A novel method for determining the trajectory of vulnerable road users from video recordings and its practical implications

Accurate trajectory reconstruction is essential for reliable surrogate safety analysis, yet most computer-vision pipelines still represent road users using the geometric centre of a bounding box-a simplification that introduces systematic spatial bias. We propose a novel trajectory-estimation method that computes a representative point derived from object geometry and motion dynamics, yielding a more realistic approximation of the true occupied space. The method was evaluated on 64 h of video data covering 3 traffic environments and 223 intersections of car-pedestrian trajectories. Using Post-Encroachment Time (PET) as the primary performance indicator, we show that the proposed method produces PET values that differ from the bounding-box-centre approach by 0.69 s on average, with discrepancies exceeding 1 s in 16.7 % of all conflict events. These deviations systematically shift the classification of conflict severity, leading to up to 3.6 % of events being re-assigned to a different PET-based risk category. The results demonstrate that conventional trajectory representations may substantially distort surrogate safety metrics. Beyond safety applications, the method enables more precise estimation of the spatial footprint of different road-user types, supporting advanced analyses of street-space allocation and utilisation.