Quantification of Urban Resilience to Natural Hazards from Traffic-Flow Data

Given that in addition to the robustness of the transportation, utility, electricity, and telecommunication networks, perhaps the most robust network that serves urban resilience is the living network of the citizens of a city, in this paper we quantify urban resilience to natural hazards by processing traffic-flow data. From the recorded traffic-flow values (number of vehicles per time) at various locations on major traffic city arteries, we compute the probability density for finding a vehicle at some distance x, from the city center at time t, and, subsequently, we calculate the time history of the mean-square displacement (MSD) of vehicles from the city center. The shape of the MSD time histories computed in this study from traffic-flow data exhibits striking similarities with the MSD time histories computed by tracking GPS locations from individual cellphone users. Accordingly, this study that uses an entirely different type of data confirms our previous finding that large American cities, following a natural hazard, revert immediately to their initial steady-state behavior and resume their normal, pre-event activities.