OSHA数据集

OSHA数据集是由加州大众创新中心创建的，专注于高速公路超车和车道变换问题。该数据集包含约900万个样本，包括车道图像和其他动态对象，用于模拟环境中的数据收集。数据集的创建过程涉及使用SimPilot模拟环境，并通过规则驱动的方法收集数据。OSHA数据集主要应用于自动驾驶领域，旨在解决高速公路上的超车和车道变换决策问题，提高车辆的自主性和安全性。

The OSHA dataset was developed by the California Mass Innovation Center, with a focus on highway overtaking and lane change-related scenarios. It contains approximately 9 million samples, including lane images and other dynamic objects, and is designed for data collection in simulated environments. The dataset's creation process leverages the SimPilot simulation environment and collects data through a rule-driven methodology. Primarily applied in the autonomous driving domain, the OSHA dataset aims to address decision-making challenges for highway overtaking and lane changes, thereby improving vehicle autonomy and safety.