Modeling motor and non-motorized vehicle conflicts at roundabouts: Integrating trajectory fluctuation and kinematic metrics

Roundabouts, serving as critical nodes in urban transportation networks, the analysis of conflicts between motorized vehicles (MVs) and non-motorized vehicles (NMVs) is complex. Existing research has failed to adequately consider the impact of trajectory characteristics on conflict analysis modeling and has ignored the multidimensional mapping relationship between conflict levels and micro-level traffic behavior, resulting in the simplification of traditional conflict indicator classification. Therefore, this study introduced Circular Trajectory Entropy (CTE), Radial Deviation Index (RDI) and Curvature Change Rate (CCR) to measure the randomness of MV and NMV trajectories, and used a multi-class logistic model to quantify the impact of micro-characteristics and trajectory fluctuations on the severity of conflicts. Statistical results showed that MVs mainly adopted conservative deceleration behavior in response to potential conflicts, whereas NMVs exhibited higher path randomness and greater trajectory fluctuations at roundabouts. A logistic regression model based on multi-feature fusion performs exceptionally well in analyzing minor and severe conflicts. When using SHAP plots to reveal key influencing factors, it was found that CCR was the most influential feature in distinguishing between minor and severe conflicts. These findings can be used to evaluate the severity of conflicts between MVs and NMVs at signal-free roundabouts.