Architecting urban air mobility airport shuttling systems with case studies: Atlanta, Los Angeles, and Dallas

The purpose of this study is to define a holistic and effective architectural approach for implementing a safe and profitable pilot UAM airport shuttling system, which is extensible to the best available data at a given time. The proposition of this research is to leverage a system of autonomous UAVs capable of vertical takeoff and landing (VTOL) to transport passengers and cargo between airports and defined destinations in different urban cities in the United States: Atlanta, Los Angeles, and Dallas. The study comprises of defining a standard set of metrics to consider, developing a system model for defined case studies, and performing tradespace analyses to quantifiably evaluate alternative ways of achieving the most desirable architecture outcomes. This study models and evaluates 1,620 enumerable architectures and analyzes numerous tradespaces to examine the correlation and interrelationships between decision variables and performance metrics. Among the metrics, this analysis focuses on the interrelationships between Annual Profit, Mean Time Between Incident (MTBI), Upfront Cost, and Passengers Shuttled Per Day. The resulting analysis ranks architectures on the True and Fuzzy Pareto Front that is used to determine essential and quasi-necessary features in relation to these interrelationships. Based on the various stakeholders and their unique needs, the model recommends Los Angeles as the pilot city and for the system to leverage a FIFO queuing system, a smartphone interface, and a hybrid energy source that utilizes electric energy.