Exploring the Influence of Multiscale Urban Road Network Centrality on Cycling Behavior: A Case Study of Shenzhen Longgang District

Abstract

Cycling, which is recognized as a sustainable and convenient mode of urban transportation, alleviates traffic congestion and improves last-mile connectivity. However, there has been relatively little research on how urban roads affect cycling behavior, even though the roads themselves are closely related to such behavior. This paper applies an urban road network analytical framework to investigate the centrality patterns of the multiscale road network in Shenzhen Longgang District as a case study. Monthly trajectory data from shared bikes in Longgang, Shenzhen, are chosen for spatial distribution analysis. In this study, a multivariate regression model was constructed to examine the determinants of cycling frequency. The model incorporates cycling frequency as the dependent variable, while three key independent variables were considered: shared bicycle supply, road network centrality, and street environmental characteristics. This analytical framework enables a comprehensive assessment of the factors influencing cycling behavior in urban contexts. Several interesting observations are revealed. The centrality metrics of road networks at multiple spatial scales exhibit significant associations with cycling behavior, with varying degrees of influence. Combining the analysis results, optimization strategies for urban street cycling are proposed from three perspectives: matching supply and demand, constructing a cycling network, and optimizing the cycling environment to promote cycling trips.

Keywords: Multiscale road network, Centrality, Cycling behavior, Urban context