Resilience of Urban Road Network to Malignant Traffic Accidents. (6th May 2022)

• Record Type: Journal Article
• Authors: Lu, Yiding; Zhang, Zhan; Fang, Xinyi; Gao, Linjie; Lu, Linjun
• Other Names: Ghahari Seyed Ali Academic Editor.
• Is Part Of: Journal of advanced transportation. Volume 2022(2022)
• Publication Date: 2022-05-06
• Subjects: Transportation -- Periodicals; 388.05
• DOI: 10.1155/2022/3682472
• Languages: English
• ISSNs: 0197-6729

Abstract

Abstract : Malignant traffic accidents are typical devastating events suffered by the urban road network. They cause severe functional loss when loading on the urban road network is high, exerting a significant impact on the operation of the city. The resilience of a road network refers to its ability to maintain a certain level of capacity and service when disturbed by external factors and to recover after a disturbance event, which is a crucial factor in the construction of transportation infrastructure systems. A comprehensive understanding of the adverse effects of malignant traffic accidents on the urban road network is imperative, and resilience is a concept employed to systematically explain this. This study investigates the impact of malignant traffic accidents on the resilience of the urban road network. A simulation is carried out focusing on an ideal urban road network, describing the temporal and spatial distribution of the average speed of road sections in the network. Inspired by the simulation experiment results, the ideal resilience curve is summarized, and the theory of resilience concept portrayal is innovatively developed into "6R" (redundancy, reduction, robustness, recovery, reinforcement, and rapidity). Combining the topological and "6R" resilience attributes of the urban road network, the urban road network resilience evaluation system is constructed, which yields an all-round and full-process evaluation for the urban road network with malignant traffic accidents. Results show that under malignant traffic accidents, the resilience of high-class surface roads, such as primary roads, is the poorest, suggesting that more attention and resources must be devoted to high-class surface roads. This study on the urban road network deepens the understanding and portrayal of its resilience and proposes an evaluation method to analyze its performance under disruption events.