Research On The Impact Of Built Environment Of Group City On Rail Transit Passenger Flow

Urban rail transit,as the backbone of urban public transportation system,is the key to alleviate city problems such as traffic congestion and environmental pollution and to build green and sustainable city.The “14th Five-Year Plan” for national urban infrastructure construction(2021-2025)points out that it is necessary to construct a development mode of urban functional structure and spatial development lead by rail transit,and strengthen the coordinated layout and construction of rail transit and urban functions.The spatial and temporal distribution of urban rail transit passenger flow reflects to some extent the travel rules of people within the city and the spatial layout of the built environment.When the structure of rail transit network does not match with the development layout of urban built environment,there are significant problems such as single functional land use around stations leading to significant time imbalance of passenger flow.Therefore,it is of great significance to analyze the mechanism of the impact of urban rail transit passenger flow and built environment on scientific TOD planning.There have been many studies exploring the influencing factors of urban rail transit passenger flow,but few studies start from the perspective of the impact of built environment around stations.This paper focuses on the rail transit passenger flow pattern under the influence of urban built environment based on the perspective of all network stations and station-to-station.Taking Chongqing Rail Transit as an example,this paper constructs a multi-level research framework for different research questions based on multi-source heterogeneous data such as rail transit passenger flow and relevant built environment data.It reveals the mechanism of the impact of urban built environment on different passenger flow patterns,improves cognition of travel rules and travel generation in urban rail transit.The main research contents are as follows:(1)Elaborate on the acquisition and processing methods of multi-source heterogeneous data sets such as urban rail transit passenger flow data and relevant built environment data.Visualize the temporal and spatial distribution of rail station passenger flow and station-to-station passenger flow at all network,line and station levels,analyze the temporal and spatial imbalance characteristics of passenger flow at different levels.Combined with relevant research and mountain group city characteristics,extract attraction range under walking environment around rail stations,select 18 variables in 4categories to characterize urban built environment,provide theoretical basis and data support for subsequent research.(2)Based on the perspective of urban rail transit network station passenger flow,ten passenger flow patterns are selected as research objects.Considering the temporal and spatial distribution characteristics of station passenger flow and residents’ travel characteristics,multi-scale geographic weighted regression(MGWR)model is introduced to analyze spatial heterogeneity and scale effect of built environment on various passenger flow patterns.Detailed suggestions are proposed to improve jobhousing separation and enhance coordinated layout between rail transit and urban functions.The results show that there are differences in key factors affecting various passenger flow patterns and their degree of influence,which are particularly evident in commuting time periods.In addition,local regression coefficients for each variable have different spatial distributions.(3)Based on the perspective of station-to-station OD passenger flow in urban rail transit network,taking OD passenger flow during peak hours in working days as research objects,gradient boosting decision tree(GBDT)model is constructed to capture nonlinear relationships.It reveals nonlinear effects and threshold effects of built environment attributes at departure end and arrival end on OD passenger flow.The results show that variables representing accessibility index such as distance from core group center have a greater impact on OD passenger flow during each period;commercial land use variables such as business land use,residential land use,administrative office use are most important factors affecting peak hour OD passenger flow;shopping entertainment variables have a greater impact on off-peak hour OD passenger flow.Each built environment variable shows nonlinear effects and threshold effects on OD passenger flow.