BAA Topics of Interest Amendment 014.pdf

BAA FAA Aviation Research 2025 Solicitation Number: 692M15-25-R-00004

Federal Aviation Administration William J. Hughes Technical Center for Advanced Aerospace Atlantic City International Airport

Atlantic City, NJ

BROAD AGENCY ANNOUNCEMENT

AVIATION RESEARCH 2025

TOPICS OF INTEREST

Amendment 014

November 3, 2026

The following is a list of BAA Topics of Interest of Aviation Research required by the FAA Technical Center. This BAA is an open request for white paper submittals at any time until the expiration of the BAA or until the Topic is removed. White papers and proposals will be assessed according to the instructions and criteria contained in the BAA. Offerors are invited to submit brief descriptive white papers relevant to a Topic or Topics described within the BAA. Each Topic identifies a Technical POC to whom questions relating to a particular Topic must be directed.

AVIATION RESEARCH AIRPORT PAVEMENTS (ARAP)

Topic Number: ARAP0010: This topic has been removed Rational Overload Criteria for Airport Pavements in the ACR/PCR Method

Topic Number: ARAP0012: This topic has been removed Engineering Analysis of Field Monitoring and Instrumentation Data

Topic Number: ARAP0014: This topic has been removed Advancing Pavement Condition Assessment Practices for Airport Pavements

Topic Number: ARAP0015: This topic has been removed Advancing Concrete Strength Evaluation for Airport Pavement Design and Construction

AVIATION RESEARCH AIRPORT SAFETY (ARAS)

Topic Number: ARAS0014:

Cybersecurity Concerns with Autonomous Ground Vehicle Systems (AGVS) in the Airport Environment

Technical POC: William Gorman; William.R.Gorman@faa.gov Copy: 9-ACT-AAQ-600-BAA@faa.gov

Background:

The integration of Autonomous Ground Vehicle Systems (AGVS) within airport environments— both in the United States (U.S.) and internationally—has accelerated due to growing demands for efficiency and automation. Airports have begun testing a wide variety of AGVSs across various functions, including but not limited to self-driving jet bridges, aircraft tugs, baggage carts, de-icing vehicles, employee shuttles, mowers, foreign object debris collection, and perimeter inspections. Numerous airport sponsors and operators in the U.S. are testing/demonstrating AGVS with the intention of integrating them into their daily operations. The introduction of AGVS into the airport environment poses a new set of safety, integration, and validation challenges.

One area of concern centers on the cybersecurity risks to AGVS. This Broad Agency Announcement (BAA) topic is to address the need to better understand the cybersecurity risks and mitigations associated with the introduction of AGVS into the airport environment.

Purpose:

The purpose of this topic is for interested parties to conduct applied research regarding innovative ways to assist airport sponsors and stakeholders to better understand how to protect against AGVS cyberattacks that could lead to malicious actions in the airport environment, specifically non-movement areas, movement areas, and remote areas (e.g., fenceline, etc.) of an airport.

Requirements:

The Federal Aviation Administration (FAA) seeks white papers to address the specific areas listed below; however, submittals are not limited to these areas.

• System Components at Risk - Provide approaches regarding how to identify the full set of system elements that are prone to potential attacks. This may extend beyond just the AGVS; and, for example, may include system-level components, such as a centralized command and control (C2) system and tablets or smart phones that may be used by airport personnel in the field to communicate and control the AGVS.

• AGVS Validation - Provide approaches regarding how to best identify standards, processes, and testing to identify and mitigate cybersecurity issues after an AGVS is operational at an airport.

mailto:William.R.Gorman@faa.gov mailto:

• Pre-emptive Protection against Attacks - Provide innovative ideas regarding how to identify best practices and approaches to protect against AGVS cybersecurity attacks during airport operations.

• Recognizing an Attack - Provide innovative ideas regarding how to identify both attempted and successful AGVS cybersecurity attacks during real-time operations and during periodic, off-shift evaluations.

• Responding to a Successful Attack - Provide innovative ideas regarding how to address the scenario where a successful cybersecurity attack has been identified o Mitigate the immediate risk o How to safely reintroduce the AGVS back into normal operations

Period of Performance/Rough Order of Magnitude:

The Period of Performance for projects under this topic is anticipated not to exceed 12 months.

Topic Number: ARAS0015 Lost Communication Concerns with Autonomous Ground Vehicle Systems (AGVS) in the Airport Environment

The integration of Autonomous Ground Vehicle Systems (AGVS) within the airport environment—both in the United States (U.S.) and internationally—has accelerated due to growing demands for efficiency and automation. Airports have begun testing a wide variety of AGVSs across various functions, including but not limited to self-driving jet bridges, aircraft tugs, baggage carts, de-icing vehicles, employee shuttles, mowers, foreign object debris collection, and perimeter inspections. Numerous airport sponsors and operators in the U.S. are testing/demonstrating AGVS with the intention of integrating them into their daily operations.

