This paper challenges the validity of vehicle-based Naturalistic Driving (ND) Safety Critical Events (SCEs) in relation to injury and fatal crashes. It asserts that mixed SCE datasets have no known or likely representativeness in relation to serious crashes and are likely invalid in regard to their causal factors. This argument is made in the context of ND attempts to associate truck driver Hours-of-Service parameters and safety. But the argument generally applies to other mixed SCE datasets. In part, the challenge is to a monolithic 'Heinrich Triangle'. Crashes are heterogeneous, both 'horizontally' within any severity strata and 'vertically' across strata. Serious crashes account for the vast majority of human harm, and are very different from minor crashes. Yet all crashes have, and are defined by, tangible external consequences. In contrast, SCEs are defined by driver maneuvers. Their datasets contain almost no crashes, let alone harm. As such, they are not properly part of the 'triangle'. Mixed SCE datasets are collections of multiple, disparate driver maneuvers chosen and defined by researchers. They are thus contrived, not analytically derived from the phenomenon of importance, serious crashes. No valid quantitative inferences about the genesis of crash harm can be made from such datasets. This deficiency does not invalidate all ND applications, however. And SCE and real crash datasets could be linked by systematic sampling and case weighting based on objective crash characteristics.(Author/publisher)
Abstract