Data-driven study of transit and bicycle interchange

Abstract

With the increasingly serious urban congestion problem, the government launched the concept of green transportation, and bike-sharing came into being. However, at present, less consideration is given to bike-sharing in urban planning, which leads to insufficient supply in bike-sharing during the peak period and serious accumulation after the peak period. Seriously hindered the development of slow bus integration. In order to better develop green transportation and promote the healthy and sustainability of travelers. By fusing GPS data and credit card data, this paper puts forward a bus stop derivation rule based on development of urban ground transportation system, supplements the bus stop information, and identifies the transfer behavior between bus and bike-sharing based on the transfer model. Finally, taking Beiguan North Station and Beitan Station of Jinan Beiyuan Street as examples, the influence of built environment on the transfer between public transport and bike-sharing is analyzed. The results show that the transfer volume in bike-sharing is highly positively correlated with the single functional area of residential area, commuting/general studies, leisure and entertainment, and strongly correlated with residential-other, commuting/general studies-leisure and entertainment, leisure and entertainment-other and mixed functional areas.