Determinants influencing risks in e-bike cyclists under mix traffic condition: a partially constrained random...

The global adoption of e-bikes improves urban mobility but can impact traffic safety. Braking behavior is a vital task with a high association with e-bike cyclists' safety, especially under mixed traffic conditions. Although traditional studies on cyclists' traffic safety analyses have been conducted based on crash data in transportation research, most studies focus on crash severity rather than the specific behavior risks associated with different traffic conditions. This paper uses field experiment data to study the factors that affect the observed braking behavior of e-bike cyclists under mixed and non-mixed traffic conditions. To simultaneously account for this flexibility to model varying effects across traffic conditions and capture unobserved heterogeneity, a partially constrained random parameters logit model with heterogeneity in the means is estimated. The analysis controls cyclists' characteristics, behavioral factors and roadway characteristics. Our main findings indicate that safety is affected by mixed traffic conditions, which has implications for infrastructure design and cyclist characteristics. Different head-turning and handlebar turning behavior reflect cyclists' risk perception and risk avoidance responses under various road conditions. Overall, accounting for unobserved heterogeneity and cross-condition correlation provides a more nuanced understanding of e-bike cyclists' braking behavior.