Document Detail

Quasi-induced exposure: methodology and insight.
MedLine Citation:
PMID:  9110039     Owner:  NLM     Status:  MEDLINE    
Even though the numerator in accident rates can be accurately determined nowadays, the denominator of these rates is an item of discussion and debate within the highway safety community. A critical examination of an induced exposure technique, based on the non-responsible driver/vehicle of a two-vehicle accident (quasi-induced exposure), is presented here. Differences in exposure for a series of accident location and time combinations are investigated, the assumption of similarities between drivers of single-vehicle accidents and the responsible driver of multiple-vehicle accidents is refuted, and the use of the non-responsible driver as a measure of exposure is tested using vehicle classification data. The results of the analyses reveal the following: (1) accident exposure is different for different location and time combinations: (2) induced exposure estimates provide an accurate reflection of exposure to multiple-vehicle accidents; (3) induced exposure estimates are acceptable surrogates for vehicle miles of travel when estimates are made for conditions during which the mix of road users is fairly constant; and (4) the propensity for involvement in single-vehicle accidents is generally different than that in multiple-vehicle accidents for a given class of road users. We concluded that the quasi-induced exposure is a powerful technique for measuring relative exposure of drivers or vehicles when real exposure data are missing.
N Stamatiadis; J A Deacon
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Accident; analysis and prevention     Volume:  29     ISSN:  0001-4575     ISO Abbreviation:  Accid Anal Prev     Publication Date:  1997 Jan 
Date Detail:
Created Date:  1997-05-07     Completed Date:  1997-05-07     Revised Date:  2004-11-17    
Medline Journal Info:
Nlm Unique ID:  1254476     Medline TA:  Accid Anal Prev     Country:  ENGLAND    
Other Details:
Languages:  eng     Pagination:  37-52     Citation Subset:  IM    
Department of Civil Engineering, University of Kentucky, Lexington 40506-0281, USA.
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MeSH Terms
Accidents, Traffic / statistics & numerical data*
Analysis of Variance
Automobile Driving / statistics & numerical data*
Likelihood Functions
Middle Aged

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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