The introduction of AGVS into the airport environment poses a new set of safety, integration, and validation challenges.

One area of concern centers on the loss of communication between the command-and-control system (C2) monitored by a human-in-the-loop and the AGVS. This Broad Agency Announcement (BAA) topic is to address the need to better understand the circumstances regarding how to approach loss of communication issues with the introduction of AGVS into the airport environment.

Purpose:

The purpose of this topic is for interested parties to conduct applied research regarding innovative ways to better understand how AGVS will operate in the event of loss of communications/control and lost link to ensure the safety of aircraft and airport operations. This includes what procedures can be adapted to address loss of communications/control, lost link, or other AGVS failures.

Requirements:

https://usfaa-my.sharepoint.com/personal/ryan_king_faa_gov/Documents/AAA%20E263%20Emerging%20Tech%202025/AGVS/AGVS%20Research%20Request%20Feb%202026/BAA%20Lost%20Comm/9-ACT-AAQ-600-BAA@faa.gov

The Federal Aviation Administration (FAA) seeks white papers to address the specific areas listed below; however, submittals are not limited to these areas.

• Identification of Procedures and Vehicle Behavior in the Event of Lost Communications- AGVS are autonomous but typically still maintain a wireless communication link with their respective C2, monitored by a human-in-the-loop; where through different wireless platforms, commands may be issued to start or end specific tasks or abort the mission in the event of a problem. Due to the nature of wireless communication, this communication link may be lost at times, usually temporarily, but possibly for longer durations.

o Identify (1) the varying processes AGVS companies currently follow and, where appropriate, (2) provide updates to existing processes or (3) recommend new processes that should be followed in the event of a lost link with AGVS operating in airport movement areas. Different lost link time durations (e.g., sporadic vs.

longer term) and the purpose or AGVS vehicle type (e.g., mowers, luggage delivery, etc.) should be considered.

o Research should consider vehicle behavior in the event of loss of communication

– e.g., will the vehicle continue and complete its task, under what circumstances should the vehicle immediately stop, under what conditions should the vehicle go to a safe area, and when should the vehicle abort the mission and return to its home base location.

o Provide innovative ideas to identify procedures to follow when the communication link is restored – e.g., remain stationary, resume the mission, move to a temporary safe location, or return to the home base location.

• Safety Analysis – Identify a safety analysis regarding the procedures and vehicle behavior in the event of lost communications.

Period of Performance/Rough Order of Magnitude:

The Period of Performance for projects under this topic is anticipated not to exceed 12 months.

Topic Number: ARAS0016 Spectrum Interference Concerns with Autonomous Ground Vehicle Systems (AGVS) in the Airport Environment

The integration of Autonomous Ground Vehicle Systems (AGVS) within the airport environment—both in the United States (U.S.) and internationally—has accelerated due to growing demands for efficiency and automation. Airports have begun testing a wide variety of AGVSs across various functions, including but not limited to self-driving jet bridges, aircraft tugs, baggage carts, de-icing vehicles, employee shuttles, mowers, foreign object debris collection, and perimeter inspections. Numerous airport sponsors and operators in the U.S. are testing/demonstrating AGVS with the intention of integrating them into their daily operations.

The introduction of AGVS into the airport environment poses a new set of safety, integration, and validation challenges.

mailto:9-ACT-AAQ-600-BAA@faa.gov

One area of concern centers on the impact by AGVS on frequencies used by other airport equipment. This Broad Agency Announcement (BAA) topic is to address the need to better understand the possibility of spectrum interference associated with the introduction of AGVS into the airport environment.

Purpose:

The purpose of this topic is for interested parties to conduct applied research regarding innovative ways to better understand and mitigate potential spectrum interference risks in the airport environment due to the introduction of AGVS. Research will explore: (1) The spectrum impact that AGVS may introduce to FAA Navigational Aids (NAVAIDS)/airport equipment (e.g., avian radar, unmanned aircraft detection systems, foreign object debris detection systems, and other equipment) and (2) the spectrum impact that FAA NAVIDS/airport equipment may have on AGVS.

Requirements:

The Federal Aviation Administration (FAA) seeks white papers to address the specific areas listed below; however, submittals are not limited to these areas.

• Identify Airport Risks o Propose a process identifying the list of frequencies used by AGVS, frequencies used by airport communication, navigation, and surveillance (CNS) infrastructure (e.g., with FAA NAVAIDS), and how to identify the spectrum interference risks to both FAA NAVAIDS/airport equipment and to the AGVS. The AGVS frequencies being employed may extend beyond just the vehicle and include related equipment (e.g., command and control equipment and vehicle communication devices).

o Provide information regarding how to determine a governance policy to identify and address all spectrum interference issues

The Period of Performance for projects under this topic is anticipated not to exceed 12 months.

