z-logo
open-access-imgOpen Access
Modelling of unmanned aircraft visibility for see-and-avoid operations
Author(s) -
Patrick Highland,
Jon Williams,
M. Yazvec,
A. Dideriksen,
Nicole M. Corcoran,
Kristin K. Woodruff,
Cyril C. Thompson,
Levi Kirby,
Edward K Chun,
H. Kousheh,
Jon Stoltz,
Thomas Schnell
Publication year - 2020
Publication title -
journal of unmanned vehicle systems
Language(s) - English
Resource type - Journals
ISSN - 2291-3467
DOI - 10.1139/juvs-2020-0011
Subject(s) - visibility , rulemaking , aviation , aeronautics , work (physics) , computer science , collision , engineering , computer security , aerospace engineering , meteorology , law , geography , political science , mechanical engineering
With more unmanned aircraft (UA) becoming airborne each day, an already high manned aircraft to UA exposure rate continues to grow. Pilots and rulemaking authorities realize that UA visibility is a real, but unquantified, threat to operations under the see-and-avoid concept. To finally quantify the threat, a novel contrast-based UA visibility model is constructed here using collected empirical data as well as previous work on the factors affecting visibility. This work showed that UA visibility <1300 m makes a midair collision a serious threat if a manned aircraft and a UA are on a collision course while operating under the see-and-avoid concept. Similarly, this work also showed that a midair collision may be unavoidable when UA visibility is <400 m. Validating pilot and rulemaking authority concerns, this work demonstrated that UA visibility distances <1300 and <400 m occur often in the real world. Finally, the model produced UA visibility lookup tables that may prove useful to rulemaking authorities such as the U.S. Federal Aviation Administration and International Civil Aviation Organization for future work in the proof of equivalency of detect and avoid operations. Until then, pilots flying at slower airspeeds in the vicinity of UA may improve safety margins.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom