Researchers have developed an AI pilot that enables autonomous aircraft to navigate a crowded airspace. The artificial intelligence can safely avoid collisions, predict the intent of other aircraft, track aircraft and coordinate with their actions, and communicate over the radio with pilots and air traffic controllers. The researchers aim to develop the AI so the behaviors of their system will be indistinguishable from those of a human pilot.
From: Carnegie Mellon University
August 9, 2022 -- "We believe we could eventually pass the Turing
Test," said Jean Oh, an associate research professor at CMU's Robotics
Institute (RI) and a member of the AI pilot team, referring to the test of an
AI's ability to exhibit intelligent behavior equivalent to a human.
To interact with other
aircraft as a human pilot would, the AI uses both vision and natural language
to communicate its intent with other aircraft, whether piloted or not. This
behavior leads to safe and socially compliant navigation. Researchers achieved
this implicit coordination by training the AI on data collected at the
Allegheny County Airport and the Pittsburgh-Butler Regional Airport that
included air traffic patterns, images of aircraft and radio transmissions.
The AI uses six cameras
and a computer vision system to detect nearby aircraft in a manner similar to
that of a human pilot. Its automatic speech recognition function uses natural
language processing techniques to both understand incoming radio messages and
communicate with pilots and air traffic controllers using speech.
Advancement in
autonomous aircraft will broaden opportunities for drones, air taxis, helicopters
and other aircraft to operate -- moving people and goods, inspecting
infrastructure, treating fields to protect crops, and monitoring for poaching
or deforestation -- often without a pilot behind the controls. These aircraft
will have to fly, however, in an airspace already crowded with small airplanes,
medical helicopters and more.
The FAA and NASA have
proposed dividing this urban airspace into lanes or corridors with restrictions
on when, what kind and how many aircraft can use them. This would significantly
alter the current use and standard practices in this airspace and could create
air traffic jams, preventing critical aircraft, like a medivac helicopter, from
reaching its destination.
While autopilot
controls are common among commercial airliners and other aircraft operating in
higher altitudes under instrument flight rules (IFR), developing an AI to
handle the often crowded and pilot-controlled lower-altitude traffic operating
under visual flight rules (VFR) has challenged the aerospace industry. The
team's AI is designed to seamlessly interact with aircraft in the VFR airspace.
"This is the first
AI pilot that works in the current airspace," said Sebastian Scherer, an associate
research professor in the RI and a member of the team. "I don't see that
airspace changing for UAVs. The UAVs will have to change for the
airspace."
The team has yet to
test the AI pilot on actual aircraft, but it has performed well on flight simulators.
To test the AI, the team sets up two flight simulators. One is controlled by
the AI, the other by a human. Both operate in the same airspace. The AI can
safely navigate around the piloted aircraft, even if the person behind the
controls is not an experienced pilot.
Commercially, the AI
could help autonomous aircraft deliver packages and ferry passengers. Delivery
drones and air taxis ideally would not operate with a pilot to save weight and
insulate them from a pilot shortage.
"We need more
pilots, and AI can help," said Jay Patrikar, a Ph.D. student in the RI who
worked on the project.
This research was
supported by the U.S. Army Research Office and the Army Futures Command's
Artificial Intelligence Integration Center (AI2C).
https://www.sciencedaily.com/releases/2022/08/220809101737.htm
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