AIRPORT RESEARCH STRUCTURES AND MATERIALS

(ARSM)

Topic Number: ARSM0001:

Structural Integrity of Metallic Components

Technical POC: Dr. Edward Weinstein Edward.Weinstein@faa.gov Sohrob Mottaghi Sohrob.Mottaghi@faa.gov

Copy: 9-ACT-AAQ-600-BAA@faa.gov

Background:

FAA Order 8110.107B prescribes the use of the Monitor Safety/Analyze Data (MSAD) process to make Continued Operational Safety (COS) decisions based on risk analysis methodologies. This order explains how the MSAD process analyzes COS data and monitors safety in aircraft fleets throughout their life cycle. The MSAD process helps the FAA identify hazards in in-service aircraft fleets and mitigate safety risks across the fleet by analyzing aviation safety data. MSAD also identifies other causes of hazards that cannot be addressed by aircraft fleet mitigations, such as issues related to product or part design or manufacturing. Additionally, MSAD discusses a data-driven, risk-based approach for follow-on actions, such as airworthiness directives (AD), special airworthiness information bulletins (SAIB), and others.

Purpose:

The purpose of this project is to obtain data that can be used in risk assessment and the development of guidance material for airplane structural integrity concerns in metallic structures of transport category airplanes, aligned with MSAD as prescribed by FAA Order 8110.107B.

Requirements:

The FAA will consider white papers for research outlining the sources, capabilities, and methods to obtain MSAD compliance data that could help the FAA improve its risk assessment methods for safety concerns related to the structural integrity of metallic components.

Period of Performance/Rough Order of Magnitude:

The Period of Performance (PoP) and Rough Order of Magnitude (ROM) will be determined based on the proposed work, deliverables, and project objectives for each proposed activity. Continued efforts upon the completion of each milestone or deliverable are at the discretion of the FAA, based on performance and results. These efforts are anticipated to be funded annually, subject to the availability of funds. There are currently no set parameters for these elements.

mailto:Edward.Weinstein@faa.gov mailto:Sohrob.Mottaghi@faa.gov

AVIATION RESEARCH STRUCTURES AND

PROPULSIONS (ARSP)

Topic Number: ARSP0001:

Nickel Anomaly Fatigue Testing

Technical POC: Daniel Cordasco, Daniel.Cordasco@faa.gov

Service experience of aircraft turbine engines has demonstrated manufacturing and service-induced anomalies still occur which can degrade the structural integrity of turbine engine rotors leading to premature and abrupt failure jeopardizing passenger safety. National Transportation Safety Board (NTSB) findings from the uncontained engine failure on American Airlines (AA) Flight 383 in Chicago determined that the high-pressure turbine disk failed due to cracks consistent with low-cycle fatigue (LCF). The LCF cracks initiated from an undetected nickel material anomaly known as a dirty white spot (DWS) which formed during the processing of nickel alloy 718 used to manufacture the disk. The Federal Aviation Administration (FAA) requires a better understanding of the LCF behavior of nickel alloy in the presence of anomalies such as DWS.

Purpose:

The purpose of this Topic is to conduct research to develop fatigue crack growth (FCG) methods to address engine rotor failure mechanisms due to nickel material anomalies. Specifically, research will be performed to test wrought nickel alloy fatigue specimens with subsurface melt anomalies, such as DWS, to understand the effects on LCF life.

Requirements:

The FAA would like white papers to address the specific areas listed below; however, submittals are not limited to these requirements.

i. LCF testing of premium quality aerospace grade double-melt or triple-melt wrought nickel alloy material with a minimum ten (10) known or suspected (from inspection) subsurface melt anomalies such as DWS

ii. Determination of cycles to failure for LCF specimens containing subsurface anomalies as well as sufficient baseline pedigree testing of anomaly-free specimens

iii. Post-test fractography and metallography necessary to identify the size and type of anomaly, determine fatigue crack growth rate, and crack incubation/nucleation period

iv. Outreach and teaming plan to collaborate with subject matter experts (SME) from multiple commercial aircraft engine manufacturers on fatigue of aerospace grade wrought nickel alloy. SME input can include, but is not limited to, defining the specific LCF test conditions and review of the test results necessary to facilitate industry-wide adoption.

mailto:Daniel.Cordasco@faa.gov

Period of Performance (PoP)/Rough Order of Magnitude (ROM):

The PoP is anticipated to be twenty-four (24) months. The ROM for this research is estimated to be approximately $350,000.

Topic Number: ARSP0002:

Hydrogen Aviation Safety Research

Technical POC: Kendall J. Laster; Kendall.J.Laster@faa.gov

Background:

The emergence of hydrogen as a primary energy carrier for aviation propulsion represents potentially one of the most significant technological transitions in the history of civil aviation.

Hydrogen-powered aircraft spanning fuel cell electric propulsion, hydrogen combustion engines, and hybrid configurations offer the potential for substantially reduced carbon emissions and are actively developed by airframe manufacturers, propulsion OEMs, and emerging aviation companies worldwide.

