@article{ref1,
title="Autonomous flight-test data in support of safety of flight certification",
journal="Journal of air transportation (Reston, Va.)",
year="2021",
author="Costello, Donald H. and Jewell, Jason and Xu, Huan",
volume="29",
number="2",
pages="93-106",
abstract="The current safety of flight clearances for unmanned aircraft requires a qualified operator who can make decisions and ultimately bears the responsibility for the safe operations of the vehicle. The future of aviation is unmanned, and ultimately autonomous. Yet, a method for certifying an autonomous vehicle to make decisions currently reserved for qualified pilots does not exist. Before we can field autonomous systems, a process needs to be approved to certify them. This paper analyzes the flight-test data (both developmental and operational) of an autonomous decision engine selecting an appropriate landing site for a large rotorcraft in an unprepared landing zone. In particular, this paper focuses on using legacy test and evaluation methods to determine their suitability for obtaining a safety of flight clearance for a system that possesses autonomous functionality. We will show that the autonomous system under test was able to complete a mission currently reserved for qualified pilots under controlled conditions. However, when confronted with conditions that were not anticipated (or programmed), the software lacked the judgment a pilot uses to complete a mission under off-nominal conditions.<p /> <p>Language: en</p>",
language="en",
issn="2380-9450",
doi="10.2514/1.D0220",
url="http://dx.doi.org/10.2514/1.D0220"
}