Typology of bike lane users motion on horizontal curves: a surrogate safety approach

Abstract

[EN] This study examines the safety implications of horizontal curves in bike lanes, focusing on cyclists' and e-scooter riders' behavior. As cities transition from auto-centric to sustainable transportation systems, bike lanes are increasingly integrated into urban infrastructure, particularly in Europe. Despite the benefits of active transportation, safety concerns for bike lane users persist. Horizontal curves can pose significant safety risks due to lower radii, higher curvature degrees, and reduced surface friction. This study has shown that cyclists and e-scooter riders are siginificantly affected by sudden changes in geometry, reacting by aggressive maneuvers and increased risks of conflict and fall. To address this, a motion analysis methodology is proposed to identify risky maneuvers in bike lanes, using microscopic analysis of trajectory and speed, revealing naturalistic reactions of bike lane users to various curve geometries. The study employs previous track typology and density-based spatial clustering algorithm to cluster distinct trajectory patterns. Additionally, a decision tree regression model finds the degree of curvature as the most effective variables in user motion behavior. Findings indicate that horizontal curve geometry significantly influencing user behavior. Generally, left-turn maneuvers on curve show greater diversity and higher risks, especially in sharp curves on a bi-directional bike lane. Speed analysis reveals that reducing curve radii increses speeding behaviors and variance. The method proposed is scalable and can help in the development of mitigation strategies such as geometric treatments, surface skid resistance improvements, enhanced signage, and enforcement in high-risk curves identify after using this approach.