Congestion and extreme events in urban street networks

Congestion and extreme events in transportation networks are emergent phenomena with significant socio-economic implications. In this work, we study congestion and extreme event properties on real urban street (planar) networks drawn from four cities and compare it with that on a regular square grid. For dynamics, we employ three variants of random walk with additional realistic transport features. In all the four urban street networks and 2D square grid and with all dynamical models, phase transitions are observed from a free flow to congested phase as a function of birth rate of vehicles. These transitions can be modified by traffic-aware routing protocols, but congestion cannot be entirely mitigated. In organically evolved street networks, we observe a semi-congested regime which has both congested and free-flow components. In the free-flow regime, the extreme event occurrence probability is larger for small degree nodes than for hubs, a feature originally observed in non-planar scale-free networks. In general, with respect to congestion and extreme events, the urban street networks and regular square grid display similar properties.