{"title":"大型UAS流量管理(UTM)结构","authors":"D. Sacharny, T. Henderson, Michael Cline","doi":"10.1109/MFI49285.2020.9235237","DOIUrl":null,"url":null,"abstract":"The advent of large-scale Unmanned Aircraft Systems (UAS) exploitation for urban tasks, such as delivery, has led to a great deal of research and development in the UAS Traffic Management (UTM) domain. The general approach at this time is to define a grid network for the area of operation, and then have UAS Service Suppliers (USS) pairwise deconflict any overlapping grid elements for their flights. Moreover, this analysis is performed on arbitrary flight paths through the airspace, and thus may impose a substantial computational burden in order to ensure strategic deconfliction (that is, no two flights are ever closer than the minimum required separation). However, the biggest drawback to this approach is the impact of contingencies on UTM operations. For example, if one UAS slows down, or goes off course, then strategic deconfliction is no longer guaranteed, and this can have a disastrous snowballing effect on a large number of flights. We propose a lane-based approach which not only allows a one-dimensional strategic deconfliction method, but provides structural support for alternative contingency handling methods with minimal impact on the overall UTM system. Methods for lane creation, path assignment through lanes, flight strategic deconfliction, and contingency handling are provided here.","PeriodicalId":446154,"journal":{"name":"2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Large-Scale UAS Traffic Management (UTM) Structure\",\"authors\":\"D. Sacharny, T. Henderson, Michael Cline\",\"doi\":\"10.1109/MFI49285.2020.9235237\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The advent of large-scale Unmanned Aircraft Systems (UAS) exploitation for urban tasks, such as delivery, has led to a great deal of research and development in the UAS Traffic Management (UTM) domain. The general approach at this time is to define a grid network for the area of operation, and then have UAS Service Suppliers (USS) pairwise deconflict any overlapping grid elements for their flights. Moreover, this analysis is performed on arbitrary flight paths through the airspace, and thus may impose a substantial computational burden in order to ensure strategic deconfliction (that is, no two flights are ever closer than the minimum required separation). However, the biggest drawback to this approach is the impact of contingencies on UTM operations. For example, if one UAS slows down, or goes off course, then strategic deconfliction is no longer guaranteed, and this can have a disastrous snowballing effect on a large number of flights. We propose a lane-based approach which not only allows a one-dimensional strategic deconfliction method, but provides structural support for alternative contingency handling methods with minimal impact on the overall UTM system. Methods for lane creation, path assignment through lanes, flight strategic deconfliction, and contingency handling are provided here.\",\"PeriodicalId\":446154,\"journal\":{\"name\":\"2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)\",\"volume\":\"73 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MFI49285.2020.9235237\",\"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 International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MFI49285.2020.9235237","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The advent of large-scale Unmanned Aircraft Systems (UAS) exploitation for urban tasks, such as delivery, has led to a great deal of research and development in the UAS Traffic Management (UTM) domain. The general approach at this time is to define a grid network for the area of operation, and then have UAS Service Suppliers (USS) pairwise deconflict any overlapping grid elements for their flights. Moreover, this analysis is performed on arbitrary flight paths through the airspace, and thus may impose a substantial computational burden in order to ensure strategic deconfliction (that is, no two flights are ever closer than the minimum required separation). However, the biggest drawback to this approach is the impact of contingencies on UTM operations. For example, if one UAS slows down, or goes off course, then strategic deconfliction is no longer guaranteed, and this can have a disastrous snowballing effect on a large number of flights. We propose a lane-based approach which not only allows a one-dimensional strategic deconfliction method, but provides structural support for alternative contingency handling methods with minimal impact on the overall UTM system. Methods for lane creation, path assignment through lanes, flight strategic deconfliction, and contingency handling are provided here.