not exceed one third of the jam accumulation
Summary
Traffic in an urban network becomes congested once there is a critical number of vehicles in the network. Traffic is a many-particle system[4], where congestion is defined as the state when increasing the number of vehicles decreases travel production. During free-flow states, increasing the number of vehicles increases travel production. The system’s critical point is located at the boundary between the network’s free-flow and congested states. At this point, the maximum in travel production, the traffic capacity of urban networks, is reached. MFDs exist and are well-defined in roughly homogeneously congested networks[10] Aggregating somehow chaotic single detector measurements - as seen in Fig. 1b,c - inside a regional network, results in the smooth MFDs curve between production and accumulation as seen in Fig. 1d, and between a b www.nature.com/scientificreports c
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