DriveMRP-10K: A Synthesized High-Risk Motion Dataset for Autonomous Driving

DriveMRP-10K is a large-scale, synthesized multimodal dataset designed for training and evaluating motion risk prediction models in autonomous driving. It is the official dataset accompanying the paper 'DriveMRP: Enhancing Vision–Language Motion Risk Prediction via Controllable High-Risk Motion Synthesis' and was last updated on 2026-04-02.

Use Cases

• Training motion risk prediction models based on synthesized high-risk motion data.
• Evaluating model performance on controllable high-risk scenarios.
• Developing multimodal (vision-language) systems for autonomous driving safety.

Strengths

• Large-scale dataset designed for a specific, high-impact task.
• Synthesized data likely enables controlled generation of high-risk scenarios.
• Multimodal nature supports vision-language model development.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and file formats are unknown, which may limit suitability assessment.

Provenance

Source

Author SII-HZY, associated with the paper 'DriveMRP: Enhancing Vision–Language Motion Risk Prediction via Controllable High-Risk Motion Synthesis'.

Collection Method

Synthesized data generation for high-risk motion scenarios.

Time Range

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Freshness

Last updated 2026-04-02 16:16:21; freshness should be verified.

Geography

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