Identifying critical road segments and optimizing resilience strategies based on multi-state congested characteristics

Abstract

The urban transportation systems are susceptible to congestion, accidents, and other costly delays, and recovery is challenging. Accurately identifying critical road segments and determining the optimization order are essential prerequisites for significantly improving network resilience. In this context, this paper proposes a method for identifying critical segments in congested road networks and a resilience optimization strategy based on the optimized order. Firstly, multiple congested states of segments are classified by their speed, and the performance is estimated by the probability-based method. Then, performance and temporal dimensions are combined to evaluate segment resilience. After that, the concept of local network resilience for segments is introduced. A resilience-based method for identifying critical road segments is proposed considering both segment performance and their connections with the network. Finally, the proposed resilience optimization strategy is demonstrated to significantly enhance network resilience by comparing it based only on complex network approaches or segment resilience. This has practical implications for alleviating traffic congestion or determining post-disaster network repair priorities.