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.
Autonomous drone aircraft traffic in uncontrolled airspace below 400 feet altitude is expected to substantially increase in the next few years. Experts anticipate a fleet of nearly 1 million commercial uncrewed aircraft systems (UAS) in the U.S. by 2027, engaging in tasks like package delivery, traffic monitoring, and emergency assistance.
Artificial intelligence aboard aircraft could help prevent terrifying drops in altitude. In a new study, an international research team successfully tested a machine learning system for preventing trouble with turbulence. The findings are published in the journal Nature Communications.
Designing reliable aircraft can be both challenging and time-consuming, as it often entails several steps and analyses. Deep learning models could potentially help to speed up aircraft design and deployment, helping developers to identify the most promising solutions or potential flaws with a specific aircraft.