Advanced Air Mobility Automation and Testing
Autonomy Roadmap and Certification Approach
The FAA, in coordination with international National Aviation Authorities Network (NAA Network) partners, has committed to the NAA Network Roadmap for AAM Type Certification.
The Roadmap outlines a clear path to align aircraft type certification standards, harmonize airworthiness requirements, and facilitate robust information sharing. The goal is to maximize the transferability of type-certified AAM across the Network while using a deliberate, incremental approach to certification.
Six Key Principles
The Roadmap relies on the pursuit of six key principles:
- Safety and innovation: Balancing safety standards with technological advancement while promoting innovation
- Harmonized type certification: Using a three-phased approach focused on performance-based requirements, aligning requirements where differences exist, and applying mutually accepted Means of Compliance to streamline validation of AAM aircraft
- Collaboration and alignment: Foster collaboration and coordination within the NAA Network and with other key Authorities that have active domestic AAM certification projects
- Collaborative multi-authority validation: Reduce the validation burden for AAM Network Authorities and AAM OEMs by implementing a “one-to-many” collaborative program between the type certifying Authority and validating Authorities
- Incremental approach: Recognize a crawl, walk, run approach for type certifying AAM aircraft, building first on piloted AAM and then remotely piloted AAM with increasing levels of autonomy
- AAM inclusive bilateral agreements: Establish guiding principles and a comprehensive process for establishing new bilateral agreements and updating existing bilateral agreements for type certification and streamlined validation of AAM aircraft
Three-Phased Approach to Type Certification
To unify efforts across NAA Network Authorities, the framework utilizes a structured, three-phased operational approach:
- Performance-based requirements: Leverage existing regulatory frameworks to establish flexible, performance-based requirements
- Alignment of differing requirements: Exchange type certification knowledge and compliance data to resolve differences and align airworthiness requirements
- Mutually accepted means of compliance: Maximize the use of consensus and means of compliance standards, develop common compliance guidelines, and build toward the acceptance of compliance findings to streamline validation of AAM
Phased, Incremental Progression
The Roadmap employs a phased, incremental strategy for type certifying AAM aircraft, moving systematically from piloted and early-autonomy designs to remotely piloted configurations with increasing levels of autonomy.
Airworthiness criteria will be developed dynamically for each technology phase, initially informed by individual type certification projects and the application of industry consensus standards. The success of each technology phase depends on the success of the phase before. This deliberate pace ensures safety while reducing the time and resources required for validation. Ultimately, this approach will normalize AAM validation into a steady-state regulatory activity.
Virtual testing can provide data needed to understand the widespread use of increasingly autonomous aircraft and scaled operations. Verified and validated Artificial Intelligence and Machine Learning systems can assist the FAA in creating automation performance requirements, standards, and regulation frameworks.
Additionally, these advanced systems assist the aviation ecosystem by:
- Enhancing Testing and Evaluation: Planning and executing developmental testing and evaluation for AI-enabled components, applications, and systems
- Informing Industry Standards: Providing a reliable means to validate and verify fully automated or autonomous aircraft while informing industry consensus standards
Reducing Risk, Time, Cost
Understanding the performance requirements of a novel aircraft requires scenario-based analysis using sophisticated, data-heavy simulation tools. Testing scenarios must encompass both nominal conditions (routine, everyday operations) and complex contingencies likely to be encountered during regular operations.
Conducting these comprehensive scenarios exclusively through physical flight tests can be dangerous, expensive, and time-consuming. Utilizing digital engineering and mixed-reality testing during the Research, Development, Test, and Evaluation (RDT&E) phase allows the program to identify early requirement gaps, integration bugs, and operational issues—significantly reducing overall certification timelines, risks, and costs.
Note on Physical Testing: Virtual testing in early developmental phases does not eliminate the need for FAA-required physical safety testing. Instead, it serves as a highly repeatable, cost-effective method for catching errors and faults before physical testing, creating a more streamlined path to final certification.
Many AAM manufacturers and future operators are pursuing aircraft with high levels of automation to improve accessibility, operational flexibility, and economic efficiency.
To achieve this, the industry is leveraging two primary automation concepts:
- Simplified Vehicle Operations (SVO): A design approach that utilizes advanced automation to reduce or eliminate specific tasks traditionally managed by the pilot.
- Simplified Flight Controls (SFC): A subset of SVO that provides automated flight control and stabilization, making the physical piloting of an aircraft simpler and more intuitive.
Expanding the Aviation Workforce
Remotely piloted and remotely supervised autonomous aircraft represent the next major evolution in aerospace automation. By lowering traditional barriers to entry while maintaining or increasing rigorous safety standards, these technologies have the potential to significantly increase the number of individuals who can join the aviation industry as pilots or remote supervisors.
Evolving Human-Machine Frameworks
As flight deck automation matures, the FAA and its industry partners are continually evaluating the relationship between human operators and automated systems. Ongoing collaborative efforts focus on modernizing pilot training models, updating flight simulation credits, and ensuring robust safety baselines for both nominal and emergency operations. This deliberate approach ensures that regulations evolve dynamically alongside technological breakthroughs, keeping safety at the forefront of the advanced aviation ecosystem.
Some AAM operators and manufacturers are focused on pioneering remotely piloted and fully autonomous operations.
Implementing this vision depends directly on completing critical research, infrastructure planning, and procedural development. The initial phase requires identifying specific facility and equipment requirements for remotely piloted and autonomous AAM aircraft at airports, vertiports, and heliports, while systematically balancing low-altitude airspace demand and capacity.
The Infrastructure Challenge: Evolving Beyond the Flight Deck
Current airport, heliport, and vertiport design frameworks do not account for the unique facility or equipment requirements of automated aircraft.
The Human Factors Shift: Decades of existing infrastructure guidance for airport signage, surface markings, and safety lighting are based strictly on a human pilot sitting inside a physical flight deck. Automated flight requires a complete rethinking of these core spatial environments.
To resolve these integration gaps, the FAA and industry partners will conduct targeted research focusing on:
- Autonomous Navigation and Precision Landing: Evaluating automated traffic management functions and how infrastructure must adapt when an automated vehicle is at the controls rather than a human pilot.
- High-Fidelity Digital Mapping: Determining whether highly precise, continuously updated digital maps of airports and obstacles must be maintained and broadcast directly to unmanned aircraft.
- Real-Time Surface Tracking: Assessing the need to feed real-time positioning data of dynamic ground obstacles—such as passenger shuttles and ground servicing equipment—directly into autonomous flight systems.
- Advanced Surface-Based Equipment: Integrating new software and ground equipment to manage aircraft approach, departure, and taxi procedures around takeoff and landing areas. This ensures seamless integration into existing air traffic control operations without causing inefficiencies or safety hazards for traditional aircraft.