title: Estimation of the severity of safety critical events.
abstract: Today, various measures are used to estimate the severity of a traffic conflict. However, these measures are all limited to estimating the crash risk and do not include any estimates of the possible consequences of a potential crash. In accident analysis the estimated severity of the event is related to the outcome of the crash, such as injury levels. This article proposes a new method for estimating the severity of safety critical events based on both an estimate of crash risk and an estimate of possible consequence that, in addition to a measure of safety margins, takes vehicle mass as well as the relative speed of the involved road users into consideration. The article compares the estimated severity of 61 conflicts and 9 accidents of the proposed method with the traffic conflict technique. The results from the severity estimates of our proposed method show a significant difference in the severity levels of events involving vehicles with similar mass compared to critical events involving vehicles with dissimilar mass and events involving pedestrians. The proposed method gives the possibility to compare different conflicts, with regard to severity, with each other regardless of what type of conflict it is, e.g. intersection or rural road, or what kind of road users that are involved. In addition, an event classification, i.e. serious or very serious event, based on the severity estimate of the proposed method, shows promising results indicating that the severities are estimated in a homogenous way. The article concludes that our proposed method of estimating the severity of critical event seems to be able to reflect the dangerousness in a more realistic way than the traffic conflict technique and should facilitate the development of traffic safety analysis methods.
authors.affiliation: VTI, Swedish National Road and Transport Research Institute, PO Box 920, SE-781 29 Borlänge, Sweden. omar.bagdadi@vti.se
authors.forename: Omar
authors.initials: O
authors.lastname: Bagdadi
mesh_terms: D000054:Acceleration; D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D001334:Automobile Driving; D006801:Humans; D015601:Injury Severity Score; D011237:Predictive Value of Tests; D012307:Risk Factors; D012449:Safety