The integration of hydrogen propulsion into civil aviation introduces a broad range of safety, operational, infrastructure, and regulatory challenges that are not fully addressed by existing FAA regulations, Advisory Circulars, or industry standards. Hydrogen’s unique physical and chemical properties including its low volumetric energy density requiring large, probably cryogenic tanks, wide flammability range, low ignition energy, high buoyancy, and potential for material embrittlement require new approaches to hazard detection, consequence modeling, risk management, and operational integration.

At the forefront of our efforts is aviation safety. In December 2024 the FAA published its Hydrogen-Fueled Aircraft Safety and Certification Roadmap outlining current knowledge, key research priorities, and collaborative efforts essential to enabling the safe use of hydrogen in civil aviation aircraft. Concurrently, the FAA, in collaboration with other agencies, is identifying regulatory gaps and targeting safety research to address them. Through these initiatives, the FAA aims to proactively build the research foundation necessary to support safe hydrogen aviation operations, inform regulatory development, and seamlessly integrate hydrogen-powered aircraft into the National Airspace System (NAS). To support this mission, this Call invites white papers from academia, industry, research institutions, and other qualified organizations across all relevant technical disciplines.

Purpose:

The purpose of this Topic is to advance knowledge and understanding across the full spectrum of hydrogen aviation safety from fundamental detection and dispersion science to operational integration and regulatory framework development. Research conducted under this Topic will produce findings, data, and recommendations that support FAA’s mission to ensure the safest and most efficient aerospace system in the world as hydrogen aviation technologies mature toward commercial deployment.

The FAA encourages innovative, interdisciplinary white papers and welcomes teaming arrangements between industry partners, academic institutions, and research organizations.

mailto:Kendall.J.Laster@faa.gov

Requirements:

The FAA would like white papers to address one or more of the following Research Areas listed below. White papers are not limited to these areas; novel approaches and emerging research directions are encouraged.

Research Area 1 — Hydrogen Leakage Detection The most significant risk for hydrogen in aviation is fire and explosion. A root cause for this hazard is leakage, resulting in stable flames even at much lower rates than currently considered.

Research is needed addressing the detection, monitoring, and characterization of hydrogen gas leaks in aviation-relevant environments. White papers may address, but are not limited to:

• Development or adaptation of hydrogen sensor technologies for use in aircraft, airport infrastructure, and ground support equipment environments

• Sensor array design, signal processing, and data fusion approaches to improve detection accuracy and reduce false alarms

• Sensor performance, reliability, calibration, and maintenance under aviation operational conditions

• Integration of hydrogen detection systems with existing airport and aircraft safety architecture

• Novel or emerging detection modalities applicable to aviation hydrogen safety

Research Area 2 — Hydrogen Dispersion and Simulation Research addressing the modeling, simulation, and experimental characterization of hydrogen release, both liquid and gaseous, and dispersion behavior in aviation environments. White papers may address, but are not limited to:

• Computational modeling and simulation of hydrogen dispersion in aviation geometries including aircraft (e.g., powerplant installations), hangars, fueling stations, and airport facilities

• Experimental validation of hydrogen dispersion models using laboratory or field test data

• Simulation of ignition, combustion, and consequence scenarios associated with hydrogen releases

• Development of tools, datasets, or methodologies to support hydrogen safety analysis and facility design

• Novel modeling approaches including machine learning, reduced-order models, or surrogate methods applied to hydrogen dispersion

Research Area 3 — Hydrogen Risk Assessment and Mitigation Research is conducted by researching the identification, quantification, and mitigation of risks associated with hydrogen use in aviation. White papers may address, but are not limited to:

• Quantitative risk assessment methods for hydrogen release and ignition scenarios in aviation settings

• Failure analysis of hydrogen storage, distribution, and fueling components and systems

• Understanding and risk characterization of novel phenomena, such as detonations in liquid hydrogen phase, ignition and flame propagation upon spills on water, or secondary explosions upon releases

• Engineering controls, safety systems, and mitigation strategies for hydrogen hazards in aviation environments

• Incident response frameworks, emergency procedures, and training standards for hydrogen aviation events

• Material compatibility, hydrogen embrittlement, and structural integrity considerations for aviation hydrogen systems

Research Area 4 — Integration of Hydrogen-Powered Aircraft in the National Airspace System (NAS) Research addressing the broad operational, infrastructure, regulatory, and safety challenges associated with integrating hydrogen-powered aircraft into the NAS. White papers may address, but are not limited to:

• Hydrogen aircraft operational safety within the NAS alongside conventional aircraft

• Airport and airspace infrastructure readiness and capability gaps for hydrogen aviation operations

• Certification, airworthiness, and regulatory framework development for hydrogen-powered aircraft

• Air traffic management procedures and protocols for hydrogen aircraft operations and emergencies

• Ground handling, fueling, and servicing standards for hydrogen aircraft at commercial and general aviation airports

• Workforce training, qualifications, and readiness requirements to support safe hydrogen aviation operations

• Environmental and community impacts of hydrogen aviation operations within the NAS

• Risk assessment and safety management for hydrogen aircraft fleet operations in the NAS

• Innovative approaches to any other aspect of hydrogen-powered aircraft NAS integration not listed above

Period of Performance/Rough Order of Magnitude:

Efforts not exceeding 36 months will be considered. These efforts are subject to availability of funds. ROM (Rough Order of Magnitude) for this research is anticipated not to exceed $650,000 per award, per period of performance for any awards made under this topic.

