Jeff Homola

An Overview of Current Capabilities and Research Activities in the Airspace Operations Laboratory at NASA Ames Research Center

The Airspace Operations Laboratory at NASA Ames conducts research to provide a better understanding of roles, responsibilities, and requirements for human operators and automation in future air traffic management (ATM) systems. The research encompasses developing, evaluating, and integrating operational concepts and technologies for near-, mid-, and far-term air traffic operations. Current research threads include efficient arrival operations, function allocation in separation assurance and efficient airspace and trajectory management. The AOL has developed powerful air traffic simulation capabilities, most notably the Multi Aircraft Control System (MACS) that is used for many air traffic control simulations at NASA and its partners in government, academia and industry. Several additional NASA technologies have been integrated with the AOLs primary simulation capabilities where appropriate. Using this environment, large and small-scale system-level evaluations can be conducted to help make near-term improvements and transition NASA technologies to the FAA, such as the technologies developed under NASA’s Air Traffic Management Demonstration-1 (ATD-1). The AOL’s rapid prototyping and flexible simulation capabilities have proven a highly effective environment to progress the initiation of trajectory-based operations and support the mid-term implementation of NextGen. Fundamental questions about accuracy requirements have been investigated as well as realworld problems on how to improve operations in some of the most complex airspaces in the US. This includes using advanced trajectory-based operations and prototype tools for coordinating arrivals to converging runways at Newark airport and coordinating departures and arrivals in the San Francisco and the New York metro areas. Looking beyond NextGen, the AOL has started exploring hybrid human/automation control strategies as well as highly autonomous operations in the air traffic control domain. Initial results indicate improved capacity, low operator workload, good situation awareness and acceptability for controllers teaming with autonomous air traffic systems. While much research and development needs to be conducted to make such concepts a reality, these approaches have the potential to truly transform the airspace system towards increased mobility, safe and efficient growth in global operations and enabling many of the new vehicles and operations that are expected over the next decades. This paper describes how the AOL currently contributes to the ongoing air transportation transformation.

A Human-in-the-Loop Investigation of Multi-Sector Planning Operations for the NextGen Mid-Term

A human-in-the-loop simulation was conducted to evaluate a concept for introducing multi-sector trajectory planning operations into en route air traffic facilities in the NextGen Mid-Term timeframe. Multi-sector planning tools and procedures for local area traffic flow management were developed, and then tested using two different service provider team configurations. In one condition, local area flow planning was performed by the traffic management coordinator and area supervisor. A second condition added a new, dedicated multi-sector planner position to the planning team. A set of eight convective weather and traffic load scenarios was used to evaluate the operational feasibility, potential benefits, and tool performance requirements of each condition. Significant improvements in weather avoidance and controller workload were observed in the multi-sector planner condition but no significant improvement was observed in user efficiency. Results indicate that multisector planning operations are effective and feasible in either team configuration.

Transitioning Resolution Responsibility between the Controller and Automation Team in Simulated NextGen Separation Assurance

As part of an ongoing research effort on separation assurance and functional allocation in NextGen, a controller-in-the-loop study with ground-based automation was conducted at NASA Ames’ Airspace Operations Laboratory in August 2012 to investigate the potential impact of introducing self-separating aircraft in progressively advanced NextGen time-frames. From this larger study, the current exploratory analysis of controller–automation interaction styles focuses on the last and most far-term time frame. Measurements were recorded that firstly verified the continued operational validity of this iteration of the ground-based functional allocation automation concept in forecast traffic densities up to two times that of current day high altitude en-route sectors. Additionally, with greater levels of fully automated conflict detection and resolution as well as the introduction of intervention functionality, objective and subjective analyses showed a range of passive to active controller–automation interaction styles between the participants. Not only did the controllers work with the automation to meet their safety and capacity goals in the simulated future NextGen timeframe, they did so in different ways and with different attitudes of trust/use of the automation. Taken as a whole, the results showed that the prototyped controller–automation functional allocation framework was very flexible and successful overall.

Concept Investigation via Air-Ground Simulation with Embedded Agents

Next Generation Air Transportation System (NGATS) concepts require design and analysis of interactions involving human operators and new automation tools. Research is exploring how air-ground simulations with embedded agents can complement human-in-theloop simulations for this purpose. This paper describes research toward integrating computational air traffic controller agents into a large-scale distributed simulation in the Airspace Operations Laboratory (AOL) at NASA Ames Research Center. Before detailing the agent model and architecture and discussing simulation integration issues, the paper describes a methodology for using agents to understand human-system integration issues and illustrates how the methodology can be applied to an example concept.

NASA UAS traffic management national campaign: Operations across Six UAS Test Sites

NASAs Unmanned Aircraft Systems Traffic Management research aims to develop policies, procedures, requirements, and other artifacts to inform the implementation of a future system that enables small drones to access the low altitude airspace. In this endeavor, NASA conducted a geographically diverse flight test in conjunction with the FAAs six unmanned aircraft systems Test Sites. A control center at NASA Ames Research Center autonomously managed the airspace for all participants in eight states as they flew operations (both real and simulated). The system allowed for common situational awareness across all stakeholders, kept traffic procedurally separated, offered messages to inform the participants of activity relevant to their operations. Over the 3-hour test, 102 flight operations connected to the central research platform with 17 different vehicle types and 8 distinct software client implementations while seamlessly interacting with simulated traffic.

Exploring management of arrival spacing using route extensions with terminal spacing tools

Airports with shared runway operations between arrivals and departures can experience severe departure gridlock and delays during a heavy arrival push due to insufficient gaps in the arrival stream for aircraft to depart. The problem is accentuated in situations when a large gap in the arrival spacing has to be created at the last minute due to wake vortex separation requirements. At LaGuardia airport, wake vortex separation problems arise when a heavy jet, such as a B757, departing on Runway 31 needs additional spacing between arrivals on Runway 22. A standard solution for controllers in many airports in situations such as this is to extend the downwind leg of arrival aircraft to create extra space between the arrivals. The question addressed in this paper is how such route extensions would work with terminal scheduling operations, namely (1) the Terminal Sequencing and Spacing (TSS) tools and (2) a new scheduling tool which increases the availability of gaps for departure aircraft-Departure Sensitive Arrival Spacing (DSAS). In a simulated LaGuardia airport (LGA) Terminal Radar Approach Control (TRACON) airspace, two new RNAV arrival routes were created along with extensions to these routes. The arrival route from the south had a downwind leg extension near the airport in the final sector. The arrival route from the north had an extension in a feeder sector further from the airport. An exploratory one-hour run with the route extensions was compared to an hour run without the extensions. Topics included in this paper are 1) how the route extensions were developed, 2) a procedure outlining how the aircraft could be scheduled to the extensions and who would do it, and 3) the results of the exploratory run compared to the original run without the extensions. The results indicated that the extended downwind leg route helped to create a B757 departure gap in the middle of a packed arrival stream, resulting in a reduction of 11 minutes in average wait time for the B757s, but at a cost of increased controller self-reported workload from low to moderate.