A field operational test of an early prototype Drowsy Driver Warning System was conducted by the National Highway Traffic Safety Administration and the Federal Motor Carrier Safety Administration. The final dataset for analysis consisted of 102 drivers from 3 for-hire trucking fleets using 46 instrumented trucks, containing nearly 12.4 terabytes of truck instrumentation, kinematic data, and video recordings for 2.4 million miles of driving. This dataset is described as the largest ever collected by the U.S. Department of Transportation.
Use Cases
- Evaluating the safety benefits of drowsiness detection systems based on driver performance metrics.
- Analyzing driver acceptance and opinion of in-cab warning systems based on survey and behavioral data.
- Developing novel data reduction and analysis procedures for large-scale, multimodal field operational test data.
- Comparing drowsiness levels and safety outcomes between control and test groups of commercial drivers.
Strengths
- Dataset scale is substantial, with nearly 12.4 terabytes of data from 2.4 million miles and 48,000 hours of driving.
- Data collection involved 102 drivers and 46 instrumented trucks from three commercial fleets, providing real-world operational context.
- The study addressed 53 specific research questions related to safety, acceptance, and deployment.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Last update date is unknown; freshness unverified.
- Row count and specific file formats are unknown, which may limit suitability assessment.
Provenance
- Source
- National Highway Traffic Safety Administration and Federal Motor Carrier Safety Administration
- Collection Method
- Field operational test conducted with instrumented trucks across three for-hire trucking fleets.
- Geography
- United States (inferred from involvement of U.S. Department of Transportation agencies)