AVIATION RESEARCH SOFTWARE & SYSTEMS

(ARSS)

Topic Number: ARSS0008: Topic is On Hold pending an update to topic Complex Digital Systems

Technical POC: Srini Mandalapu; Srini.Mandalapu@faa.gov

Aircraft manufacturers and modifiers are developing highly integrated and distributed system architectures with multiple aircraft functions. New methodologies, tools, and Artificial Intelligence/Machine Learning (AI/ML) applications are planned for use in airborne systems.

Aircraft system element development is also evolving due to technological advancements and the desire to reduce costs and time to market. The aviation industry seeks assurance criteria and guidance to address the growing complexity introduced by new technologies in airborne systems. This includes exploring innovative assurance approaches alongside the development of new methodologies, tools, software implementations, and AI/ML applications.

Safe use of the new technologies, tools, and commercial off-the-shelf (COTS) components may not have been demonstrated in embedded aircraft equipment; which may introduce a safety risk for undetected errors with failure manifestation at the aircraft level; and may only be suitable to meet safety regulations when new, revised or additional assurance activities are also included. For example, industry is proposing to use AI where little is known about the validation and verification of AI in a safety critical environment. In addition, use of autonomous (non-piloted) aircraft are also being proposed under conditions where, currently, regulations and guidance do not exist. These methodologies, individually or in combination, could introduce unknown risk if not properly addressed early in the development process.

The Federal Aviation Administration (FAA) plans to conduct research to proactively address certification issues that may arise due to the introduction of new methodologies, tools, and techniques with a particular focus on AI/ML applications and autonomy that can potentially cause new failure conditions posed by the rapid or new and novel development processes on highly integrated and distributed systems. The research results will be used in improving the assurance standards, guidance, and training material for certification engineers.

Purpose:

The purpose of this Topic is to address the use of new methodologies and techniques particularly AI/ML applications and software assurance in safety critical airborne systems by identifying assurance concerns, validation and verification issues, and potential mitigation techniques to address risks early in the development process. Also, the FAA is studying new assurance processes that can address the safety risk that may have been introduced while implementing newer architectures, tool, and technologies. The Topic also further explores the validity of the currently-recognized development assurance standards for highly integrated and distributed systems and determine if newer development assurance approaches are needed mailto:Srini.Mandalapu@faa.gov to demonstrate compliance with the regulations in light of the rapid advances in design and development of highly integrated and distributed aircraft systems. Furthermore, to address errors originating from requirement issues and minimize the risk of single point of failure, the research will explore novel validation approaches like diverse specifications.

The goal is to develop recommendations that assist in the certification and assurance of highly integrated, distributed, and complex digital aircraft systems, including systems development processes and architectures, requirements validation and integration; use of COTS devices, new and novel electronic hardware and software implementation techniques, tools, methods, and processes; continued operational safety; and streamlining approaches for safety assurance and aircraft certification.

The FAA would like white papers to address the specific areas listed below; however, submittals are not limited to these requirements. Innovative ideas are welcome and encouraged.

The research should address airborne system safety and assurance issues in the following specific areas or combination of areas, but not be limited to:

• Assurance and verification Methodologies for Automation using AI/ML in safety critical airborne systems.

• Risk mitigation methodologies and approaches to address the unknown behavior of new technologies such as AI/ML.

• Pilot studies to evaluate the use of new assurance approaches, e.g., Overarching

Properties as Alternative Means of Compliance.

• Use of Formal Methods and Assurance Cases, and their use in aircraft certification.

• Explainability approaches and recommendations of AI/ML implementations for different level of autonomy and design assurance levels.

• Explore safety improvements through diverse specifications developed from multiple prospectives.

• Explore the use of Large Language Models to classify latent risks in aviation systems.

For the research areas above, the FAA aims to:

• Assess alternative assurance approaches to currently recognized standards and their effectiveness in addressing safe implementation of new technologies such as AI/ML and addressing the safe implementation of autonomy.

• Identify the issues, challenges, and gaps in the current standards/guidance in assuring new complex airborne systems and components.

• Develop criteria, mitigation approaches, recommendations, training material, or position papers.

The results of the research will be used by FAA to develop/modify standards, guidance, or training material to support the FAA’s certification workforce.

