A Naturalistic Approach for Identifying Latent Behavioral Classes of Two- And Three-Wheel Vehicle Users

Abstract

Two- and three-wheel vehicle users are generally considered a homogeneous group in traffic safety research. However, evidence supports that rider behaviors vary largely based on situational factors such as interactions with vehicles, other riders, and the environment. Identifying latent behavioral subgroups can therefore provide a more meaningful basis for understanding behavioral patterns among riders, as well as developing targeted safety interventions. This study aims to uncover behavioral patterns among two- and three-wheel vehicle users within Copenhagen’s bicycle lanes. Observational video data collected in 2025 at four locations were analyzed using Latent Class Analysis to identify distinct behavioral groups based on vehicle, environmental, and sociodemographic factors. Three resulting classes were then described based on the profile of their observed characteristics. Findings from this research provide insights that can be used to inform targeted safety and policy interventions as a means of addressing subgroup specific behaviors among two- and three-wheel vehicle users.