Dynamic cascading failure analysis in congested urban road networks with self-organization

• Main Authors: Jia, Hongfei, Li, Feiyan, Yang, Lili, Luo, Qingyu, Li, Yongxing
• Other Authors: School of Civil and Environmental Engineering
• Format: Article
• Language: English
• Published: 2021
• Subjects: Engineering::Civil engineering; Logistics; Transportation Network
• Online Access: https://hdl.handle.net/10356/145753
• Institution: Nanyang Technological University

An efficient freight transportation system is a core part of the modern urban logistics. The transportation system depends on an efficient urban road network. In urban road networks, the failure of some components leads to others failing in succession, triggering cascading failures. This may cause the collapse of the freight transportation system. A cascading failure model is proposed for analyzing the propagation of failures on urban road networks, which can provide guidance for the planning of freight transportation routes in case of emergency. When analyzing the cascading failure process, failed components are commonly deleted permanently. Travelers will avoid failed components, resulting in no increase in traffic flow on the failed components. At the same time, vehicles on these failed components will evacuate slowly to alleviate congestion. Considering this point, this paper proposes a dynamic cascading failure model. This model is established based on a hybrid routing strategy in which traffic flow is distributed according to global and local information. Specifically, the new input traffic demand is assigned along efficient paths in an urban road network (using global information). Efficient paths are determined according to the weights of all edges in urban road networks. Meanwhile, failed edges transfer some traffic flow to their normally working neighbors by self-organization (using local information). The proportion of transferred traffic flow is determined by the residual capacity of the failed edges' normally working neighbors. The feasibility of the proposed model is verified in a partial road network in Changchun, China.