Validation of not-at-fault driver representativeness assumption for quasi-induced exposure using U.S. national traffic databases

•Quasi-induced exposure (QIE) method assumes not-at-fault drivers in a crash represent the driving population.•The QIE representativeness was tested using Fatality Analysis Reporting System (FARS) and National Occupant Protection Use Survey (NOPUS).•The other not-at-fault drivers excluding the first...

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Veröffentlicht in:Journal of safety research 2019-12, Vol.71, p.243-249
Hauptverfasser: Shen, Sijun, Pope, Caitlin N., Stamatiadis, Nikiforos, Zhu, Motao
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Sprache:eng
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Zusammenfassung:•Quasi-induced exposure (QIE) method assumes not-at-fault drivers in a crash represent the driving population.•The QIE representativeness was tested using Fatality Analysis Reporting System (FARS) and National Occupant Protection Use Survey (NOPUS).•The other not-at-fault drivers excluding the first not-at-fault drivers in three-or-more vehicle crashes (D3_other) in FARS did not differ from observed drivers in NOPUS.•D3_other drivers in FARS represents the driving population at the time of crash. Introduction:The quasi-induced exposure (QIE) method has been widely implemented into traffic safety research. One of the key assumptions of QIE method is that not-at-fault drivers represent the driving population at the time of a crash. Recent studies have validated the QIE representative assumption using not-at-fault drivers from three-or-more vehicle crashes (excluding the first not-at-fault drivers; D3_other) as the reference group in single state crash databases. However, it is unclear if the QIE representativeness assumption is valid on a national scale and is a representative sample of driving population in the United States. The aims of this study were to assess the QIE representativeness assumption on a national scale and to evaluate if D3_other could serve as a representative sample of the U.S. driving population. Method: Using the Fatality Analysis Reporting System (FARS) and the National Occupant Protection Use Survey (NOPUS), distributions of driver gender, age, vehicle type, time, and roadway type among the not-at-fault drivers in clean two-vehicle crashes, the first not-at-fault drivers in three-or-more-vehicle crashes, and the remaining not-at-fault drivers in three-or-more vehicle crashes were compared to the driver population observed in NOPUS. Results: The results showed that with respect to driver gender, vehicle type, time, and roadway type, drivers among D3_other did not show statistical significant difference from NOPUS observations. The age distribution of D3_other driver was not practically different to NOPUS observations. Conclusions: Overall, we conclude that D3_other drivers in FARS represents the driving population at the time of the crash. Practical applications: Our study provides a solid foundation for future studies to utilize D3_other as the reference group to validate the QIE representativeness assumption and has potential to increase the generalizability of future FARS studies.
ISSN:0022-4375
1879-1247
DOI:10.1016/j.jsr.2019.09.024