| With the rapid increase of the urban population,the process of urbanization is accelerating,and urban congestion and traffic pollution have become important issues for building a healthy and sustainable smart city.The promotion of public transportation and green transportation is an important step to achieve this goal.In Chinese cities such as Suzhou,Nanjing,Hangzhou,Nanchang,many subways are being built to alleviate traffic congestion and reduce environmental pollution,and the deep integration of public bikeshare and subway is the key measure to achieve this goal.However,the research on the impact of newly-built subway on public bikeshare has not been extensively studied.In order to deepen the understanding of this research field,this paper will carry out the impact of newly-built subway on public bikeshare,which is really useful for indepth understanding of subway and public bikeshare.There are important theoretical and practical values for deeply understanding the relationship between subway and public bikeshare and realizing the integration and development of these two transportation systems.The specific research content is as follows:First of all,the world and Chinese bikeshare development overview is described,and the basic situations of the Suzhou Metro Line 4(M4)and Suzhou Public Bikeshare System(SPBS)in the study area are also introduced,and the overviews of the cycling data and station data are used in this article too.Furthermore,the data source and preprocessing are explained to ensure the authenticity and scientificity of the study data.Secondly,the cycling data of SPBS is used to analyze the laws of time and space,and the trend analysis of usage,travel time and travel distance within a year to explore the changes in time trends.Furtherore,the changes in the usage of four types in the time series before and after the operation of M4 are explored.Finally,spatial analysis of the loan amount,the repayment amount,the total amount of loans,the usage value of the loan difference nuclear density,cold and hot spots,clusters,and outliers on the daily and monthly scales are carried out.Finally,the supplementary analysis of the impact of M4 on SPBS mobility patterns is explained.First of all,we perform a causal analysis on the changes in travel time,travel distance,and passenger age.In addition,the igraph package of the R language is applied to perform statistical analysis on the characteristics of the SPBS mobility network,including node flow,node degree,clustering coefficient,betweenness centrality and Page Rank.Furthermore,the spatial analysis of node degree,node in degree,node out degree,and point of betweenness centrality is applied to explore the changes in connectivity and heterogeneity of the SPBS network. |
