Research On Urban Road Network Resroration Decision Under Snowfall Conditions Based On Resilience Assessment

As one of the key infrastructure of the city,urban transportation is open and complex,which is vulnerable to extreme weather,natural disasters,terrorist attacks and other emergencies.As far as the extreme weather is concerned,there are many rain and snow attacks in various regions of China in recent years.In winter,the northern region of China is often affected by heavy snow,resulting in urban road network and other infrastructure damage,which not only hinders the development of urban society and economy,but also fails to timely guarantee rescue needs.Therefore,it is essential to repair the damaged urban road network in time.Taking the damaged urban road network as the research object,this paper aimed to establish a road network restoration model which fully took into account the interests of managers and users when the road section was damaged due to snowfall,that is,when the traffic capacity of the road section was reduced,so as to provide a new idea for the restoration of the damaged road network.The main contents are as follows:Firstly,the average road speed was obtained based on the GPS data of taxi,the road capacity was calculated,the appropriate road resistance function was selected,the parameters were calibrated,and the traffic flow was further obtained.A method to obtain the traffic flow through the average road travel speed was proposed.According to the dynamic curve of road network performance with time,the definition of urban road network resilience under snowfall condition was determined.In order to effectively improve the efficiency of urban emergency management,this paper proposed a comprehensive evaluation system of urban road network resilience based on the road network performance curve from the two dimensions of time resilience and performance resilience.A bi-level optimization model of road network restoration based on resilience evaluation was constructed by combining resilience measurement with road network optimization to realize the restoration of road network.The upper model was a mixed integer planning model.The comprehensive index of enhancing resilience was taken as the optimization objective of road network restoration,so as to determine the selection and restoration sequence of damaged road sections to be restored,which consider the constraints of time and resources.The lower model adopted the user equilibrium allocation model to reflect the change of route choice behavior of travelers under the upper decision.Aiming at the bi-level optimization model constructed in this paper,the algorithm was designed based on the hybrid discrete particle swarm optimization algorithm,and it was improved combined with the characteristics of this model.Finally,the applicability of the model and algorithm was proved through the case study of Harbin Road Network,and the impact of resilience factor,the number of snow removal teams and the minimum performance requirements of travelers on the road network recovery strategy was analyzed.Through case analysis,this paper showed that the model can effectively improve the road network resilience level under the minimum performance requirements of travelers,effectively improve the efficiency of urban emergency management,and improve the research of urban road network recovery after disaster,which can provide more scientific decision support for decision makers to a certain extent.