Resilience of Urban Road Network to Malignant Traffic Accidents

被引:2
|
作者
Lu, Yiding [1 ]
Zhang, Zhan [2 ]
Fang, Xinyi [1 ]
Gao, Linjie [1 ]
Lu, Linjun [1 ]
机构
[1] Shanghai Jiao Tong Univ, Sch Naval Architecture Ocean & Civil Engn, Dept Traff Engn, Shanghai 200240, Peoples R China
[2] Shanghai Jiao Tong Univ, Sch Design, Shanghai 200240, Peoples R China
关键词
VULNERABILITY ANALYSIS;
D O I
10.1155/2022/3682472
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
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.
引用
收藏
页数:13
相关论文
共 50 条
  • [41] Analysis of Urban Road Traffic Network Based on Complex Network
    Tian, Zhao
    Jia, Limin
    Dong, Honghui
    Su, Fei
    Zhang, Zundong
    [J]. GREEN INTELLIGENT TRANSPORTATION SYSTEM AND SAFETY, 2016, 138 : 537 - 546
  • [42] Technical Resilience of an Urban Road Network after an Earthquake
    Deng, Milan
    [J]. CONSTRUCTION RESEARCH CONGRESS 2020: INFRASTRUCTURE SYSTEMS AND SUSTAINABILITY, 2020, : 295 - 303
  • [43] Improving regional road network resilience by optimised traffic guidance
    Kaviani, Arash
    Thompson, Russell G.
    Rajabifard, Abbas
    [J]. TRANSPORTMETRICA A-TRANSPORT SCIENCE, 2017, 13 (09) : 794 - 828
  • [45] Predicting road traffic accidents using artificial neural network models
    de Soto, Borja Garcia
    Bumbacher, Andreas
    Deublein, Markus
    Adey, Bryan T.
    [J]. INFRASTRUCTURE ASSET MANAGEMENT, 2018, 5 (04) : 132 - 144
  • [46] Predicting Road Traffic Accidents-Artificial Neural Network Approach
    Gataric, Dragan
    Ruskic, Nenad
    Aleksic, Branko
    Duric, Tihomir
    Pezo, Lato
    Loncar, Biljana
    Pezo, Milada
    [J]. ALGORITHMS, 2023, 16 (05)
  • [47] Determination of Key Nodes in Urban Road Traffic Network
    Tian, Zhao
    Jia, Limin
    Dong, Honghui
    Zhang, Zundong
    Yang, Yanfang
    Su, Fei
    [J]. 2014 11TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA), 2014, : 3396 - 3400
  • [48] Spatial development of urban road network traffic gridlock
    Qi, H. S.
    Y, Y.
    Wang, Dian Hai
    Bie, Y. M.
    [J]. INTERNATIONAL JOURNAL OF CIVIL ENGINEERING, 2015, 13 (4A) : 388 - 399
  • [49] Urban road traffic network vulnerability identification method
    [J]. Zhang, Y. (sinkey@126.com), 1600, Chang'an University (26):
  • [50] Fuzzy peak hour for urban road traffic network
    Tian, Zhao
    Jia, Li-Min
    Dong, Hong-Hui
    [J]. MODERN PHYSICS LETTERS B, 2015, 29 (15):