The Period of Performance (PoP)/Rough Order of Magnitude (ROM) will be determined based on the projects proposed. However, the tasks lasting for more than 3 years will NOT be considered.

Continued efforts at the completion of each milestone or deliverable are at the discretion of the FAA, based on performance and results. These efforts are anticipated to be funded annually, subject to availability of funds. ROM for this research is expected not to exceed $400,000.00 per project, per fiscal year for any awards made under this announcement.

Topic Number: ARSS0009:

Future of Oversight

Technical POCs: Huasheng Li: Huasheng.Li@faa.gov Michael Bartron: Michael.S.Bartron@faa.gov

Copy: 9-ACT-AAQ-600-BAA@faa.gov

Background:

The Federal Aviation Administration (FAA) continuously improves the effectiveness of its oversight to ensure the aviation system meets public expectations. Oversight activities encompass the breadth of FAA actions, such as regulation, safety promotion, approvals, surveillance, and the compliance program. The scope and method of these activities have largely been developed over decades of experience and in response to in-service events.

Modern concepts for safety systems and data capture/analysis, and system modeling provide an opportunity to transform how oversight can be used effectively to assure the public’s expectations for safety. Industry and the FAA are embracing Safety Management Systems (SMS). In 2024, the FAA expanded the regulatory applicability of SMS requirements for certain industry segments. FAA continues to encourage other industry segments to voluntarily implement SMS. FAA is also evolving its State Safety Program1. New data sources and methods have become available, and new tools are being developed using technologies such as AI/ML (Artificial Intelligence/Machine Learning). To support the aviation system’s adoption of these opportunities while meeting safety expectations, the FAA must explore new methods for developing, monitoring, and informing changes to its oversight.

The FAA expects the foundation of a future oversight system will use performance-based regulations, systems, measures, tools, and procedures that proactively monitor the performance of compliance and safety promotion actions and be capable of making timely adjustments to ensure the rigor of oversight achieves a level of safety that satisfies expectations. A mature company SMS, delivering on a commitment to compliance and safety, enables the FAA to change its engagement to focus on areas of highest risk and to monitor the effectiveness of the company’s safety systems to recognize when intervention is needed.

1 U.S. State Safety Program document:

https://www.faa.gov/sites/faa.gov/files/about/initiatives/sms/reference_library/AVS-210503-001-Supporting- US_State_Safety_Program.pdf mailto:Huasheng.Li@faa.gov mailto:Michael.S.Bartron@faa.gov mailto:9-ACT-AAQ-600-BAA@faa.gov https://www.faa.gov/sites/faa.gov/files/about/initiatives/sms/reference_library/AVS-210503-001-Supporting-US_State_Safety_Program.pdf https://www.faa.gov/sites/faa.gov/files/about/initiatives/sms/reference_library/AVS-210503-001-Supporting-US_State_Safety_Program.pdf

Purpose:

The purpose of this BAA research topic is to explore new concepts for oversight that would modernize the FAA’s procedures and systems and enable the FAA to evaluate the effectiveness of oversight activities. This will require methods to evaluate the performance of oversight systems as well as to identify comprehensive and transparent performance indicators for continuous improvement. The research will explore oversight performance and compare the effectiveness and cost-efficiency among oversight systems across various aviation segments.

The analysis will identify the characteristics that lead to effective oversight. Considerations include:

• How to evaluate the effectiveness of oversight systems and define the success of oversight?

• How to estimate safety expectations for and of aviation operations?

• How to effectively communicate safety intentions and objectives between the FAA, industry, and the public.

• How to match oversight results with safety expectations, intentions, and objectives?

• How to transform FAA oversight to leverage effective Safety Management Systems?

• How can oversight evaluate the effectiveness of a Safety Management System?

• How to integrate the oversight functions across FAA services and offices to achieve safety goals and objectives.

• Other proposals to modernize how the FAA conducts oversight.

The FAA seeks white papers to address the areas listed below. However, white papers are not limited to these areas:

• Traditional Oversight and SMS-based Oversight: The performance-based intentions of safety management systems offer flexibility and scalability benefits to industry while also challenging regulators to develop oversight approaches that support these industry benefits. The FAA has an interest in comparing traditional, prescriptive-based oversight and SMS-based oversight approaches regarding identified findings, resources applied, and other pertinent conclusions in a real-world setting, to gain insight into the lessons learned in implementing these two approaches.

• Safety workforce of the future: The transition from traditional compliance-based oversight to performance-based oversight warrants changes in the FAA oversight workforce. The FAA is interested in identifying the characteristics of a future safety oversight workforce and recruiting and developing pathways to transform it into such a workforce.

• Measures of effectiveness of FAA involvement in the oversight actions of certification and surveillance: As a regulator, the FAA is involved in every stage of certification and surveillance processes and takes oversight actions as warranted and is seeking to identify new and novel measurements of the effectiveness of the FAA’s roles in certification and surveillance.

