| Under the policy background of transportation power,public transportation system,as a key part of urban modernization system,plays a huge role in urban management and residents’ life.However,a variety of emergencies have a continuous and unpredictable impact on the operation of public transport system.The public transport system is faced with opportunities and challenges,which requires its operators to have accurate understanding and scientific management of the stability and anti-disturbance ability of public transport system.Therefore,it is a valuable research perspective in the field of transportation to introduce the research results of resilience science into bus network,explore the resilience of bus network and its influencing factors,and quickly digest and eliminate the negative impact of emergencies.Based on the complex network theory,this paper designs the topology model structure of urban public transport network,and analyzes the node degree,clustering coefficient and centrality index of the network.Secondly,put forward suitable for urban transit network resilience concept and measure,based on the network performance indicators and emergency event simulation strategy has been clear about the 6 kinds of toughness calculation(IDC,IBC,ICC,RDC,RBC,RCC),and through the literature research and application experience for reference,analyzes the factors influencing urban theory-oriented and toughness of 24 indicators.Then,based on The Bayesian network,the resilience model of urban bus network was constructed,the structure learning method and parameter learning method were selected,and the evaluation indexes of model quality and causal inference method were determined.This article select the Beijing bus operation process of multi-source data,Beijing bus network topology model is established and analyzed,with Beijing’s four representative line road(740,966 road,610 road,619 road)for the typical,using K2 structure learning method and learning method to get the optimal bayesian estimation parameters of resilience model,The accuracy is 0.8571,0.7143,0.7143 and 0.8571 respectively,and the corresponding calculation method of toughness is IBC and RBC based on intermediary centrality calculation.The causal inference models of four routes were modeled,identified,estimated and refuted to verify the causal relationship between the influencing factors of toughness,and the recommendations for toughness optimization strategies were given from three aspects: driving plan,bus connection and intelligent emergency response system.The research results of this paper can enrich the research system of the resilience of urban bus network,and provide a theoretical framework for analyzing the absorptive capacity,adaptive capacity and resilience of urban bus network in response to emergencies.Taking the toughness index as the starting point,the causal inference model of Bayesian network was established to analyze the causal relationship between the influencing factors and the toughness of public transport system.The results provide a scientific and accurate model basis for the study of bus system resilience,and help to put forward more effective suggestions for improving resilience. |
