A resilience-oriented evaluation and identification of critical thresholds for traffic congestion diffusion

Identifying, evaluating, and managing traffic congestion is crucial to constructing smart cities. However, there are few studies on congestion quantification from the system perspective. We symbolized traffic congestion as an internal disturbance and proposed a resilience-oriented assessment method to evaluate traffic state and effectively identify the critical threshold of traffic congestion diffusion. We integrated multi-dimensional indexes to represent the network's resilience and constructed the congestion index from both resilience and transport system perspectives. The network's minimum required performance (MRP) and the critical threshold of congestion diffusion are calculated based on the percolation theory. The results showed that this method has more stability and timeliness than typical approaches and accurately identifies critical instants when traffic congestion diffusion. Sensitivity analysis further verifies that the MRP is indispensable in traffic state assessment. This method can prejudge the crucial instant of traffic congestion diffusion and help traffic management departments build efficient response procedures.