Global Collaboration Seeking worldwide partners
We invite global collaborators to jointly develop fusion datasets for autonomous driving and intelligent chassis, and algorithms for dataset development and utilization.
- Real-vehicle data collection and closed-loop verification platform
- In-house server: 8× NVIDIA RTX 5090 GPUs
- Broad industry partnerships for validation and deployment
We are recruiting interns in computer science, with a stipend of 100–300 RMB per day and support for industry and academic recommendations.
Interested in co-development, data partnership, or internships? Contact us
Sensor Configuration
- 5× Surround RGB cameras (front-left, front-right, rear-left, rear-right, rear-center)
- ZED 2i Stereo camera — left + right RGB with per-frame dense depth maps (.npy)
- LiDAR Forward-facing LiDAR point clouds (.npy) per frame
- GNSS High-precision GPS: north/east velocity, absolute heading, centimeter-level positioning
- Chassis Speed, yaw rate, raw IMU (X/Y acceleration) — direct side-slip angle derivation
Select a scene category to explore. Each episode contains fully synchronized multi-sensor streams — surround RGB, ZED stereo + depth, LiDAR, and vehicle dynamics — resampled to a uniform 4 Hz grid.
Scene Demos
Synchronized multi-sensor recordings across all scene categories. Select a category and clip to preview.
Team
Intelligent Chassis Team · School of Vehicle and Mobility, Tsinghua University
Shiyue Zhao · Yuhong Jiang · Xinhan Li · Chengkun He · Junzhi Zhang
Citation
@misc{extreme_driving_dataset_2026,
title = {Extreme Driving Dataset: Multi-Modal Episodes
for Critical and Adverse-Condition Driving},
author = {Shiyue Zhao and Yuhong Jiang and Xinhan Li
and Chengkun He and Junzhi Zhang},
howpublished = {Intelligent Chassis Team, School of Vehicle
and Mobility, Tsinghua University},
year = {2026}
}