Enabling Urban Air Mobility: Human-Autonomy Teaming Research Challenges and Recommendations
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Human Autonomy Teaming↗
Engineering topics
Quang V Dao
Publications and source records attributed to Quang V Dao.
The High Density Vertiplex Advanced Onboard Automation Overview
While many studies have been performed examining Urban Air Mobility (UAM) operations from UAM Maturity Level (UML) UML-1 to UML-4, [1, 2] some uncertainty exists regarding the integration and role of onboard autonomous systems, airspace management systems, ground control and fleet management systems, and how they integrate with vertiport automation systems to ensure safe high-density future operations. One thrust of the Advanced Air Mobility (AAM) High Density Vertiplex (HDV) sub-project is to perform rapid prototyping and assessment of an Urban Air Mobility (UAM) Ecosystem within the terminal operational area to help inform future research investments and technology development. Another thrust within HDV is to perform integration, testing, and safety risk assessments required to acquire operational credit for several NASA small Unmanned Aerial Systems (sUAS) beyond visual line of sight (BVLOS) enabling technologies to expand test capabilities and to expedite technology transfer and ultimate effective usage. Both thrusts leverage sUAS to serve as surrogates for the highly-technologically-similar envisioned UAM aircraft as well as to provide significant contributions to sUAS Part-135 operators. This report provides an overview of the activities accomplished within the Advanced Onboard Automation (AOA) schedule work package of HDV.
Human Factors, Simulation↗
A Flight Replanning Tool for Terminal Area Urban Air Mobility Operations
In this presentation we describe and evaluate a flight replanning tool, called the trial planner, for terminal area air transport applications. The trial planner employs predefined airspace structures to generate rerouting options between vertiports. In a simplified definition, vertiports are facilities that provide services for managing the take-off and landing of autonomous or manned electric vertical take-off or landing (eVTOL) aircraft. The airspace structures involved in our test cases are arrival routes that consist of predefined entry points to which a transitional path is computed dynamically from the current position of the aircraft. Rerouting options include the transitional path and approach segment along the arrival route; these rerouting options are not vetted for potential conflicts with other operations until a human operator commits to a choice and forwards the flight plan modification for approval from an automated airspace management service. A selected rerouting option is executed by loading a flight plan file to the aircraft ground control station. We conducted a qualitative evaluation of the trial planner using ratings provided by flight crews and air transportation human factors experts with relevant experience from air traffic control. Evaluation criteria included trust in the route recommendations and adequate explanation for the route options. We detail the logic and implementation of the trial planner, as well as report the results of the evaluation of the implementation herein.
Trial planning↗
Progressive Development of Fleet Management Capabilities for a High Density Vertiplex Environment
The High Density Vertiplex (HDV) Sub-Project, as part of NASA’s Advanced Air Mobility (AAM) Project, has been developing a reference automation architecture with a far-term view of scalable, high-density operations in and around vertiport terminal areas. One of the components of that architecture under development has been focused on fleet management capabilities to support the management of multiple AAM operations from a supervisory role of a fleet manager. This capability relies on connectivity and information exchanges with other services for airspace and vertiport management as well as with flight crews responsible for operation execution. This paper will present this capability with a focus on its user interface developments as well as its integration into the simulation and flight testing performed as part of the HDV research roadmap.
AAM↗
High Density Vertiplex: Scalable Autonomous Operations Prototype Assessment Simulation
Urban Air Mobility is a rapidly growing topic within the field of aviation because of the impact a refined ecosystem and uncrewed aerial vehicles could have on modern society, such as urban air, cargo, and emergency transport. Before the UAM concept can be actualized, research is needed to understand how to integrate these new classes of vehicles and operations into the National Airspace System. One under-researched but critical piece of infrastructure required for UAM operations is Vertiport operations. Vertiports are the envisioned takeoff and landing locations for these uncrewed aerial vehicles. To accommodate the high use of the vertiport, new technologies and roles will be required for optimal use. At NASA, the High Density Vertiplex sub-project targets research into vertiports. The High Density Vertiplex team created their own Advanced Air Mobility ecosystem to test and evaluate different concepts and tools used to support higher density operations at vertiports. Part of the test and evaluation included the Prototype Assessment Operations simulation of high-density operations around a vertiport to study vertiport management and vertiport operations. The research team also evaluated how their simulated Urban Air Mobility ecosystem supported fleet managers, ground control station operators, and vertiport managers in execution of nominal and off-nominal high-density operations. Takeaways from this simulation helped the team evaluate well how the users of the ecosystem were able to use the components of the ecosystem to complete Urban Air Mobility missions.
