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.

本研究的目的是定义一种整体有效的架构方法，用于实施安全且有利可图的 UAM 飞行员机场穿梭系统，该系统可扩展到给定时间的最佳可用数据。这项研究的提议是利用能够垂直起降 (VTOL) 的自主无人机系统在机场和美国不同城市的指定目的地之间运输乘客和货物：亚特兰大、洛杉矶和达拉斯。该研究包括定义要考虑的一组标准指标，为定义的案例研究开发系统模型，以及执行交易空间分析以量化评估实现最理想架构结果的替代方法。本研究模拟并评估了 1、620 个可枚举的架构并分析众多交易空间，以检查决策变量和性能指标之间的相关性和相互关系。在这些指标中，此分析侧重于年利润、平均事件间隔时间 (MTBI)、前期成本和每天接送乘客之间的相互关系。结果分析在真实和模糊帕累托前沿对架构进行排名，用于确定与这些相互关系相关的基本和准必要特征。根据各个利益相关者及其独特需求，该模型推荐洛杉矶作为试点城市，该系统利用先进先出排队系统、智能手机界面和利用电能的混合能源。