Shuangshuang Han, Feiyue Wang, Yingchun Wang, Dongpu Cao, Li Li
{"title":"基于ACP理论的平行车辆:自动驾驶安全行驶","authors":"Shuangshuang Han, Feiyue Wang, Yingchun Wang, Dongpu Cao, Li Li","doi":"10.1109/IVS.2017.7995693","DOIUrl":null,"url":null,"abstract":"With the development of intelligent technologies, self-driving vehicles are considered as a promising solution against accident, traffic congestion and pollution problems. Intelligent vehicle techniques have been the research focus all over the world. However, full self-driving vehicles are still far away from its realization and extensive application due to safety requirements and cost considerations. As a novel breakthrough, PArallel VEhicles (PAVE) incorporate the ACP theory, which facilitates real-time interaction and optimization of the actual self-driving vehicles and the artificial ones. As a result, PAVE can maintain intelligent control of the actual self-driving vehicles and achieve the global optimization via software-defined self-driving vehicles, intelligent infrastructure construction, and parallel control center. Besides, PAVE can effectively reduce the cost of high-precision equipments on the actual self-driving vehicles via remote processing and intelligent road(side) infrastructure, and also achieve improved safety and reliability via remote control, guidance and planning.","PeriodicalId":143367,"journal":{"name":"2017 IEEE Intelligent Vehicles Symposium (IV)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Parallel vehicles based on the ACP theory: Safe trips via self-driving\",\"authors\":\"Shuangshuang Han, Feiyue Wang, Yingchun Wang, Dongpu Cao, Li Li\",\"doi\":\"10.1109/IVS.2017.7995693\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the development of intelligent technologies, self-driving vehicles are considered as a promising solution against accident, traffic congestion and pollution problems. Intelligent vehicle techniques have been the research focus all over the world. However, full self-driving vehicles are still far away from its realization and extensive application due to safety requirements and cost considerations. As a novel breakthrough, PArallel VEhicles (PAVE) incorporate the ACP theory, which facilitates real-time interaction and optimization of the actual self-driving vehicles and the artificial ones. As a result, PAVE can maintain intelligent control of the actual self-driving vehicles and achieve the global optimization via software-defined self-driving vehicles, intelligent infrastructure construction, and parallel control center. Besides, PAVE can effectively reduce the cost of high-precision equipments on the actual self-driving vehicles via remote processing and intelligent road(side) infrastructure, and also achieve improved safety and reliability via remote control, guidance and planning.\",\"PeriodicalId\":143367,\"journal\":{\"name\":\"2017 IEEE Intelligent Vehicles Symposium (IV)\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE Intelligent Vehicles Symposium (IV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IVS.2017.7995693\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Intelligent Vehicles Symposium (IV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IVS.2017.7995693","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Parallel vehicles based on the ACP theory: Safe trips via self-driving
With the development of intelligent technologies, self-driving vehicles are considered as a promising solution against accident, traffic congestion and pollution problems. Intelligent vehicle techniques have been the research focus all over the world. However, full self-driving vehicles are still far away from its realization and extensive application due to safety requirements and cost considerations. As a novel breakthrough, PArallel VEhicles (PAVE) incorporate the ACP theory, which facilitates real-time interaction and optimization of the actual self-driving vehicles and the artificial ones. As a result, PAVE can maintain intelligent control of the actual self-driving vehicles and achieve the global optimization via software-defined self-driving vehicles, intelligent infrastructure construction, and parallel control center. Besides, PAVE can effectively reduce the cost of high-precision equipments on the actual self-driving vehicles via remote processing and intelligent road(side) infrastructure, and also achieve improved safety and reliability via remote control, guidance and planning.