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New dataset tackles autonomous driving in flooded roads

By PulseAugur Editorial · [2 sources] ·

Researchers have introduced the Flooded Road Environments Dataset (FRED), the first multi-modal dataset designed for autonomous driving in flooded conditions. FRED includes synchronized data from cameras, LiDAR, and IMU sensors, captured across five locations during and after flood events. The dataset is released in KITTI-style and RTMaps formats, complete with semantic labels to facilitate the development and evaluation of water hazard detection systems. AI

IMPACT Enables development of specialized AI for autonomous vehicles to navigate hazardous flooded road conditions.

RANK_REASON The cluster describes a new academic dataset release for a specific research problem.

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

COVERAGE [2]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    FRED: A Multi-Modal Autonomous Driving Dataset for Flooded Road Environments

    The Flooded Road Environments Dataset (FRED) is, to our knowledge, the first multi-modal autonomous driving dataset specifically targeting the collection of data from scenarios involving water hazards on the road. The dataset contains images from a 2.3 MP FLIR Blackfly USB3 camer…

  2. arXiv cs.CV TIER_1 English(EN) · Connor Malone, Sebastien Demmel, Sebastien Glaser ·

    FRED: A Multi-Modal Autonomous Driving Dataset for Flooded Road Environments

    arXiv:2605.22018v1 Announce Type: new Abstract: The Flooded Road Environments Dataset (FRED) is, to our knowledge, the first multi-modal autonomous driving dataset specifically targeting the collection of data from scenarios involving water hazards on the road. The dataset contai…

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