Research on Vehicle-Based Drowsy Driver Detection and Countermeasures

NHTSA-supported research investigates driver drowsiness as a cause of traffic crashes. The work focuses on developing in-vehicle systems to monitor driver alertness and performance. The dataset likely contains research findings and metrics supporting the feasibility of this countermeasure concept.

Use Cases

• Training models for driver alertness classification based on described performance metrics.
• Analyzing correlations between drowsiness indicators and crash risk mentioned in the research.
• Developing prototype in-vehicle monitoring systems based on the described countermeasure concept.
• Benchmarking drowsiness detection algorithms against the research's scientific support.

Strengths

• Research is supported by NHTSA as part of its IVHS/human factors program.
• Focuses on a major, though elusive, cause of traffic crashes.
• Provides scientific support for the feasibility of in vehicle countermeasure systems.

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, file formats, and last update date are unknown.

Provenance

Source

R R Knipling via paperswithcode.

Collection Method

Research conducted as part of the NHTSA IVHS/human factors program.

Time Range

Temporal coverage is unknown.

Freshness

Last update date is unknown; freshness unverified.

Geography

Spatial coverage is unknown.