{"title":"限速确定中多传感器dempster-shafer融合的冲突管理","authors":"Jérémie Daniel, Jean-Philippe Lauffenburger","doi":"10.1109/IVS.2011.5940398","DOIUrl":null,"url":null,"abstract":"This paper deals with a Speed Limit Determination Advanced Driver Assistance System (ADAS) performing the combination of a navigation system and a Speed Limit Sign Recognition System (SLSR). The present strategy is based on a multi-level data fusion using the Evidence theory. In a first step, the sensor reliabilities are estimated using indicators provided by the sources. Simultaneously, a multi-criterion fusion is processed on attributes extracted from the navigation system to detect its potential erroneous data and define the best navigation limit speed candidate. The second fusion level - the multi-sensor fusion - considers the navigation and the camera-based SLSR to be independent and specialized. In addition, the conflict is interpreted as an additional source of information for the final speed limit definition. The benefits of the proposed solution are shown through simulations and real experiments.","PeriodicalId":117811,"journal":{"name":"2011 IEEE Intelligent Vehicles Symposium (IV)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Conflict management in multi-sensor dempster-shafer fusion for speed limit determination\",\"authors\":\"Jérémie Daniel, Jean-Philippe Lauffenburger\",\"doi\":\"10.1109/IVS.2011.5940398\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper deals with a Speed Limit Determination Advanced Driver Assistance System (ADAS) performing the combination of a navigation system and a Speed Limit Sign Recognition System (SLSR). The present strategy is based on a multi-level data fusion using the Evidence theory. In a first step, the sensor reliabilities are estimated using indicators provided by the sources. Simultaneously, a multi-criterion fusion is processed on attributes extracted from the navigation system to detect its potential erroneous data and define the best navigation limit speed candidate. The second fusion level - the multi-sensor fusion - considers the navigation and the camera-based SLSR to be independent and specialized. In addition, the conflict is interpreted as an additional source of information for the final speed limit definition. The benefits of the proposed solution are shown through simulations and real experiments.\",\"PeriodicalId\":117811,\"journal\":{\"name\":\"2011 IEEE Intelligent Vehicles Symposium (IV)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-06-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE Intelligent Vehicles Symposium (IV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IVS.2011.5940398\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE Intelligent Vehicles Symposium (IV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IVS.2011.5940398","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Conflict management in multi-sensor dempster-shafer fusion for speed limit determination
This paper deals with a Speed Limit Determination Advanced Driver Assistance System (ADAS) performing the combination of a navigation system and a Speed Limit Sign Recognition System (SLSR). The present strategy is based on a multi-level data fusion using the Evidence theory. In a first step, the sensor reliabilities are estimated using indicators provided by the sources. Simultaneously, a multi-criterion fusion is processed on attributes extracted from the navigation system to detect its potential erroneous data and define the best navigation limit speed candidate. The second fusion level - the multi-sensor fusion - considers the navigation and the camera-based SLSR to be independent and specialized. In addition, the conflict is interpreted as an additional source of information for the final speed limit definition. The benefits of the proposed solution are shown through simulations and real experiments.