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README.md
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- 3D bounding box annotations for all objects
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- **Key Statistics:**
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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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### 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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