{"title":"先进驾驶辅助系统空间记忆的使用:防止固定ACC误报","authors":"H. Deusch, R. Graf, M. Fritzsche, K. Dietmayer","doi":"10.1109/IVS.2013.6629644","DOIUrl":null,"url":null,"abstract":"This paper presents a self-learning spatial memory approach for advanced driver assistance systems. The storage concept for this memory is based on an object relational data base with support for spatial queries. This memory component is applied to the problem of stationary false alarms of an adaptive cruise control system. Test results which demonstrate the practicality of this approach are also provided. Furthermore, an evaluation for different weather conditions is presented.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"27 21","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The use of spatial memory for advanced driver assistance systems: Preventing stationary ACC false alarms\",\"authors\":\"H. Deusch, R. Graf, M. Fritzsche, K. Dietmayer\",\"doi\":\"10.1109/IVS.2013.6629644\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a self-learning spatial memory approach for advanced driver assistance systems. The storage concept for this memory is based on an object relational data base with support for spatial queries. This memory component is applied to the problem of stationary false alarms of an adaptive cruise control system. Test results which demonstrate the practicality of this approach are also provided. Furthermore, an evaluation for different weather conditions is presented.\",\"PeriodicalId\":251198,\"journal\":{\"name\":\"2013 IEEE Intelligent Vehicles Symposium (IV)\",\"volume\":\"27 21\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE Intelligent Vehicles Symposium (IV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IVS.2013.6629644\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE Intelligent Vehicles Symposium (IV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IVS.2013.6629644","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The use of spatial memory for advanced driver assistance systems: Preventing stationary ACC false alarms
This paper presents a self-learning spatial memory approach for advanced driver assistance systems. The storage concept for this memory is based on an object relational data base with support for spatial queries. This memory component is applied to the problem of stationary false alarms of an adaptive cruise control system. Test results which demonstrate the practicality of this approach are also provided. Furthermore, an evaluation for different weather conditions is presented.