Driving Behaviour Multimodal Human Factors Eye Tracking Dataset

A multimodal dataset focused on driving behavior and human factors, likely containing eye-tracking data. It was authored by Xiaoming Tao and is available via the paperswithcode platform under an Open Access (green) license. The specific scale, collection period, and detailed contents are not provided in the available metadata.

Use Cases

• Train models for driver attention prediction based on eye-tracking data.
• Analyze correlations between visual behavior and driving performance.
• Develop multimodal systems for assessing driver cognitive load.
• Benchmark algorithms for human factors analysis in simulated or real driving environments.

Strengths

• Dataset is multimodal, combining eye-tracking with other behavioral signals.
• Available under an Open Access (green) license, facilitating reuse.

Limitations

• Row count and dataset scale are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

Xiaoming Tao