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 a complete test run from a participating team. The dataset was created by Yuhang253820 and was last updated on May 8, 2026.
Use Cases
- Planning algorithm testing based on virtual-physical fusion scenarios.
- Decision-making model evaluation based on complex interactive driving clips.
- Replay-based analysis of autonomous driving test runs.
- Deployment-oriented performance benchmarking for autonomous driving systems.
Strengths
- Dataset is derived from a specific challenge event, the 2025 OnSite Autonomous Driving Challenge.
- Data is organized at the clip level, with each clip representing a complete test run.
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 is unknown, which may limit suitability assessment.
Provenance
- Source
- Yuhang253820
- Collection Method
- Derived from the 2025 OnSite Autonomous Driving Challenge.
- Freshness
- Last updated 2026-05-08 05:50:46; freshness should be verified.