The development of autonomous vehicles arises new challenges in urban traffic scenarios where vehicle-pedestrian interactions are frequent e.g. vehicle yields to pedestrians, pedestrian slows down due approaching to the vehicle. Over the last years, several datasets have been developed to model these interactions. However, available datasets do not cover near-accident scenarios that our dataset covers. We introduce I see you, a new vehicle-pedestrian interaction dataset that tackles the lack of trajectory data in near-accident scenarios using YOLOv5 and camera calibration methods. I see you consist of 170 near-accident occurrences in seven intersections in Cusco-Peru. This new dataset and pipeline code are available on Github.
翻译:在城市交通情况中,自发车辆的开发产生了新的挑战,在城市交通情况中,车辆-私家车的相互作用频繁发生,例如行人车辆的产量,行人因接近车辆而放慢速度。在过去几年中,已经开发了若干数据集来模拟这些相互作用。但是,现有的数据集并不涵盖我们数据集覆盖的近乎事故的假设。我们介绍你,这是一个新的车辆-私家车互动数据集,它利用YOLOv5和相机校准方法,解决近乎事故情况下缺乏轨道数据的问题。我看到你在库斯科-秘鲁七个交叉点建立了170个近乎事故事件。这个新的数据集和管道代码可以在Github上找到。