CarlaVSP

该数据集名为CarlaVSP，旨在模拟多样的驾驶风格和车型，以实现对车辆速度的高精度预测。它包含了在都市模拟环境中，不同驾驶员驾驶各类车辆时所收集的数据，涵盖了内部控制信息和视觉数据。与其他现有驾驶数据集相比，该数据集的独特之处在于其包含了驾驶员和车型标签，这使得它在自动驾驶个性化应用方面具有实用价值。该数据集的规模涉及十名志愿者驾驶三种不同类型车辆的数据，其任务是对车辆速度进行预测。

This dataset, named CarlaVSP, is designed to simulate diverse driving styles and vehicle types to enable high-precision vehicle speed prediction. It collects data from different drivers operating various vehicles in an urban simulation environment, covering both internal vehicle control information and visual data. Compared with other existing driving datasets, the distinct advantage of CarlaVSP is that it includes driver and vehicle type labels, which grants it practical value for personalized autonomous driving applications. The dataset encompasses data from ten volunteers driving three different types of vehicles, with the core task being vehicle speed prediction.