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 accide...
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Hebei University of Science and Technology
2021
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oai:doaj.org-article:842bde32de914678a686f3edbbb6ede02021-11-23T07:08:58ZInjury prediction for advanced automatic crash notification system1008-154210.7535/hbkd.2021yx04002https://doaj.org/article/842bde32de914678a686f3edbbb6ede02021-08-01T00:00:00Zhttp://xuebao.hebust.edu.cn/hbkjdx/ch/reader/create_pdf.aspx?file_no=b202104002&flag=1&journal_https://doaj.org/toc/1008-1542In 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.Ying LUYufa LIUYu SHUXiaojie JIHebei University of Science and Technologyarticleother subjects of highway transportation; road accident data; logistic regression model; driver injury prediction model; the advanced automatic crash notification systemTechnologyTZHJournal of Hebei University of Science and Technology, Vol 42, Iss 4, Pp 327-333 (2021) |
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ZH |
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other subjects of highway transportation; road accident data; logistic regression model; driver injury prediction model; the advanced automatic crash notification system Technology T |
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other subjects of highway transportation; road accident data; logistic regression model; driver injury prediction model; the advanced automatic crash notification system Technology T Ying LU Yufa LIU Yu SHU Xiaojie JI Injury prediction for advanced automatic crash notification system |
| description |
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. |
| format |
article |
| author |
Ying LU Yufa LIU Yu SHU Xiaojie JI |
| author_facet |
Ying LU Yufa LIU Yu SHU Xiaojie JI |
| author_sort |
Ying LU |
| title |
Injury prediction for advanced automatic crash notification system |
| title_short |
Injury prediction for advanced automatic crash notification system |
| title_full |
Injury prediction for advanced automatic crash notification system |
| title_fullStr |
Injury prediction for advanced automatic crash notification system |
| title_full_unstemmed |
Injury prediction for advanced automatic crash notification system |
| title_sort |
injury prediction for advanced automatic crash notification system |
| publisher |
Hebei University of Science and Technology |
| publishDate |
2021 |
| url |
https://doaj.org/article/842bde32de914678a686f3edbbb6ede0 |
| work_keys_str_mv |
AT yinglu injurypredictionforadvancedautomaticcrashnotificationsystem AT yufaliu injurypredictionforadvancedautomaticcrashnotificationsystem AT yushu injurypredictionforadvancedautomaticcrashnotificationsystem AT xiaojieji injurypredictionforadvancedautomaticcrashnotificationsystem |
| _version_ |
1718416837903908864 |