Small Uncrewed Aerial Vehicle (sUAS)↗
A Human-In-The-Loop Simulation for Urban Air Mobility in the Terminal Area
In this paper researchers propose a human-in-the-loop experiment to study human performance when tasked with tactical deconfliction in terminal area air taxi operations. The air taxi operations being considered herein are an advanced air transportation concept called Urban Air Mobility (UAM). The UAM concept aims to support not only air taxi operations, but also package delivery and emergency response among other use cases. The key innovation over current air transportation lies with the introduction of highly automated aircraft and air traffic management systems. Development of the UAM system will include transitional midterm phases where some operational services will be provided by a mixture of automation and human actors. Midterm operations present a unique challenge, since the scope of responsibility of automated systems is largely undefined, suggesting the need for direct human participation with little to inform how much human intervention is necessary. Here it is assumed that traffic management responsibilities require coordination between human actors and automated systems and focus on arrival flows for midterm operations. In the proposed human-in-the-loop simulation, virtual UAM traffic is strategically deconflicted by a Provider of Services for UAM at departure, then tactically managed by a human at the arrival facility. Generated traffic consists of UAM participants flying in UAM exclusive airspace structures, thus isolated from traditional traffic. The human operator is tasked with managing spacing of arrival traffic and executing speed adjustments as deemed necessary. Researchers propose the investigation of three levels of automation assistance: 1) no assistance; 2) spacing violation detection; 3) spacing violation detection and speed adjustment recommendations. Quantitative measures like throughput and delay are used to assess the human's capacity for accommodating airborne delays. Qualitative evaluations such as surveys and open-ended feedback are used to gain insight into human factors. These factors could introduce additional capacity constraints on traffic, independent of physical or technical constraints. Although findings for this study will not be reported as the study has not yet been executed, the authors conclude with potential outcomes informed by previous simulations in the literature and suggestions for the structure and procedures of midterm human-automation air traffic management.
UAM↗
A Human-In-The-Loop Simulation for Urban Air Mobility in the Terminal Area
In this presentation we propose a human-in-the-loop experiment to study the potential impact of human engagement in tactical mitigation of delay in terminal area air taxi operations. The air taxi operations being considered herein is an advanced air transportation concept called Urban Air Mobility (UAM). The UAM concept aims to support not only air taxi operations, but also package delivery and emergency response among other use cases. The key innovation over current air transportation lies with the introduction of autonomous aircraft and autonomous air traffic management systems. Development of the UAM system will include transitional midterm phases where some operational services will be provided by a mixture of automation and human actors. Midterm operations present a unique challenge, since the scope of responsibility of automated systems is largely undefined, suggesting the need for direct human participation with little to inform how much human intervention is necessary. Here we assume that traffic management responsibilities require coordination between human actors and automated systems and focus on arrival flows for midterm operations. In the proposed human-in-the-loop simulation, virtual UAM traffic is strategically deconflicted by a Provider of Services for UAM at departure, then tactically managed by a human at the arrival facility. Generated traffic consists of UAM participants flying in UAM exclusive airspace structures, thus isolated from traditional traffic. The human operator is tasked with managing spacing of arrival traffic and executing speed adjustments as deemed necessary. We propose the investigation of three levels of automation assistance: 1) no assistance; 2) spacing violation detection; 3) spacing violation detection and speed adjustment recommendations. Quantitative measures like throughput and delay are used to assess the human's capacity for accommodating airborne delays. Qualitative evaluations such as surveys and open-ended feedback are used to gain insight into human factors. These factors could introduce additional capacity constraints on traffic, independent of physical or technical constraints. Although findings for this study will not be reported as the study has not yet been executed, we conclude with potential outcomes informed by previous simulations in the literature and suggestions for the structure and procedures of midterm human-automation air traffic management.
UAM↗