无人驾驶算法模型训练路侧数据

通过自动驾驶示范区道路的路侧设备采集的场景数据，经过抽帧后的图片，用描述文件标注出其中的要素，如：小汽车、SUV、大巴车、摩托车、骑手、行人等要素，可用于无人驾驶算法模型训练，提高算法精准度。

This dataset consists of images obtained through frame sampling of scene data collected by roadside equipment deployed on roads within autonomous driving demonstration zones. These images are annotated with descriptive annotation files to identify key traffic elements such as cars, SUVs, buses, motorcycles, riders, pedestrians and other relevant traffic participants. It can be applied to the training of autonomous driving algorithm models to improve their detection accuracy.

搜集汇总

背景与挑战

背景概述

该数据集包含通过自动驾驶示范区道路的路侧设备采集的场景数据，经过抽帧处理形成图片，并配有描述文件标注出小汽车、SUV、大巴车、摩托车、骑手、行人等关键要素。这些数据专门用于无人驾驶算法模型的训练，旨在提升算法的识别精准度和性能。