Injury prediction for advanced automatic crash notification system

In order to improve the rescue efficiency of the advanced automatic crash notification (AACN) system,a driver injury prediction algorithm was proposed,and the overall design of the AACN system terminal was conducted based on this algorithm.First,the amount of speed change,the direction of the accident,the driver′s age,gender,whether to wear the seat belt,and whether the driver′s side airbag inflated were selected as the influencing factors of the driver′s injury.Next,a Logistic regression model was analyzed and developed based on traffic accident data.The effectiveness of the model was verified by using the Hosmer-Lemeshow test table,and the best trigger threshold was obtained through sensitivity analysis.Then,the AACN system terminal was designed.Finally,an actual case was used to test the accuracy of the injury prediction algorithm and the effectiveness of AACN system terminal.The results of the case study show that the proposed driver injury prediction algorithm and the AACN system are highly accurate,which can effectively predict the driver′s injury and help the rescue center work out an active rescue plan.The research results can be used to solve the problem that existing centralized AACN systems′ efficiency is not high and their accuracy is greatly affected by human factors.Consequently,they provide a reference for the design of driver injury prediction algorithm in the decentralized AACN system.