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Update README.md

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  - 3D bounding box annotations for all objects
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  - **Key Statistics:**
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- - 12,858 instances
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- - 254,436 ego poses
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- - 225,085 total annotations
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  ---
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  - Built upon the **nuScenes validation set** (150 scenes)
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  - Uses nuScenes’ original sensor data and annotations as foundation
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  ### Filtering
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  Scenarios are filtered to ensure:
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  - No collisions between adversarial and other vehicles
 
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  - 3D bounding box annotations for all objects
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  - **Key Statistics:**
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+ - 10538 instances
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+ - 247,548 ego poses
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+ - 184,209 total annotations
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  ---
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  - Built upon the **nuScenes validation set** (150 scenes)
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  - Uses nuScenes’ original sensor data and annotations as foundation
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+ ### Source Data
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+ - 1.**Potential Risk Monitoring and Detection**: Obtain the consecutive segments with the highest potential risk by using the sliding window method and evaluate the vehicle with the greatest potential risk to the ego.
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+ - 2.**Trajectory Generation**: The two-stage "decision-making + control" strategy is utilized to control the agent to perform risky behaviors on the ego vehicle while ensuring compliance with driving regulations.
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+ - 3.**Neural Rendering**: Produces photorealistic multiview videos using MagicDrive-V2
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+
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  ### Filtering
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  Scenarios are filtered to ensure:
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  - No collisions between adversarial and other vehicles