OVPD: Virtual-Physical Fusion Dataset for Autonomous Driving Testing

OVPD is a virtual-physical fusion testing dataset derived from the 2025 OnSite Autonomous Driving Challenge. It is organized at the clip level, with each clip corresponding to one complete test run from a participating team. The dataset was created by Yuhang253820 and was last updated on Hugging Face in May 2026.

Use Cases

• Testing planning algorithms based on virtual-physical fusion scenarios.
• Evaluating decision-making systems in complex interactive driving situations.
• Conducting replay-based analysis of autonomous driving test runs.
• Performing deployment-oriented evaluation of autonomous driving systems.

Strengths

• Derived from a specific 2025 autonomous driving challenge, providing a defined context.
• Organized at the clip level, with each clip representing a complete test run.
• Last updated on Hugging Face on 2026-05-08.

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

2025 OnSite Autonomous Driving Challenge.

Collection Method

Derived from test runs of participating teams.

Freshness

Last updated 2026-05-08 05:50:46; freshness should be verified.