Aircraft avionics and training systems are evolving with artificial intelligence<\/p>\n\n\n\n
Artificial intelligence (AI) is disrupting every facet of the aviation industry, and the technology is poised to completely change the way aircraft fly. While pilotless passenger flights on self-flying, AI-powered airliners won\u2019t become a reality anytime soon, AI technology is already creeping into airplane flight decks and transforming how pilots do their jobs\u2014and how they learn to fly.<\/p>\n\n\n\n
A handful of companies developing AI-driven flight control systems are already flying autonomous aircraft experimentally, but AI isn\u2019t piloting any aircraft yet. Rather, autonomous airplanes being flown today by companies such as Xwing, Reliable Robotics, and Merlin rely on enhancements to existing autopilot technologies and remote-piloting capabilities. Using Cessna Grand Caravans as testbeds, those companies aim to convert existing legacy aircraft into autonomous aircraft under supplemental type certificates (STCs).<\/p>\n\n\n\n
\u201cAutonomy is not necessarily equal to artificial intelligence, or machine learning, or deep neural networks, or non-deterministic systems or anything like that. Autonomous machines can be perfectly deterministic,\u201d explained Honeywell Aerospace\u2019s Stephane Fymat at the Vertical Flight Society\u2019s 10th biennial autonomous VTOL technical meeting. \u201cThat’s good, because it means that the certifiability of autonomous aircraft can be a more tractable problem, especially considering some of the deeper challenges that we’re addressing right now around the explainability of AI, trust of AI, the generalizability of AI.\u201d<\/p>\n\n\n\n
Air safety regulators such as the FAA and the European Union Aviation Safety Agency (EASA) currently have no set path to certification for aircraft that fly themselves with AI. However, that\u2019s something both agencies are looking to change in the not-too-distant future. <\/p>\n\n\n\n
EASA and the FAA have both published their own AI \u201croadmaps\u201d in which the agencies spell out similar approaches to certifying AI. In EASA\u2019s AI roadmap, a \u201cliving document\u201d last updated in 2023, the regulator said it expects fully autonomous AI aircraft to enter service in the 2035 to 2050 timeframe\u2014yet it expects to certify its first AI avionics system as early as next year.<\/p>\n\n\n\n
According to EASA\u2019s roadmap, initial applications for AI in the cockpit will center around pilot assistance, helping to reduce pilot workload and improve safety. Over the next decade, progressively more automated solutions will enable reduced-crew or single-pilot operations\u2014maintaining a human in the loop\u2014and by 2050, AI could be flying aircraft without any human supervision.<\/p>\n\n\n\n
The first AI-powered avionics system appears to be on track for EASA certification by the end of this year, according to Swiss AI start-up Daedalean, which is working on an STC for an AI-powered pilot assistance system called PilotEye.<\/p>\n\n\n\n
Developed in partnership with U.S. avionics manufacturer Avidyne, PilotEye uses cameras, sensors, and AI software developed with machine-learning algorithms to provide pilots with complete situational awareness plus detect-and-avoid capabilities. The company refers to its computer vision technology as \u201csituational intelligence\u201d because it \u201cencompasses situational awareness as well as the ability to anticipate and react to a threatening situation.\u201d<\/p>\n\n\n\n
PilotEye uses AI and neural networks to analyze images and data from various cameras and sensors to accurately perceive its surroundings. \u201cYou don’t need AI for decision-making; you need the AI part for seeing that it’s a runway and not a road and that it’s actually going the way you wanted to land on,\u201d Daedalean founder and CEO Luuk van Dijk .<\/p>\n\n\n\n
The AI-enabled computer vision software can accurately identify objects and obstacles to determine, for example, whether a camera has spotted \u201ca cloud that\u2019s not actually moving, or there’s an airplane that’s coming right at you,\u201d he explained. \u201cThese are a couple of the harder problems.\u201d<\/p>\n\n\n\n
Avidyne intends to offer the PilotEye as a feature in the Quantum avionics suite it launched last year specifically for new advanced air mobility aircraft, such as eVTOL air taxis and hybrid-electric regional airplanes. Daedalean is also developing an AI flight planning system that integrates with an aircraft\u2019s autopilot and enables autonomous navigation. This would ensure an aircraft can safely travel through designated corridors, such as eVTOL air taxis flying at low altitudes in urban areas.<\/p>\n\n\n\n
