A More Effective Post-Crash Safety Feature to Improve the Medical Outcome of Injured Occupants

Automatic Crash Notification (ACN) technology provides an opportunity to rapidly transmit crash characteristics to emergency care providers in order to improve timeliness and quality of care provided to occupants in the post crash phase. This study evaluated the relative value of crash attributes in providing useful information to assist in the identification of crashes where occupants may be seriously injured. This identification includes an indication of whether a crash is likely to require a level of emergency response with higher priority than is needed for most crashes reported by ACN Systems. The ability to predict serious injury using groupings of variables has been determined. In this way, the consequence of not transmitting each variable can be estimated. In addition, the incremental benefit of voice communication is shown.

The crash variables evaluated using regression analysis were: deltaV, impact direction, presence of the right front passenger, knowledge of three point belt usage in front seats and the recognition of multiple impact crash events. The analysis showed that each added variable improved the ability to identify and capture crashes with serious and fatal injuries. However, the extent of over-triage remained fairly constant at around 20%. The use of voice communications to identify cases without injury in low severity crashes could substantially reduce the over-triage rate.