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Japan Autonomous Driving Multi-Sensor Dataset – Labeled Camera, LiDAR & Sensor Fusion Data for ADAS

self driving car dataset
automotive AI training dataset
ADAS dataset
vehicle perception dataset
lane detection dataset
autonomous driving dataset japan

This Japan autonomous driving dataset is a high-precision multi-sensor annotated driving dataset collected from real-world vehicles in Japan. This dataset can be used for object detection and tracking, lane recognition, HD map construction, and autonomous driving algorithm validation. It is suitable for training deep learning models in complex real-world traffic environments.

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SpecificationsSpecifications
Objective
To build a multi-sensor annotated dataset in Japan for R&D scenarios related to autonomous driving, ADAS, environmental perception, object tracking, and high-definition (HD) maps.
Data collection equipment
Collected via a real vehicle platform in Japanese road environments, with sensors including LiDAR, RGB cameras, RTK/GNSS, IMU, and CAN bus (wheel speed).
Collection scenarios
Urban roads and their adjacent coastal road scenes in Japan, primarily under real daytime traffic conditions and mainly on sunny days.
Collection content
LiDAR point clouds, 6-view synchronized RGB images, RTK/GNSS, IMU, and vehicle speed information.
Annotation content
2D traffic sign annotation, 3D object tracking annotation, and 4D lane line annotation.
Application scenarios
Can be used for perception model training, object tracking, lane recognition, map construction, algorithm verification, and other scenarios.
2Dinformation
189 clips / 2,301 frames / 4,893 boxes
3Dinformation
258 clips / 10,320 frames / 195,782 boxes
4Dinformation
251 clips / 132.373kilometer
Sample Sample
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