Resilience Assessment of Urban Road Network Based on Day-to-Day Traffic Assignment

In order to effectively evaluate road network performance under major disruptive events, on the basis of a day-to-day traffic assignment (DTA) model, an urban road network resilience assessment model is proposed. With explicit consideration on the dynamic characteristics of traffic flow under a major disruptive event, a DTA model that comprehensively cover the influencing factors including travelers’ cognitive update and behavioral inertia is constructed, and then a heuristic solution algorithm is designed. Based on the DTA model, a road network accessibility index is defined, and a resilience metric as well as an evaluation model are established, which can fully measure the system performance during the disruptive event life cycle. Finally a case study is performed on the Nguyen and Dupuis network. The results show that, after the disruptive event, the road network resilience fluctuates in the first 10 days; then as the traffic flow distribution tends to be stable, it increases monotonically from 0.323 on the 10th day to 0.794 on the 50th day, an increase by 145.77%. Compared to classical stochastic user equilibrium (SUE) model, there are significant differences in both road network accessibility and resilience indicators obtained from DTA model. The road network accessibility index under SUE model monotonically increases with time, while that index under DTA model fluctuates sharply in the first 15 days, after then increasing monotonically. It indicates that, in order to acquire accurate road network resilience metric, travel decision behaviors and corresponding traffic assignment model must be accurately assumed in the first place. All factors including travelers’ behavior inertia, the degradation degree and recovery rate of link capacity, and road network congestion degree have a significant impact on the distribution of traffic flow, which in turn affect road network accessibility index and ultimately result in obvious changes in road network resilience metric. As a result, relevant parameters should be reasonably calibrated under full investigation over practical applications.