Autonomous driving paper index
IROSCD: Indonesia Road Surface Classification Dataset
One-line summary
To address this gap, we introduce the Indonesia Road Surface Classification Dataset (IROSCD), a new dataset that captures real road conditions in Indonesia under four categories: Normal Road, Damaged Road, Bumpy Road, and Wet Road.
Engineering notes
The IROSCD dataset is expected to serve as a benchmark for further studies in intelligent transportation systems , road condition monitoring , and autonomous vehicle research , both within Indonesia and globally.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
Road surface condition is a critical factor in transportation safety, vehicle maintenance, and the development of intelligent transportation systems. Damaged, uneven, or wet road surfaces can increase the risk of accidents and reduce driving comfort. However, research on road surface classification in Indonesia remains limited due to the absence of a representative and realistic dataset reflecting local road conditions. To address this gap, we introduce the Indonesia Road Surface Classification Dataset (IROSCD), a new dataset that captures real road conditions in Indonesia under four categories: Normal Road, Damaged Road, Bumpy Road, and Wet Road. Each category includes typical visual characteristics such as cracks, potholes, bumps, and water puddles, collected from various regions across Indonesia. The IROSCD dataset is expected to serve as a benchmark for further studies in intelligent transportation systems , road condition monitoring , and autonomous vehicle research , both within Indonesia and globally.
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