NASA Ames meeting to shape framework for routine autonomous multi-aircraft operations

MOFFETT FIELD, Calif. - The National Aeronautics and Space Administration (NASA)-sponsored Routine Autonomous Multi-Aircraft Operations Working Group is advancing efforts to enable routine, autonomous, multi-aircraft operations in the national airspace by identifying and addressing technical, operational, and regulatory barriers to scale.

Formerly known as the m:N Working Group, this body brings together stakeholders from government, industry, and academia to determine how multiple human operators can safely oversee multiple autonomous aircraft in shared airspace environments.

Uncrewed aircraft systems are evolving as a transformational technology with applications ranging from urban air taxis and cargo delivery to disaster response, firefighting, and military logistics. To realize that potential and support expected fleet growth, operators must be able to scale safely from one-to-one control models to supervisory control of multiple aircraft.

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Aptima Inc. in Woburn, Mass., under a NASA award, is applying its expertise in human-autonomy teaming to support the initiative. The company facilitated the Working Group's biannual meeting in July at NASA Langley Research Center and is supporting the upcoming meeting 3-5 March at the NASA Ames Research Center at Moffett Field, Calif.,, where participants will develop technical white papers and address challenges associated with enabling multi-aircraft operations.

Humans in the loop

A central focus of the effort is determining the minimal number of human operators, m, who can safely oversee growing numbers of autonomous aircraft, N, without cognitive overload, underload, or degraded performance.

Scaling operations across domains will require one operator controlling multiple aircraft, known as 1:N, or multiple operators managing multiple aircraft, known as m:N. During flight, operators may need to hand off aircraft at different phases, such as takeoff or landing, or in response to mechanical failures or changing airspace density, conditions that can increase workload and require redistribution of tasks or assets.

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Subgroups

The Interventions and Exceptions subgroup is developing modeling and simulation methods to validate the safety of m:N operations by quantifying when human operators must intervene. Large-scale scenario simulations are intended to help fleet operators assess safety performance before seeking certification from the Federal Aviation Administration.

The Small Unmanned Aircraft Systems subgroup is identifying regulatory gaps in autonomous multi-aircraft operations, particularly related to beyond visual line of sight flight. The effort aims to provide policymakers with technical information aligned with evolving Advanced Air Mobility concepts and emerging operational use cases.

The Scalable Remote Crew Design Considerations subgroup is focused on best practices for task allocation, role definition, and handoffs among remote crew members in multi-aircraft operations. This includes lessons learned for operator procedures, original equipment manufacturer system design, and third-party service provider integration.

The m:N Validation and Verification subgroup is developing an evaluation framework and associated metrics for workload, system performance, and safety to support scalable operational approval.

The System of Systems Design subgroup is defining baseline considerations for robust management of multi-aircraft operations in fully integrated, non-segregated airspace environments.

A proposed new standard under development within ASTM International aims to provide a flexible framework for analyzing and implementing autonomy in aviation by focusing on how autonomy affects the role of the human operator rather than defining rigid levels of automation.

From a military perspective, the U.S. Army Aviation and Missile Center highlighted challenges in managing multiple systems under contested conditions, including jamming and operational disruptions. Officials emphasized the integration of artificial intelligence and machine learning into human-machine interfaces, with a long-term vision of humans and autonomous agents operating as peer partners.

The Working Group ultimately seeks to produce technical insights and operational data to inform the evolution of future standards and regulatory frameworks supporting routine, autonomous, multi-aircraft operations across civil and defense domains.

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