The effects of built environments on bicycle accidents around bike-sharing program stations using street view images and deep learning techniques: The moderating role of streetscape features

Abstract

With the global rise of bike-sharing programs (BSP), planners and traffic experts have raised concerns as to whether the rapid growth of BSP ensures cycling safety. Despite numerous studies on built environments encouraging bike usage, there is limited knowledge whether streetscape environments around BSP stations affect bicycle accidents. We address this gap by investigating the relationships between various built environments and bicycle accidents around BSP stations, with a particular focus on the moderating effects of comprehensive streetscapes. Streetscape environments, estimated through semantic segmentation and k-means clustering, were used in two-level negative binomial regression models to clarify how street- and station-level environments affect different types of bicycle accidents. The findings indicate increased crash likelihoods on higher-speed roads, streets with traffic facilities, in proximity to public transportation infrastructure, and specific streetscape types. In particular, streetscape features like green oasis streets and open-sky roadways positively contribute to mitigating the negative effects of traffic facilities, such as bike networks and crosswalks, on cycling safety. This study aids in developing comprehensive strategies and guidelines to retrofit built environments for better traffic safety and thereby promote urban cycling.