Asia-Pacific AAM Report 1H 2023

INTERVIEW WITH STUTTGART UNIVERSITY OF APPLIED SCIENCES
Moreover, the subtleties of the passenger experience play
a significant role. The takeoff and landing phases, widely
acknowledged as the most nerve-wracking aspects of any flight,
remain a paramount challenge in ensuring passenger comfort
within an autonomous eVTOL, especially considering the unique
surroundings associated with each flight path.
To address these concerns, researchers and developers are
striving to create intuitive and responsive autonomous systems
that can emulate the expertise and human touch of seasoned
pilots. Advancements in artificial intelligence, such as the AI
pilot model developed at Carnegie Mellon University's Robotics
Institute, leverage natural language processing and speech
recognition capabilities to humanize interactions and coordination
with pilots and air traffic controllers.
Thus far, simulation tests have yielded promising results,
showcasing the AI's effectiveness in navigating complex and everchanging
conditions inherent to typical eVTOL flight paths operating
under visual flight rules (VFR), potentially in segregated lanes.
Furthermore, ease of use and passenger interface are crucial
factors. As passengers become more actively engaged in their
flight experiences, operators in this emerging market must prioritize
a seamless user journey as a key selling point. Initially, interacting
with an autonomous system may feel unfamiliar and disconcerting
to many. Therefore, an empathetic user experience (UX) design
needs to be developed, one that fosters a sense of control, comfort,
and safety, bridging the gap between users and automation.
Operator's Perspective: Refinement for
Efficiency and Safety
From the operator's standpoint, autonomous eVTOLs present a
distinctive array of challenges that need to be addressed. The
paramount concern revolves around maintaining optimal levels of
efficiency and safety in uncrewed operations.
Operators must develop robust fail-safe systems, ensuring their
ability to conduct maintenance tasks swiftly and reliably, and
regularly update the machine learning algorithms that govern the
aircraft's functions. In this context, efficient data management and
real-time monitoring systems play an indispensable role, allowing
operators to predict and proactively address potential failures.
The second area of concern pertains to air traffic control for
eVTOLs. As the skies become increasingly populated with
autonomous aircraft, a sophisticated system must be in place to
manage the escalating volume of air traffic and facilitate the safe
coexistence of autonomous and piloted flights. Regulatory bodies
like the Federal Aviation Administration (FAA) will undeniably
exert a significant influence in shaping the management of
competitive and uncontrolled airspace, with an unwavering
commitment to ensuring absolute safety.
It is anticipated that substantial capital investment and
collaboration with aviation regulators will be necessary to
formulate and establish operational frameworks that fulfill
the unique safety requirements of eVTOL systems. These
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