Evaluation And Hierarchical Optimization Strategy For Urban Street Bikeability Based On Multi-Source Data

In the background of increasing traffic congestion,change in philosophy of people towards travel,and the development of shared bicycles,the demand for cycling is increasing.However,there are still many problems in urban streets,such as interrupted cycling,mixed lane use of motor vehicles and non-motorized vehicles,and the occupation of non-motorized lanes,resulting in low bikeability of urban streets.At present,problems of various evaluation indicators for cycling environment,low data precision,and weak model portability,restrict the application of related researches.Therefore,this paper first obtained multi-source data through open platforms,then built an urban street bikeability evaluation system based on factor analysis-entropy weight combination method and fuzzy comprehensive evaluation method.Finally,a hierarchical optimization strategy for cycling environment based on cycling demand matching was proposed.This study enriches and improves the theory of cycling environment evaluation and optimization,and has important practical significance for promoting the vigorous development of urban bicycle travel mode.This study selected 14 indicators to evaluate street built environment from safety,comfort,and convenience levels.The Beilin District of Xi’an City was chosen as research area,and a 50 m street segment was used as the research scale.Based on Arc GIS,Python,and the visual semantic segmentation algorithm,multisource data of OSM road network,POI,DEM elevation,and street view images were obtained.Then a street bikeability evaluation system based on factor analysis-entropy weight combination method and fuzzy comprehensive evaluation method was constructed,followed by the calculation of Bikeability Index(BI)of each street segment.Finally,we measured the level of cycling demand in the road segment using POI density,POI mixing degree and BI data,proposed a road network hierarchical optimization strategy and specific optimization measures based on the matching degree of cycling demand and cycling environment.The results indicate that the evaluation and hierarchical optimization method for street bikeability proposed in this study is suitable for large-scale urban street cycling environment assessment and has good transferability;There are significant differences in the impact of different types of built environment indicators on street bikeability.The isolation type of bicycle lanes,road grade,and greening rate indicators have the greatest impact on street bikeability.Overall,safety indicators>comfort indicators>convenience indicators;The hierarchical optimization method for street improvement based on matching degree between cycling demand and cycling environment can accurately locate the most urgent urban streets that need improvement,and guide efficient resource allocation in situations where resources are limited;Empirical research showed that 22.64% of the streets in Beilin District had conflicts between cycling demand and cycling environment,and improvement priority should be given to these streets.