1008-1542 article 面向高級車輛事故自動呼救系統的傷情預測 Injury Prediction for Advanced Automatic Crash Notification System 高級車輛事故自動呼救(Advanced Automatic Crash Notification,AACN)系統能在車輛發生碰撞事故時及時根據駕駛員傷情預測算法預測車內駕駛員傷情,有助于救援中心做出早期判斷并制定積極有效的救援方案,從而提高救援效率,挽救更多重傷駕駛員的生命。選取速度變化量、事故碰撞方向、駕駛員年齡、性別、是否佩戴安全帶以及駕駛員側安全氣囊是否打開作為引起駕駛員傷情的影響因素;利用道路事故數據分析并構建Logistic回歸模型,使用Hosmer-Lemeshow測試表驗證了模型的有效性,并通過敏感性分析獲得了最佳觸發閾值。然后,提出了一種駕駛員傷害預測算法,并基于該算法實現了AACN系統終端的總體設計。最后,通過一個實際案例來檢驗傷情預測算法的準確性。結果表明,提出的駕駛員傷情預測算法準確率較高,能夠有效預測駕駛員傷情,也提高了AACN系統的準確性。 When a vehicle collision occurs, the Advanced Automatic Crash Notification (AACN) system can predict the driver’s injury in the vehicle based on the driver’s injury prediction algorithm. It helps the rescue center make early judgments as well as positive and effective decisions, which improves rescue efficiency and saves more lives of seriously injured drivers. First, by selecting 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 as the influencing factors of the driver’s injury, a Logistic regression model was analyzed and built based on road accident data. Next, 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, a driver injury prediction algorithm was proposed, and the overall design of the AACN system terminal was realized based on this algorithm. Finally, an actual case was used to test the accuracy of the injury prediction algorithm. The results of the case study show that the proposed driver injury prediction algorithm has a high accuracy rate, can effectively predict the driver’s injury, and improve the accuracy of the AACN system. 公路運輸其他學科;道路事故數據;Logistic回歸模型;駕駛員傷情預測模型;高級車輛事故自動呼救系統 other subjects of highway transportation; road accident data; logistic regression model; driver injury prediction model; the advanced automatic crash notification system 陸穎,劉裕發,束瑜,季小潔 Liu Yufa,Shu Yu,Ji Xiaojie 1.江蘇大學;2.鎮江市第四人民醫院 1.Jiangsu University;2.The Fourth Affiliated People’s Hospital hbkjdx/article/abstract/QB202103310081
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