Proceedings of the National Academy of Sciences· 2016Q1
Driver crash risk factors and prevalence evaluation using naturalistic driving data
- 1,026citations
- Q1SCImago
- 2016year
Short summary
Driver-related factors like error, impairment, fatigue, and distraction are present in nearly 90% of crashes, a significant shift in recent years. Handheld electronic devices are a major contributor to distraction and increased risk.
AI-generated from the title and abstract; the full text is not read.
Key points
- Driver-related factors are present in almost 90% of injurious and property damage crashes.
- Crash causation has shifted dramatically towards driver error, impairment, fatigue, and distraction.
- Distraction from handheld electronic devices is a significant risk factor.
- The study analyzed a dataset of 905 crash events.
AI-generated from the title and abstract; the full text is not read.
Abstract
The accurate evaluation of crash causal factors can provide fundamental information for effective transportation policy, vehicle design, and driver education. Naturalistic driving (ND) data collected with multiple onboard video cameras and sensors provide a unique opportunity to evaluate risk factors during the seconds leading up to a crash. This paper uses a National Academy of Sciences-sponsored ND dataset comprising 905 injurious and property damage crash events, the magnitude of which allows the first direct analysis (to our knowledge) of causal factors using crashes only. The results show that crash causation has shifted dramatically in recent years, with driver-related factors (i.e., error, impairment, fatigue, and distraction) present in almost 90% of crashes. The results also definitively show that distraction is detrimental to driver safety, with handheld electronic devices having high use rates and risk.
The authors' abstract, as published at the source. Proceedings of the National Academy of Sciences, 2016 · DOI ↗
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Field: Safety, Risk, Reliability and Quality
Safety, Risk, Reliability and QualityEngineering