\u201cThings such as the ability to perceive or localize the aircraft in the world, the ability to interact perhaps with ATC using natural language (as much as we would all like it to go to data), the ability to help an aircraft plan complex courses of action on the fly in novel situations, and the ability to learn from the world also might make the system less brittle, and less expensive potentially to build or maintain,\u201d Fymat explained.<\/p>\n\n\n\n
Although totally AI-piloted aircraft may not enter service for several decades, some AI technology is already flying on aircraft today\u2014just not with the power to control the aircraft. So far, the focus of AI on aircraft has revolved around improving operational efficiencies.<\/p>\n\n\n\n
For example, flight management systems use AI algorithms to optimize routes and reduce fuel burn. Generative AI can also help to automate routine tasks. For example, in October, Turkish low-cost carrier Pegasus Airlines introduced AI-generated pilot announcements that provide passengers with flight information in several languages, allowing pilots to stay focused on flying.<\/p>\n\n\n\n
Earlier this year, Swedish company Web Manuals launched a new AI-powered search tool for pilots\u2019 flight manuals. Called Amelia AI, the platform functions as a chatbot that pilots can use to quickly retrieve information from within their flight manuals, allowing them to make swift and well-informed decisions.<\/p>\n\n\n\n
Web Manuals\u2019 AI search function \u201cmakes navigating through large amounts of operational and company manuals much more manageable and time efficient, with data retrieval within seconds,\u201d said the company\u2019s chief technology officer, Richard Sandstr\u00f6m.<\/p>\n\n\n\n
Researchers are also experimenting with AI-driven face and voice recognition software that could potentially monitor pilots\u2019 health and mental well-being. Blueskeye AI, a U.K.-based software company, uses facial recognition and voice analysis software \u201cto look at medically and biophysically relevant behavior, so we can use it to help assess, diagnose, monitor, and treat medical conditions that actually change your expressive behavior,\u201d such as fatigue, pain, and anxiety, Blueskeye AI founder and CEO Michel Valstar.<\/p>\n\n\n\n
When it comes to AI, the aviation industry (along with the rest of the world) is only beginning to understand the wealth of possibilities the technology can offer. While AI is changing the way aircraft and pilots fly, it\u2019s also changing just about every aspect of ground operations, ranging from flight booking platforms to supply chain management.<\/p>\n\n\n\n
Flight schools already have initiatives underway to use AI technology to make pilot training more efficient, effective, and accessible. At the forefront of those efforts is CAE, a global company that manufactures flight simulators and other training devices for airlines and flight schools.<\/p>\n\n\n\n
CAE is developing AI-driven tools that can provide personalized training experiences by analyzing a student pilot\u2019s performance and tailoring training plans to every individual\u2019s specific needs.<\/p>\n\n\n\n
\u201cFor future learning ecosystems to be successful, training providers must find ways to smartly blend the incredible advances we\u2019re seeing in education technology with the latest understanding in learning science,\u201d said Regan Patrick, CAE\u2019s chief learning officer. \u201cIt\u2019s important for CAE to understand what cognitive, behavioral, and neuroscience tells us regarding how humans learn so we can carry that forward into our training systems designs.\u201d<\/p>\n\n\n\n
According to CAE, its patented adaptive learning technology makes training more efficient and cost-effective. It implements systematic and objective rule-based measures of performance and effectiveness, and it provides instructors and students with real-time feedback. With an integrated biometric suite, it allows instructors to gauge students\u2019 stress, engagement, and cognitive workload.<\/p>\n\n\n\n
\u201cOne of the biggest challenges we see is the need to adjust mindsets, specifically migrating from traditional instructor-based training approaches to more student-centric experiential learning,\u201d Patrick said. <\/p>\n\n\n\n
CAE has also been using AI for years to enhance its flight simulators. According to the company, AI enables a broader range of realistic and dynamic environments and scenarios, including unanticipated events that could catch a pilot by surprise. <\/p>\n\n\n\n
In addition to AI and machine-learning capabilities, CAE and other flight training companies are integrating several other cutting-edge technologies into their training products, including virtual reality, mixed reality, and data analytics. CAE\u2019s virtual-reality training hardware includes headsets and hand-tracking technology. According to CAE, combining those types of tools with artificial intelligence will further expand the horizons for extended reality training.<\/p>\n\n\n\n