Analysis of factors influencing cycling count: A micro-level study using road segment count data in London

Abstract

Cycling has gained increasing popularity worldwide as a healthy and sustainable mode of travel. This study aims to investigate the factors affecting the cycle count at the road segment level based on a detailed survey dataset of 794 road segments in London from 2015 to 2019. A spatial regression model was employed to control for possible spatial correlations among neighboring count points. The influencing factors at three spatial levels were considered in this study, including the characteristics of the target road segment, adjacent road segments, and adjacent areas. In addition, we investigated the differences in cycle counts between private and rental cycles during different time periods (morning peak, evening peak, and off-peak hours). The results indicated that private cycle count was positively correlated with cycle facility, public transit, minor road, network continuity, and connectivity. A similar positive effect was found for rental cycles, although the magnitude of this effect was smaller. In addition, parking facilities (i.e., docking stations and cycle parking) had significant impacts on cycle counts for both private and rental cyclists. This study provides several practical suggestions for improving cycling environments.