SIT-PET: Long-Term Multimodal Traffic Trajectory Data with PET-Based Interaction Events at a Signalized Intersection
Markus Steinmaßl, Karl Rehrl, Timo Vornberger (): SIT-PET: Long-Term Multimodal Traffic Trajectory Data with PET-Based Interaction Events at a Signalized Intersection In: Data 2026, 11, 68.
In this paper, we present a curated dataset derived from continuous multi-object tracking observations over a two-year period from a signalized urban intersection in Salzburg, Austria. The dataset includes time-resolved trajectories of multimodal road users, post-processed object attributes, movement relations, and Post-Encroachment Time values computed for a fixed set of eight predefined multimodal traffic conflict scenarios. Moreover, traffic signal data are included and can be used as contextual information. A temporal six-month subset is published via Zenodo including usage examples written in python. The full dataset can be provided on request. Potential applications include traffic safety analysis, behavioral modeling, method development for interaction detection, and educational use in data-driven traffic research.
