Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/151831
Title: Framework of level-of-autonomy-based concept of operations : UAS capabilities
Authors: Pang, Bizhao
Wang, John Chung-Hung
Low, Kin Huat
Keywords: Civil engineering::Transportation
Engineering::Aeronautical engineering::Aviation
Issue Date: 2021
Source: Pang, B., Wang, J. C. & Low, K. H. (2021). Framework of level-of-autonomy-based concept of operations : UAS capabilities. 2021 IEEE/AIAA 40th Digital Avionics Systems Conference (DASC). https://dx.doi.org/10.1109/DASC52595.2021.9594469
Abstract: The utility of unmanned aircraft system (UAS) is growing fast in recent years with applications like parcel delivery and security patrol. However, most of the current applications require the involvement of human operator, posing challenges for large-scale UAS deployment due to the operator’s and air traffic control officer’s (ATCO) limited cognitive capability to control and monitor the traffic. Autonomous UAS operation that reduces the operator and ATCO workload could be a promising solution to meet that challenge. The main aim of this paper, therefore, is to propose a conceptual framework for Level of Autonomy (LoA) based concept of operations (ConOps). The discussion includes the definition and evaluation of LoA and the investigation opportunities of enabling UAS operation at various LoA via case studies. This could be further extended for mixed operation with vehicles of multiple LoA. The framework is presented around core factors defining levels of autonomy for UAS and character for each level in terms of operational actions. Two use cases involving scheduled parcel delivery and non-scheduled emergency operation are presented to demonstrate the evaluation of LoA for a given operation. The proposed framework could serve to identify opportunities for research and engineering development of UAS operations in urban environments.
URI: https://hdl.handle.net/10356/151831
DOI: 10.1109/DASC52595.2021.9594469
Rights: © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/DASC52595.2021.9594469.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:ATMRI Conference Papers
MAE Conference Papers

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