Driving Scenarios Dataset

该数据集包含了多种交通场景，用于在各类城市、乡村和高速公路环境中训练和评估自动驾驶策略。该数据集的特点是拥有复杂的地图，其中包括随机分布的车辆和行人，旨在评估自动驾驶技术在不同场景下的表现。其规模宏大，包含24万个训练样本，16,800个情节，覆盖了7,102公里的路程。该数据集的任务是针对自动驾驶车辆的导航和决策制定进行研究和改进。

This dataset contains diverse traffic scenarios, designed for training and evaluating autonomous driving strategies across various urban, rural and highway environments. It features complex maps populated with randomly distributed vehicles and pedestrians, aiming to evaluate the performance of autonomous driving technologies across different scenarios. It boasts a large-scale dataset corpus, consisting of 240,000 training samples, 16,800 driving episodes, and covering a total driving distance of 7,102 kilometers. The core task of this dataset is to conduct research and improve the navigation and decision-making capabilities of autonomous vehicles.