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AIAA 2023-0787
Session: Autonomy for Advanced Air Mobility Systems I
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Air vehicles routinely encounter turbulence, and appropriate responses to turbulence are critical for flight safety and passenger comfort. Currently, human pilots have primary responsibility for detecting and responding to turbulence, but many future air vehicles are likely to be operated without a skilled pilot onboard. This includes both unmanned air vehicles, and vehicles such as distributed electric propulsion vertical take-off and landing air taxi vehicles, many of which are being developed to operate with high levels of autonomy. Automated systems are thus needed to perform turbulence-related functions currently allocated to onboard human pilots. The authors have developed turbulence modeling methods, and associated onboard turbulence quantification and decision-making technologies that address the unique challenges of new classes of vehicles and complex, low altitude operating environments, especially in urban areas. Collectively, these tools are referred to as the Turbulence Modeling And Decision Support (TMADS) System. This paper focuses on a flight test demonstration of the turbulence quantification aspects of the TMADS system. The flight tests employed small quadcopter vehicles, and made use of research-grade ground-based sensors to provide accurate turbulence measures against which to validate TMADS outputs. The results show the effectiveness of the TMADS turbulence quantification methods, and the feasibility of implementing these in near-real-time using existing flight control sensors and computational resources available on a small vehicle.