Volume 39 Issue 3
Jun.  2021
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Article Navigation >  Journal of Transport Information and Safety  > 2021  >  39(3): 33-40
SHEN Ling, LU Jian, WANG Chengchen. Rapid Generation and Dynamic Optimization of Traffic Emergency Plans for Large-scale Events[J]. Journal of Transport Information and Safety, 2021, 39(3): 33-40. doi: 10.3963/j.jssn.1674-4861.2021.03.005
Citation: SHEN Ling, LU Jian, WANG Chengchen. Rapid Generation and Dynamic Optimization of Traffic Emergency Plans for Large-scale Events[J]. Journal of Transport Information and Safety, 2021, 39(3): 33-40. doi: 10.3963/j.jssn.1674-4861.2021.03.005
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Rapid Generation and Dynamic Optimization of Traffic Emergency Plans for Large-scale Events

doi: 10.3963/j.jssn.1674-4861.2021.03.005

  • School of Transportation, Southeast University, Nanjing 210096, China

  • Received Date: 2020-09-01
    Abstract
  • The generation and dynamic optimization technology of traffic-emergency plans under large-scale emergencies rely on experience, and the manual plan lacks targeted and quantitative emergency measures.The feature attributes of emergencies are extracted to quickly generate the optimal matching plan.The initial plan is quickly generated based on case-based reasoning(CBR)and naive Bayesian classification and selected according to the posterior probability obtained by the Bayesian classification algorithm.The knowledge base and rule base of traffic emergency plans are established based on rule-based reasoning(RBR), and the content of the plan is modified by forwarding reasoning.The evaluation-index system of emergency-response capability and emergency severity is established based on the fuzzy analytic hierarchy process(FAHP).Taking Beijing 2022 Winter Olympic Games as the case background, the method can quickly generate the optimal matching plan and realize dynamic adjustment and improvement.

     

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