{"title":"无监督运输车辆控制:仿真研究与性能结果","authors":"A. Beinarovica, M. Gorobetz, Ivars Alps","doi":"10.1109/RTUCON51174.2020.9316595","DOIUrl":null,"url":null,"abstract":"This paper presents current results of the research, aimed at the developing of motion control algorithms and systems for unsupervised electric vehicles, and discusses the results of the computer simulations and necessary parameters. The task of current research is to develop immune neural network based system structure and computer model for analyzing the situation and minimizing the collision probability by changing electrical vehicles movement parameters, to develop the computer model and to find appropriate parameters for best simulation results.","PeriodicalId":332414,"journal":{"name":"2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Unsupervised Transport Vehicle Control: Simulation Study and Performance Results\",\"authors\":\"A. Beinarovica, M. Gorobetz, Ivars Alps\",\"doi\":\"10.1109/RTUCON51174.2020.9316595\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents current results of the research, aimed at the developing of motion control algorithms and systems for unsupervised electric vehicles, and discusses the results of the computer simulations and necessary parameters. The task of current research is to develop immune neural network based system structure and computer model for analyzing the situation and minimizing the collision probability by changing electrical vehicles movement parameters, to develop the computer model and to find appropriate parameters for best simulation results.\",\"PeriodicalId\":332414,\"journal\":{\"name\":\"2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RTUCON51174.2020.9316595\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RTUCON51174.2020.9316595","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Unsupervised Transport Vehicle Control: Simulation Study and Performance Results
This paper presents current results of the research, aimed at the developing of motion control algorithms and systems for unsupervised electric vehicles, and discusses the results of the computer simulations and necessary parameters. The task of current research is to develop immune neural network based system structure and computer model for analyzing the situation and minimizing the collision probability by changing electrical vehicles movement parameters, to develop the computer model and to find appropriate parameters for best simulation results.