Urban Air Mobility (UAM) can only be achieved at scale when emerging eVTOL operations are safe despite reduced pilot training requirements. Increased autonomy and access to new data pipelines are viewed as foundations to enable safe UAM operations. Traditional sensor data can be augmented with new cloud resources such as roadmaps and geographical information system (GIS) Lidar/video to offer emerging unmanned aircraft systems (UAS) and UAM operations a new level of situational awareness. This presentation will introduce challenges in UAM and summarize my group's research to identify, process, and utilize new data sources during nominal and emergency flight planning. Specific efforts have utilized machine learning to automatically map urban emergency landing sites, trade in-flight and landing site risks as needed, and incorporate cell phone data into an occupancy map. Research in flight safety assessment and management (FSAM) will be summarized; this work offers potential for improved resilience and increased verification for autonomous aircraft flight management. The presentation will end with videos illustrating recent small UAS flight testing in the University of Michigan's new M-Air netted flight facility.
Speaker: Ella Atkins, Univ. of Michigan
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