15 Metrotech Center
Urban Air Mobility (UAM) is an envisioned air transportation concept where intelligent flying machines could safely and efficiently transport passengers and cargo within urban areas by rising above traffic congestion on the ground. “The convergence of technologies, and new business models enabled by the digital revolution, is making it possible to explore this new way for people and cargo to move within our cities,” said Jaiwon Shin, NASA Associate Administrator for Aeronautics Research Mission Directorate. Companies such as Boeing, Airbus, Bell, Embraer, Joby, Zee Aero, Pipistrel, and Volocopter are working with their battery vendors to build and test electric vertical takeoff and landing (eVTOL) aircraft to ensure that vehicle safety and energy efficiency become an integral part of people’s daily commute. Furthermore, in order to make UAM profitable for operators and affordable for passengers, the flight operations must be able to scaled, which means that the expected air traffic density will be extremely high. For example, as one of the industry leaders in UAM, Uber estimated more than 5,000 eVTOL flights per day in the city of Los Angeles for its future scaled Uber Air operations. The UAM community recognized a key challenge remaining unanswered to make UAM a reality: how can we design and build a real-time, trustworthy, safety-critical autonomous UAM ecosystem to enable large-scale flight operations in high-density, dynamic and complex urban airspace environments? In this talk the speaker will present preliminary studies to address this critical research challenge from areas in autonomy, control, real-time systems and safety. Our multidisciplinary approach is based on bridging guidance and control, reinforcement learning, and Markov decision process.
Peng Wei is an assistant professor in Iowa State University Aerospace Engineering Department, with courtesy appointments in Electrical and Computer Engineering Department and Computer Science Department. He is also an affiliated faculty member with the FAA Center of Excellence for General Aviation (PEGASAS), and the Human Computer Interaction graduate program at Virtual Reality Applications Center (VRAC) at ISU. Prof. Wei is leading the Intelligent Aerospace Systems Lab (IASL). With methods from control, optimization, machine learning, and artificial intelligence, he develops autonomous and decision making systems for: Air Traffic Control/Management (ATC/M), Airline Operations, UAS Traffic Management (UTM), and eVTOL Urban Air Mobility (UAM). Prof. Wei received his undergraduate degree in Information Science and Control Theory from Tsinghua University in 2007, a master degree in Electrical and Computer Engineering from Stony Brook University in 2009, and a Ph.D. degree in Aerospace Engineering from Purdue University in 2013.