Embry-Riddle Aeronautical University has teamed up with Eclipse Aerospace to create an innovative tool aimed at reducing pilot workload in aviation radio communication through the use of artificial intelligence technology. This collaboration is set to transform how pilots interact with air traffic control and enhance overall flight safety.
The AI-driven solution utilizes automatic speech recognition (ASR) and natural language processing (NLP) to effectively capture voice transmissions and extract vital information from air traffic control (ATC) communications. By streamlining cockpit tasks, it has the potential to improve pilots’ situational awareness and lessen their workload considerably.
Eclipse Aerospace is not only funding the project but also providing valuable support through its Flight Test infrastructure.
“A safer aviation future requires lighter pilot workloads — and AI is central to that future,” stated Jeffrey Rochelle, executive vice president at Eclipse Aerospace. “Eclipse Aerospace is committed to accelerating AI innovations that improve safety in the cockpit.”
Dr. Andrew Schneider, an assistant professor and director of Flight Research in the College of Aviation, along with Dr. Jianhua Liu, an associate professor of Electrical and Computer Engineering in the College of Engineering, are the main researchers driving this project.
“We are excited to work with Eclipse Aerospace on advancing AI speech recognition to bolster aircraft safety and reduce pilot workload,” Schneider commented.
The AI system listens to and processes communications between pilots and air traffic control. By leveraging automatic speech recognition (ASR) and natural language processing (NLP)—two critical elements of AI that allow for the interpretation and response to human speech—the tool captures specific instructions and commands such as heading, flight level, speed, frequency, and squawk code. These essential components are extracted and presented, allowing pilots to decide whether to execute those commands in the avionics.
“Our aim is to assess the feasibility of implementing this technology in a real-time flight deck environment,” Schneider noted.
There are challenges to overcome, including cockpit noise and radio signal interference, as well as the variability in language when pilots deviate from standard phraseology.
“It is crucial for the system to accurately decipher instructions even in chaotic environments,” Schneider emphasized.
The research team has been testing the tool in both laboratory and flight scenarios, achieving high accuracy in real-time automatic speech recognition and making solid progress in natural language processing capabilities. The project also benefits from the involvement of Ph.D. student Shital Pandey, master’s student Sai Preethi Kunjeti, and undergraduate student Avery Cuenin, all of whom are under Liu’s mentorship.
A core objective of the project is to assess the reduction of pilot workload when utilizing this tool. Supported by Ph.D. student Elizabeth Merwin, a human factors study will evaluate pilot performance, workload, and trust in automation and AI at the initial interface.
Moreover, researchers will explore how pilots engage with AI technology and how these interactions influence their performance.
“This collaboration with Eclipse allows us to investigate how human–AI teamwork can enhance decision-making in the cockpit,” Schneider concluded. “We are thrilled about the potential of this technology to evolve into a reliable tool that boosts situational awareness and overall pilot performance.”
