{"title":"无人机公路网优化设计","authors":"Masatoshi Hamnanaka","doi":"10.1109/ICUAS.2019.8798304","DOIUrl":null,"url":null,"abstract":"This paper describes a design method for drone highway networks to eliminate the risk of conflict between drones and to improve the overall flight efficiency. Many flight path designing methods have been proposed; however, none of them addresses the issue of flight efficiency. We optimize each path using ant colony optimization and optimize the position of the terminal connecting the paths using particle swarm optimization. Experimental results show that the proposed method improves flight efficiency by 15.6% on average.","PeriodicalId":426616,"journal":{"name":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Optimum Design for Drone Highway Network\",\"authors\":\"Masatoshi Hamnanaka\",\"doi\":\"10.1109/ICUAS.2019.8798304\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes a design method for drone highway networks to eliminate the risk of conflict between drones and to improve the overall flight efficiency. Many flight path designing methods have been proposed; however, none of them addresses the issue of flight efficiency. We optimize each path using ant colony optimization and optimize the position of the terminal connecting the paths using particle swarm optimization. Experimental results show that the proposed method improves flight efficiency by 15.6% on average.\",\"PeriodicalId\":426616,\"journal\":{\"name\":\"2019 International Conference on Unmanned Aircraft Systems (ICUAS)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Unmanned Aircraft Systems (ICUAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICUAS.2019.8798304\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Unmanned Aircraft Systems (ICUAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICUAS.2019.8798304","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper describes a design method for drone highway networks to eliminate the risk of conflict between drones and to improve the overall flight efficiency. Many flight path designing methods have been proposed; however, none of them addresses the issue of flight efficiency. We optimize each path using ant colony optimization and optimize the position of the terminal connecting the paths using particle swarm optimization. Experimental results show that the proposed method improves flight efficiency by 15.6% on average.