• Comparison of aviation oversight to alternate industries: Many industries, besides aviation, require SMS or similar management system-based oversight, such as the financial sector, possibly the health sector, maritime, transit, etc. The FAA is interested in lessons learned from those industries, comparing effectiveness and efficiency, and normalizing for differences in those industries.

• Aviation safety risk management cooperation, where the FAA promotes safety and enables industry: Safety information sharing and safety risk management cooperation are critical to the safety in the aviation industry but are often restricted due to information privacy and trust issues among companies. The FAA is interested in identifying the challenges and receiving recommendations on promoting or enabling data/information sharing and protection, and safety risk management cooperation among entities who are required to comply with 14 CFR Part 5 (SMS) and among entities who maintain an SMS yet may not be required to comply with 14 CFR Part 5 (SMS).

The results from this study will be used to improve the FAA’s integrated oversight practice.

The Period of Performance (PoP)/Rough Order of Magnitude (ROM) will be generally determined based on the projects proposed. However, tasks lasting for more than 3 years will NOT be considered.

Continued efforts at the completion of each milestone or deliverable are at the discretion of the FAA, based on performance and results. These efforts are anticipated to be funded annually, subject to the availability of funds. There are currently no set parameters for the ROM.

Topic Number: ARSS0010 A Training Framework for Reducing Pilot Decision-Making Errors

Technical POCs: Andrew Cheng Andrew.Cheng@faa.gov Jeffery Schroeder Jeffery.Schroeder@faa.gov;

Copy: 9-ACT-AAQ-600-BAA@FAA.gov

Background:

Pilot error remains a leading contributing factor to aviation accidents worldwide. Errors in pilot decision making, including cognitive biases, can have negative or catastrophic consequences in safety critical environments. It is imperative to incorporate practices into training programs to help pilots identify these errors, as well as instruct pilots on how to mitigate them effectively.

Currently, the FAA has initiated several research activities on developing and testing scenarios to elicit cognitive biases among airline pilots in flight simulators. Additional training modules are required to help pilots improve their decision-making skills in conjunction with existing flight instruction.

mailto:Andrew.Cheng@faa.gov mailto:Jeffery.Schroeder@faa.gov mailto:9-ACT-AAQ-600-BAA@FAA.gov

Purpose:

The objective of this BAA research topic is to create training modules that allow pilots to experience realistic aviation decision-making errors, as well as to learn and to practice effective mitigations to avoid negative or catastrophic consequences. Airlines can then incorporate these modules into their training programs to improve pilot awareness of decision-making errors and provide ways to mitigate them when they arise. The training modules should have both academic and practical components. The academic component should provide (1) the foundational knowledge regarding human decision making, (2) the human decision-making errors that are most relevant to pilots, and (3) the most successful methods of mitigating these errors. The practical component should involve simulator scenarios that include decision points at which the pilots must obtain and evaluate data to make decisions (e.g., continue with approach or execute a go-around). The scenarios will reinforce the academic training component by exposing flight crews to situations that are likely to induce decision-making errors. While some of the potential training scenarios have been developed on reducing pilot error through raising awareness of cognitive biases, additional training scenarios should be considered to induce and illustrate other types of errors. The research should also examine methods to enable the instructors to effectively teach decision making techniques and skills during both the academic and the practical training sessions.

This research aims to provide a framework for how to develop and use such training modules.

Although the output of the research is intended to be used by Part 121 carriers, the research will also seek to make the framework applicable to other Parts, such as 135, 91K, and even 61, as both the education and prevention of decision errors are part of the pilot training continuum.

Requirements:

The FAA seeks White Papers to address the specific areas listed below; however, submittals are not limited to these requirements;

• Create and evaluate training modules that contain both academics and practical scenarios so that pilots can experience decision-making errors and can learn how to mitigate them.

• Craft a framework on how to develop new and viable scenarios for training pilots on aviation decision making.

Since flight training organizations typically employ their own decision-making methods, it is highly encouraged to research and to develop training modules that align with current approaches or propose methods to incorporate the developed modules with existing airline training programs.

Period of Performance (PoP)/Rough Order of Magnitude (ROM):

The PoP is anticipated to be 24 months. The ROM for this research is expected to be no more than $910,000.

Topic Number: ARSS0011 Improving Airline Safety Using Nationwide Pilot Training Data

Technical POCs: Timothy Kuhn Timothy.G.Kuhn@faa.gov;

Copy: 9-ACT-AAQ-600-BAA@FAA.gov

Background:

mailto:Timothy.G.Kuhn@faa.gov

While high-fidelity flight simulators are widely used to train and check airline pilots, the analyzed data rely largely on the simulator instructor’s subjective ratings that are usually collected at individual airlines. Efforts to collect objective performance data have been constrained by concerns from pilot unions about potential misuse, resulting in the inability to mine a potential source of valuable training data that could be used both for training and safety improvements. This project aims to research or advance a voluntary, airline-partnered process to augment the existing Aviation Safety Information Analysis and Sharing (ASIAS)2 system with de-identified training data collected in flight simulators. Such data could support answering whether specific skills are effectively trained, benchmarking performance distributions across airlines, improving safety margins, and aligning simulator training more closely with real-world operations.

