Assessing collision risk is a critical challenge to effective traffic safety management. The deployment of unmanned aerial vehicles (UAVs) to address this issue has shown much promise, given their wide visual field and movement flexibility. This research demonstrates the application of UAVs and V2X connectivity to track the movement of road users and assess potential collisions at intersections. The study uses videos captured by UAVs. The proposed method combines deep-learning based tracking algorithms and time-to-collision tasks. The results not only provide beneficial information for vehicle's recognition of potential crashes and motion planning but also provided a valuable tool for urban road agencies and safety management engineers.
@article{arxiv.2110.06775,
title = {Using UAVs for vehicle tracking and collision risk assessment at intersections},
author = {Shuya Zong and Sikai Chen and Majed Alinizzi and Yujie Li and Samuel Labi},
journal= {arXiv preprint arXiv:2110.06775},
year = {2021}
}
Comments
Under review for presentation at TRB 2022 Annual Meeting