Spatial Heterogeneity Of Influencing Factors And Characteristics Of Shared Bicycle Travel Based On GWR

Sharing bicycles,as a new kind of environmentally friendly travel mode,has been developed in recent years.Compared with public bicycles,they have the flexibility and convenience of "stopping at will",and attract a large number of travelers.It further promotes the solution of the "last kilometer" trip and the development of green traffic,and plays a good guiding role in the transformation of traffic mode and the optimization of connecting and connecting mode.Therefore,this paper will make a study on bicycle travel characteristics,travel influencing factors and spatial heterogeneity in order to provide reference basis for sharing bicycle management and scheduling,according to the data of shared bicycle travel on weekdays.And to provide planners or policy makers with reference to effective factors to further promote urban green travel.In this paper,based on the characteristics analysis of domestic and foreign bicycle and the research status of influencing factors,and based on the information of the starting and ending points of Shared bicycle trips in xi ’an city in the working day of 2018,the research is carried out according to the ideas of travel data preprocessing,travel data characteristic analysis,travel influencing factors and spatial heterogeneity of influencing factors.Specifically,the research area and the measurement range of the index in the region are determined firstly,and then the correction,deletion and the generation of OD data are carried out according to the basic data.Secondly,the hot spot level of trip is quantitatively analyzed by using hot spot detection model according to the end point data of morning and evening peak sharing cycle,and on the basis of this,the characteristics of trip time and the trip distance related to subway are explored.The distance range between shared bike and subway in different periods is obtained,and the transfer range of long distance and close station is analyzed in combination with the hot spot.Thirdly,combined with the analysis results of the data characteristics and the literature data,the index of influencing factors of shared bicycle use is identified,and the socioeconomic variables and road infrastructure variables are determined.Public transport variables and other service facilities variables of these four categories,a total of 14 indicators.Then,using multiple linear regression analysis to determine the significant influence factors and the degree of influence of shared bike use;Finally,according to the significant factors,the spatial instability and spatial heterogeneity were studied by using the geographical weighted regression model.The results show that the distribution density of shared bicycle facilities has spatial heterogeneity on the distribution of the starting point of bicycle travel in the early peak and the start point of the bicycle trip in the late peak.The influence of enterprise distribution density on early peak end point distribution has spatial heterogeneity,and the influence of catering type distribution density on late peak trip end point has spatial heterogeneity.In addition,the model indexes of the global regression analysis and the geographical weighted regression analysis are compared and analyzed.The results show that the geographical weighted regression analysis is more effective and accurate,and the spatial distribution characteristics of the influencing factors are revealed.