Road Surface Image Dataset with Detailed Annotations for Driving Assistance

The preview of the road surface states is essential for improving the safety and the ride comfort of autonomous vehicles. This dataset consists of 1 million (240 x 360 pixels) road surface images captured under a wide range of road and weather conditions in China. The original pictures are acquired with a vehicle-mounted camera and then the patches containing only the road surface area are cropped. The images are classified into 27 categories, containing both the friction level, material, and unevenness properties. This large-scale dataset is useful for developing vision-based road sensing modules to improve the performance of the driving assistance systems.路面状态预判对于提升自动驾驶车辆的行驶安全性与乘坐舒适性至关重要。本数据集包含100万张分辨率为240×360像素的路面图像，采集自中国境内多种道路与气象条件场景。原始图像由车载摄像头采集，随后裁剪出仅包含路面区域的图像块。该数据集的图像被划分为27个类别，涵盖路面摩擦等级、路面材质与路面不平整性三类属性。该大规模数据集可用于开发基于视觉的路面感知模块，以提升驾驶辅助系统的性能。