Relationships Between Crash Casualties and Crash Attributes

Format:

Conference/Event

Author/Creator:

Malliaris, A. C., author.

Conference Name:

SAE International Congress & Exposition (1997-02-24 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 1997

Summary:

This work addresses and evaluates the likelihood of human casualty in highway crashes, projected on the basis of field crash data that may become available electronically by sensors at crash time, and/or observed at the crash scene by emergency attendants. Termed collectively as a "crash signature", such data are treated as predictors and are selected from: crash severity, general area of damage, direction of force, occurrence of rollover, intrusion, vehicle crush and its specific horizontal location, collision partner, vehicle class and size, occupant age, gender, restraint use and type, seating position, and other. Crash signatures are converted into responses such as: (a) the likelihood of the most severe outcome, fatality or survived injury, by severity AIS per occupant; and (b) the same per vehicle. Cars are the vehicles selected for this investigation. A likelihood is quantified by a probability of occurrence, as a function of a string of predictors selected for maximum resolution and sensitivity, and minimum contribution to error. Likelihood determinations are performed via maximum likelihood based logistic regressions, best suited for treating dichotomous responses: "yes or no" such and such a response or outcome. Each likelihood is accompanied by a standard error or by upper and lower confidence bounds, and each procedure is evaluated by pertinent scores. All cited procedures and findings are based on the data of the National Accident Sampling System (NASS) files 1988-1995, compiled by the National Highway Traffic Safety Administration (NHTSA). This provides a nationally representative sample of about 95,000 crash involved car occupants, and 190,000 incurred injuries, all with attributes that collectively encompass as a minimum the predictors and responses cited earlier. The paper provides pertinent predictive relations which, notwithstanding complexity, are fully programmable. Probabilities of specific outcomes may vary from nearly zero to virtually 100%, depending on circumstances. Detailed and illustrative findings are presented in tabular and graphic forms

Notes:

Vendor supplied data

Publisher Number:

970393

Access Restriction:

Restricted for use by site license