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.
翻译:评估碰撞风险是有效交通安全管理面临的一个关键挑战。部署无人驾驶飞行器解决这一问题,鉴于其广泛的视觉场和移动灵活性,已经显示出很大的希望。这项研究表明,无人驾驶飞行器和V2X连通性可用于跟踪道路使用者的移动,并评估交叉路口可能发生的碰撞。这项研究使用了无人驾驶飞行器拍摄的视频。拟议方法结合了基于深学习的跟踪算法和时间对时间的任务。其结果不仅为车辆识别潜在碰撞和运动规划提供了有益的信息,而且还为城市道路机构和安全管理工程师提供了宝贵的工具。