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TitleA study on injury prediction for ACN vehicles based on speed limit - Development of an injury prediction algorithm using Australian accident data
AuthorsKubota K, Nishimoto T, Ponte G
Year2021
TypeJournal Article
AbstractIn this study, an injury prediction algorithm for vehicle occupants was developed based on the South Australian Traffic Accident Reporting System (TARS), a traffic accident database. The algorithm uses information that can be identified from the accident location or reported by bystanders (e.g., speed limit distance from the centre of Adelaide in SA, etc) as risk factors. The best combination of factors for injury prediction was selected from 15 items based on the Akaike Information Criteria (AIC). The algorithm had an under-triage rate of less than 10% for the serious injured and an overtriage rate of 45.1% for the minor injured. This algorithm can contribute to the reduction of the number of fatalities by helping Automatic Crash Notification (ACN) systems to operate as Advanced Automatic Crash Notification (AACN) systems, or to be used by emergency medical services in on-scene triage.
ISSN1883-0811
Journal TitleTransactions of Society of Automotive Engineers of Japan
Journal Volume (Issue)52(6)
Page Range1219-1226
NotesAvailable from https://doi.org/10.11351/jsaeronbun.52.1219

Article in Japanese

Reference
Kubota K, Nishimoto T, Ponte G (2021) 'A study on injury prediction for ACN vehicles based on speed limit - Development of an injury prediction algorithm using Australian accident data', Transactions of Society of Automotive Engineers of Japan, 52(6), pp 1219-1226.