Research On The Behavior Of Access Mode Choice Of Urban Rail Transit Stations

The process of urbanization and motorization in China is in a period of rapid development.The problems of traffic congestion and energy consumption have become common problems in the development of large and medium-sized cities.Public transportation has obvious advantage in terms of per capita road utilization efficiency,energy conservation and emission reduction,etc.It is a long-term development strategy of urban transportation in China to ease urban traffic problems through optimizing public transportation.As the skeleton of the public transportation system,urban rail transit urgently needs the coordination of various modes of transportation and rail transit,and the research on the choice behavior of rail transit connections has become an important research field.Based on the research on the transfer behavior of rail transit stations in the past,from the point and line to the front and rear of the track,consider the correlation between the choice of the front end of the track and the choice of the back end connection mode,and explore the behavior characteristics of select access mode among the whole process and front and rear end of the typical rail transit travel.Starting from micro-individuals’ access mode choice of urban transit,the rail transit traveler is the main body of travel behavior,and the Logisitc regression model and the track connection mode selection behavior neural network model are established respectively.A large number of field surveys are conducted on urban rail transit and track travellers in Chongqing to capture the travel behavior characteristics of rail transit travelers,to carry out model prediction and comparative analysis of results,to further explore the mechanism of rail transit connection mode selection behavior,and proposed corresponding orbits.The research results show that compared with the characteristics of travellers and travel,the characteristics of the station have little influence on the access mode choice of the rail traveler;the front-end access mode will have significant influence in the choice of the rear-end connection mode of the track.Through the Logisitc regression model and the orbital mode selection behavior neural network model prediction results and their comparative analysis show that the neural network model can more accurately describe the nonlinear mapping between input variables and output variables,and can better predict the selection behavior of urban rail transit stations.Rail transit mode selection behavioral neural network model has certain use value.However,compared with the Logistic regression model,the neural network model is less explanatory.Finally,according to the research results,the proposed optimization of the connection of rail transit through the transportation modes such as walking,regular bus,motorcycle/bicycle and private car is proposed.The research results can provide a basis for studying the behavior mechanism of access mode choice of urban rail transit stations,rationally plan the layout of rail transit facilities,and improving the efficiency of urban rail transit travel.It has an urgent theoretical and practical significance for optimizing urban traffic structure optimization and orbital connection resource allocation.