Evaluation Of Intermodal Utility And Multi-modal Network Capacity Considering The Urban Transport Hubs

With the expansion of the city and the maturity of the multimodal traffic network system,the sub networks of the urban multimodal traffic network are more and more closely connected.The status of the traffic hub is more and more important.Reasonable planning and design of urban multimodal transport hub has become the most effective method to optimize the stock resources and maximize the transportation capacity of existing urban multimodal transport network.Therefore,this paper studies and analyzes the transfer hub hierarchy,combined travel utility,network capacity calculation and hub evaluation based on network capacity of urban multimodal transportation system.Firstly,with the background of big data,different types of data obtained from multiple channels,such as subway or bus IC card data and sharing-bike track data,are used to match different transfer travel chains based on hubs to calculate the demand of each transfer type of each node.At the same time,the API interface of Baidu Map is used to extract POI data.Linear regression is used for land use attributes analysis.Considering the location characteristics of nodes in the city,this paper divides the multimodal traffic hubs in the city.Taking Nanjing as an example,five types of multimodal urban traffic hubs are obtained.Secondly,through the design of questionnaires,implementation of surveys,statistical analysis of survey data and the use of survey data,wecalibrate the multimodal travel utility based on MNL and ML models.A typical multimodal travel utility equation is constructed,and the multimodal travel utility equation is used to analyze the influence that transfer hub has on the multimodal travel behaviour.Thirdly,on the basis of the existing research results,a multimodal urban trafficnetwork capacity model is established,which includes the upper-level model to maximize the potential network demand and the lower-level model that conduct the multimodal traffic network assignment.In this model,the choice of destination,travel mode,transfer hub and travel path are involved.This paper analyses the impact of new transfer hub on the network with an example and introduces the value of time difference coefficient to modify the impedance function of the lower-level model.Finally,by introducing the share rate index,this paper puts forward a method to identify the key transfer influencing factors by predicting the change of share rate,and then analyses the differences of key transfer influencing factors for different levels of hubs.Different optimization strategies are applied for different levels of hubs.Finally,based on the network capacity model,the hub optimization strategies are evaluated by using the network capacity and green mode share rate index.The results show that the optimization of hub transfer attributes can improve the sharing rate of green travel mode,so it is necessary to optimize both hub capacity and hub transfer attributes to improve the network level of service.According to the analysis results of the final example,the increase of the capacity of the bicycle transfer hub can effectively improve the network capacity,while the increase of the park-and-ride hub capacity has a small impact on the network capacity.The impact of hubs at different locations on the multimodal transportation network is also different.Therefore,it is necessary to find the key nodes that affect the improvement of the multimodal traffic network capacity.