This paper summarizes the initial findings from a database of crashes that involved BMW cars equipped with Automatic Crash Notification (ACN) Systems in the US and Germany. In addition, first field experiences with BMW's enhanced ACN systems are reported where vehicles not only provide an initial crash notification but also transmit data describing the nature and severity of the collision event. The benefits of such a system, including therapid recognition of potentially injured occupants based on key characteristics of each crash, are explored. Since 2006, nearly 14,000 BMW crashes have occurred in the US involving vehicles equipped with ACN or enhanced ACN technology. Of these, 70% of occupants indicate no injury to the TSP (Telematics Service Provider) operators, 20% indicate they are injured in some way and require help while 10% provide no verbal response to the TSP call-taker. An investigation of a subsample of crashes occurring in Florida suggests that no hospital transport was necessary for 81% of the calls where no voice response occurred. Although the majority of these cases require no further care, 19% of the no voice population was subsequently transported to a hospital or trauma center for additional care. This population of occupants could benefit from an automatic call for help to a Public Services Answering Point (PSAP, commonly known as 911) that includes an estimate of the likelihood of serious injuries. To assist in identifying crasheswith incapacitating injuries, the William Lehman Injury Research Center (WLIRC) in Miami, Florida and BMW have pioneered the development of an algorithm called URGENCY. This algorithm is based on US national crash statistics and BMW internal data. The injury prediction by URGENCY permits the transmission of the earliest and best information to the PSAP. Early observations of injury severity and location are reported for enhanced ACN equipped vehicle crashes occurring in the USA and Germany. The full text of thispaper may be found at:ûhttp://www-nrd.nhtsa.dot.gov/pdf/esv/esv21/09-0049.pdf For the covering abstract see ITRD E145407.
Abstract