{"title":"运动型多功能车的实时侧翻威胁指数","authors":"Bo-Chiuan Chen, H. Peng","doi":"10.1109/ACC.1999.783564","DOIUrl":null,"url":null,"abstract":"The methodology capable of computing a time-to-rollover (TTR) index in real-time is verified by using test data of two sports-utility vehicles (SUV)-a 1988 Suzuki Samurai and a 1997 Jeep Cherokee. First, simple yaw-roll models are constructed based on the test data. The TTR is computed from the simple model and then corrected by using an artificial neural network. The TTR generated by the neural network is then verified against the data for the two test vehicles.","PeriodicalId":441363,"journal":{"name":"Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251)","volume":"42 4","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"73","resultStr":"{\"title\":\"A real-time rollover threat index for sports utility vehicles\",\"authors\":\"Bo-Chiuan Chen, H. Peng\",\"doi\":\"10.1109/ACC.1999.783564\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The methodology capable of computing a time-to-rollover (TTR) index in real-time is verified by using test data of two sports-utility vehicles (SUV)-a 1988 Suzuki Samurai and a 1997 Jeep Cherokee. First, simple yaw-roll models are constructed based on the test data. The TTR is computed from the simple model and then corrected by using an artificial neural network. The TTR generated by the neural network is then verified against the data for the two test vehicles.\",\"PeriodicalId\":441363,\"journal\":{\"name\":\"Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251)\",\"volume\":\"42 4\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-06-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"73\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACC.1999.783564\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACC.1999.783564","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A real-time rollover threat index for sports utility vehicles
The methodology capable of computing a time-to-rollover (TTR) index in real-time is verified by using test data of two sports-utility vehicles (SUV)-a 1988 Suzuki Samurai and a 1997 Jeep Cherokee. First, simple yaw-roll models are constructed based on the test data. The TTR is computed from the simple model and then corrected by using an artificial neural network. The TTR generated by the neural network is then verified against the data for the two test vehicles.