400 human factors accidents and 1000 nonhuman factors accidents were analyzed using 30-day work histories of locomotive crews. Steven R. Hursh's report demonstrates a validated biomathematical fatigue model, finding a strong linear relationship (r = -0.93) between crew effectiveness and human factors accident risk. At an effectiveness score ≤ 50, human factors accidents were 65 percent more likely than chance.
Use Cases
- Validate fatigue prediction models based on work schedule data and sleep opportunities
- Calibrate safety thresholds for operator effectiveness scores mentioned in the report
- Analyze time-of-day variation in accident risk based on the reported correlation (r = 0.71)
- Compare human factors accident rates between day and night workers using the reported proportions (37% vs 27%)
Strengths
- Analysis includes 400 human factors accidents and 1000 nonhuman factors accidents
- Strong statistical relationships reported (r = -0.93 for effectiveness vs human factors risk)
- Model calibration includes concrete thresholds (e.g., effectiveness ≤ 50 increases risk by 65%)
Limitations
- Row count is 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
- Steven R. Hursh
- Collection Method
- Project examining 30-day work histories of locomotive crews prior to accidents