Past Event: Oden Institute Seminar

Unlock the Personal Sky - Safe and Assured Autonomy for On-Demand Urban Air Mobility

Peng Wei, Assistant Professor, Department of Aerospace Engineering, Iowa State University

Abstract

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. 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 scale, 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. Bio 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. Prof. Wei is leading the Intelligent Aerospace Systems Lab (IASL). By contributing to the intersection of control, optimization, machine learning, and artificial intelligence, he designs autonomous and human-in-the-loop decision making systems for aeronautics, aviation and aerial robotics. Recent applications include: Air Traffic Control/Management (ATC/M), Airline Operations, UAS Traffic Management (UTM), eVTOL Urban Air Mobility (UAM) and Autonomous Drone Racing (ADR). Prof. Wei received his undergraduate degree in Information Science and Control Theory from Tsinghua University and a Ph.D. degree in Aerospace Engineering from Purdue University. He serves in several advisory boards at Airbus and NASA. He is an associate editor of AIAA Journal of Aerospace Information Systems.