{"title":"共享型无人机企业运营商池化框架(SUAVE)的机会约束池化扇出排队分析","authors":"L. Bush","doi":"10.1109/COGSIMA.2015.7107970","DOIUrl":null,"url":null,"abstract":"The number of unmanned aerial vehicles (UAVs) in the Air Force inventory is rapidly increasing without a concomitant increase in manpower. Military planners are currently seeking technologies that enable operators to simultaneously control a greater number of UAVs. The technology planning and recommendation process requires a systems-level engineering analysis of UAV operations and their sensitivity to various constraints. Olsen and Wood introduced a concept called fan-out, which estimates how many operators are required to effectively operate a given set of UAVs. The fan-out concept assumes that UAVs are permanently assigned to a single operator or operator team. We designed a pooled UAV-to-operator team allocation scheme, which allows sharing of operator team resources across the entire UAV fleet. Rather than permanently assigning a given UAV to an operator team, our architecture dynamically allocates operator teams to UAVs on an as-needed basis during multi-UAV operations. We constructed an architecture based on queueing theory to empirically compare pooled and non-pooled performance. Queueing systems analysis of this architecture demonstrates that it performs better than a non-teaming approach. Moreover, our architectural analysis leads to a more general definition of fanout. More importantly, the closed-form queueing analysis is highly efficient, allowing us to analyze a greater number of problem configurations. This greater command of the problem space also offers advantages in determining appropriate autonomy and teaming technologies for further development.","PeriodicalId":373467,"journal":{"name":"2015 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Shared UAV enterprise operator pooling framework (SUAVE) chance constrained pooled fan-out queueing analysis\",\"authors\":\"L. Bush\",\"doi\":\"10.1109/COGSIMA.2015.7107970\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The number of unmanned aerial vehicles (UAVs) in the Air Force inventory is rapidly increasing without a concomitant increase in manpower. Military planners are currently seeking technologies that enable operators to simultaneously control a greater number of UAVs. The technology planning and recommendation process requires a systems-level engineering analysis of UAV operations and their sensitivity to various constraints. Olsen and Wood introduced a concept called fan-out, which estimates how many operators are required to effectively operate a given set of UAVs. The fan-out concept assumes that UAVs are permanently assigned to a single operator or operator team. We designed a pooled UAV-to-operator team allocation scheme, which allows sharing of operator team resources across the entire UAV fleet. Rather than permanently assigning a given UAV to an operator team, our architecture dynamically allocates operator teams to UAVs on an as-needed basis during multi-UAV operations. We constructed an architecture based on queueing theory to empirically compare pooled and non-pooled performance. Queueing systems analysis of this architecture demonstrates that it performs better than a non-teaming approach. Moreover, our architectural analysis leads to a more general definition of fanout. More importantly, the closed-form queueing analysis is highly efficient, allowing us to analyze a greater number of problem configurations. This greater command of the problem space also offers advantages in determining appropriate autonomy and teaming technologies for further development.\",\"PeriodicalId\":373467,\"journal\":{\"name\":\"2015 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-03-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COGSIMA.2015.7107970\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COGSIMA.2015.7107970","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The number of unmanned aerial vehicles (UAVs) in the Air Force inventory is rapidly increasing without a concomitant increase in manpower. Military planners are currently seeking technologies that enable operators to simultaneously control a greater number of UAVs. The technology planning and recommendation process requires a systems-level engineering analysis of UAV operations and their sensitivity to various constraints. Olsen and Wood introduced a concept called fan-out, which estimates how many operators are required to effectively operate a given set of UAVs. The fan-out concept assumes that UAVs are permanently assigned to a single operator or operator team. We designed a pooled UAV-to-operator team allocation scheme, which allows sharing of operator team resources across the entire UAV fleet. Rather than permanently assigning a given UAV to an operator team, our architecture dynamically allocates operator teams to UAVs on an as-needed basis during multi-UAV operations. We constructed an architecture based on queueing theory to empirically compare pooled and non-pooled performance. Queueing systems analysis of this architecture demonstrates that it performs better than a non-teaming approach. Moreover, our architectural analysis leads to a more general definition of fanout. More importantly, the closed-form queueing analysis is highly efficient, allowing us to analyze a greater number of problem configurations. This greater command of the problem space also offers advantages in determining appropriate autonomy and teaming technologies for further development.