The efficiency of using non-culpable crash-claim involvements from insurance data as a means of estimating travel exposure for road user sub-groups.
BACKGROUND
Induced exposure has a long history of development and usage in traffic safety research but a major question has always concerned the extent to which the accumulation of culpable and non-culpable involvements can be considered independent.


METHODS
Culpability assessments of 32,630 vehicles' crash-claim involvements adjudicated by insurance adjusters were matched with vehicle odometer readings taken at emission testing using consistent identification of vehicles and principal operators over a 5-year period.


RESULTS
It was found that the accumulation of culpable crash involvements was not entirely independent of that for non-culpable involvements. However, the rate of non-culpable involvements was determined to be an acceptable surrogate for travel exposure rate where sample sizes were large.


CONCLUSIONS
The relationship between the rate of non-culpable involvements and the rate of travel exposure for data subsets when both were normalized by the overall sample rates was reminiscent of an accident-volume curve for roadway locations in traffic engineering theory. This suggested that only a portion of non-culpable involvements actually related directly to travel and this lead to a correction factor that could be applied.


CONCLUSIONS
While lack of independence of involvement rates may be problematic for a direct risk ratio application, it does not invalidate the use of non-culpable involvements to predict travel. For insurers that have a need to estimate travel amounts for different driver/vehicle groups as part of the insurance rating purposes, this can be a useful application.
Cooper
Peter J
PJ
Insurance Corporation of British Columbia, North Vancouver, B.C. Canada.
Meckle
Wayne
W
Andersen
Linda
L
D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D000293:Adolescent; D000328:Adult; D000368:Aged; D001334:Automobile Driving / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D007344:Insurance Claim Reporting; D008297:Male; D008875:Middle Aged; D018986:Motor Vehicles / Q000706:statistics & numerical data*; D016017:Odds Ratio; D011336:Probability; D012044:Regression Analysis; D018570:Risk Assessment / Q000379:methods*; D014195:Travel / Q000706:statistics & numerical data; D055815:Young Adult