{"title":"Automated and Connected Unmanned Aerial Vehicles (AC-UAV) for Service Patrol: System Design and Field Experiments","authors":"Kaiping Wang, Rong Yang, Xi Lin, Fang He, M. Li","doi":"10.1109/ITSC45102.2020.9294353","DOIUrl":null,"url":null,"abstract":"With the recent development of Unmanned Aerial Vehicles (UAV) applications, traffic police might utilize UAV to conduct Service Patrol (SP) tasks. However, a major limitation of existing UAV systems is their limited flight endurance. To address this issue, by implementing the auto-rechargeable mechanism, we explicitly optimize hardware setting and system strategy required for regional SP with predefined initial tasks and stochastic incidents by solving a heuristic facility location problem and multi-objective path planning problem based on cooperative auto-recharging facilities, and fleet management center. The proposed fleet size and system performance are leveraged in a grid network with respect to different infrastructure settings and service coverage. The field experiments were conducted in Xi’an for SP tasks in complete vehicle coverage trajectory reconstruction, and results show that the proposed system is capable of unmanned SP tasks and large-scale application in urban scenarios.","PeriodicalId":394538,"journal":{"name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITSC45102.2020.9294353","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
With the recent development of Unmanned Aerial Vehicles (UAV) applications, traffic police might utilize UAV to conduct Service Patrol (SP) tasks. However, a major limitation of existing UAV systems is their limited flight endurance. To address this issue, by implementing the auto-rechargeable mechanism, we explicitly optimize hardware setting and system strategy required for regional SP with predefined initial tasks and stochastic incidents by solving a heuristic facility location problem and multi-objective path planning problem based on cooperative auto-recharging facilities, and fleet management center. The proposed fleet size and system performance are leveraged in a grid network with respect to different infrastructure settings and service coverage. The field experiments were conducted in Xi’an for SP tasks in complete vehicle coverage trajectory reconstruction, and results show that the proposed system is capable of unmanned SP tasks and large-scale application in urban scenarios.