Purpose:

The purpose of this topic is two-fold: 1) researching viable means to enable objective, scalable, and privacy-conscious data collection and information sharing for analysis of simulation data; 2) constructing analytics of the simulator data to support the assessment of training sufficiency, task performance, and trend analysis. Because the vast majority of simulator tasks contain abnormal events that assess the pilot’s role in overall operational safety, the study will investigate the benefits of analyzing pilot training data for safety assessment. Emphasis is placed on practical, collaborative implementations with airlines and simulator manufacturers to co-develop common data schemas, clearly defined governance structures, voluntary participation models, and meaningful safety analytics.

This effort seeks solutions that demonstrate end-to-end capability from capturing de-identified simulator data during routine training events to producing meaningful, shareable outputs.

Approaches should also consider how objective metrics compare to existing instructor grading, and how simulator performance trends relate to operational safety outcomes. Several applications are expected from the de-identified collection of such data. First, the oft asked question “is that trained?” could be answered easily and quickly. Second, distributions of how well particular tasks are performed could not only allow for safety margins to be reconciled, but a particular airline could determine its location in the distribution. Simulator data could also be compared to operational data for potential training improvements. The project should address a complete method to enable analysis of objective ATP training data and provide informed decisions concerning pilot training practices for improving airline safety.

Requirements:

The FAA seeks White Papers to address the specific areas listed below; however, submittals are not limited to these requirements.

• Research or advance a current framework for the voluntary collection and analysis of de-identified pilot training data from high-fidelity simulators, including data governance and standardized data structures;

• Identify objective performance metrics to determine training performance and sufficiency as well as to enable benchmarking against aggregated performance.

The PoP is anticipated to be 36 months.

2 Federal Aviation Administration Report to Congress: Report on the Status of Aviation Safety Information Analysis and Sharing (ASIAS) Capability Acceleration, U.S. Federal Aviation Administration (FAA), March 31, 2020.

Topic Number: ARSS0012 Pilot Operational Decision Making Aid

Technical POCs: Andrew Cheng Andrew.Cheng@faa.gov;

Copy: 9-ACT-AAQ-600-BAA@FAA.gov

Background:

Situations arise where a potential safety issue and related information are presented incompletely in any single source. Missing information from a source can (a) increased system complexity, (b) information explosion, and (c) the decrease in average airline pilot experience has raised a question as to whether useful improvements to operational decision making are warranted on the flight deck. Such improvements may be especially valuable when a need arises to integrate information that is dispersed across multiple sources, such as the flight operations manual, flight crew training manual, quick reference handbook, etc. Situations arise where a potential safety issue are presented incompletely in each source, and in order to obtain all information related to a safety issue requires information from all sources. Missing information from a source can alter a decision and cascade into a significant problem. Pilot decisions in such situations are not typically supported with structured tools. Instead, decisions are made from an accumulation of knowledge, either through detailed study of available manuals or from experience relayed by others. As recognized by at least one major airframe Original Equipment Manufacturer (OEM), these situations are increasing in prevalence.

Purpose:

The purpose of this BAA research topic is to research and test a structured tool for assisting pilot operational decision making during emergent and complicated situations. The project should propose a method to gather key information as well as design a model to present the information to enhance pilot operational decision-making. The research efforts should investigate the system complexity, critical situations that require pilot judgement to safely resolve, and key information needed for decision-making. This study should also consider differences in pilot experience to create an effective method utilizing the advances in computing technologies to present viable options for assisting pilot decision-making. The project is encouraged to include suitable testing scenarios to gather and present key information. The tool and model may be tested on the B-737 and A330 flight simulators first and then on other make/model/series aircraft. The output will be

1) a validated framework to gather and present key information for pilots to make effective decisions; and 2) an evaluation of a prototype to assess its benefit/cost ratio.

Requirements:

The FAA seeks White Papers to address the specific areas listed below; however, submittals are not limited to these requirements.

• Survey and document the state-of-the-art of relevant pilot decision-support tools

• Considerations for creating an information gathering framework for decision-making situations in flight operations

• Determination of the data needs and their limitations, including whether the aid needs to be connected to the airplane’s systems.

• Development of a model to present options for pilot decision-making.

• Evaluation of the effectiveness of the proposed model with airline pilots.

• Responses with a significant reliance on an artificial intelligence solution will be considered less favorably, as artificial intelligence is not the focus of this research.

The PoP is anticipated to be 24 months. The ROM for this research is expected to be no more than $1,200,000.