Research On Bikeability Of Urban Street Based On The Bike Sharing Track Data

As a new type of green transportation tool,bike sharing not only effectively solves the problem of residents' last mile,but also promotes the return of the slow-moving system to people's vision.Although the popularity of shared bicycles is now weakening,the urban riding environmental problems exposed by it,such as t he quality of road riding,the availability of riding facilities,and the continuity of riding,have attracted widespread attention from governments,experts and scholars.The influencing factors of cycling in urban streets can be measured not only from th e perspective of the riding environment,but also by the behavior of riding.The focus of the riding environment is on the selection and analysis of the indicators of the built environment by researchers in combination with experience.The riding behavior is Evaluation of street environment facilities from the perspective of cyclists,and measurement of street environment from a more micro level.By constructing a linear regression model of the actual riding behavior and street environment,the degree of support for riding behavior in the street environment is deduced,and the relationship between the two is determined.The three factors are riding demand,riding environment,and riding behavior.Construct a rideability assessment to assess the street environment.Taking Longgang District of Shenzhen City as an example,the 14-day shared bike trajectory data is processed,and the use characteristics of the shared bike are analyzed from the riding time and distance.It is found that the shared bike riding time in Longgang District is about 15 min.The average cycling distance is 2770 m,which is consistent with the positioning of short-distance shuttle vehicles for shared bicycles.The morning and evening peaks of cycling behavior are obvious,and the role of connecting bus stations,subway stations and other land types is significant.The cycling behavior is mostly concentrated in Within Longgang District's “Four Major Commercial Districts”;Longgang Avenue serves as the skeleton of Longgang District,with high cycling frequency in some sections.Urban secondary roads have a positive effect on cycling behavior.Streets with frequent cycling are near commercial districts.City main roads and secondary roads.By constructing a time-regression linear regression model for riding behavior,riding demand,and street environment,it was found that the street riding frequency and cyclist travel demand,road grade,street access,distance from subway stations,The number of intersections are all related and affected by the spatial autocorrelation of the streets,the busyness of the surrounding streets has a certain effect on the cycling frequency of the streets.No correlation was found between the frequency of cycling and the number of employment shops on both sides of th e street,whether there were street lights,and whether there was on-street parking.Select the relevant street environment indicators as tuples,construct a multi-level hierarchical evaluation system of riding demand,street environment,and riding behavi or,and use the correlation coefficient of the regression model as the weight of each indicator to evaluate the street environment of Longgang District,Shenzhen.to evaluate.Focus on strengthening the cycling safety facilities of the city's main and seco ndary roads,such as increasing bicycle lanes;rationally plan the flow of bicycles and other transportation modes at stations or leisure places,and reduce obstacles to improve cycling safety and comfort.