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Challenges and research for an evolving aviation system

 

More Data from More Sources for Aviation Safety

Massive Algorithm, Computational and Verification Challenge

Lesson from NextGen: hard benefit proof v. real costs 

 

NASA commissioned the National Academies of Sciences, Engineering, and Medicine to put some structure to a SMS beyond today’s capabilities.

 

NASEM convened its Aviation Safety Assurance Committee to cerebrate about the issue. ASAC is chaired by Kenneth Hylander, past chairman of the Board of Governors at the Flight Safety Foundation, executive vice president of safety at Amtrak. Members include 6 professors, 2 researchers from laboratory, two trade association executives, 4 from private industry and the FAA Deputy Administrator—a very knowledgeable team.

The goal of this team’s vision is to research, develop and implement ”an in-time aviation safety management system (IASMS) that could detect and mitigate high-priority safety issues as they emerge and before they become hazards…An IASMS could continuously monitor the national airspace system, assess the data that it has collected, and then either recommend or initiate safety assurance actions as necessary.”

Expansion of SMS holds great promise; the expansion of the data to incorporate every byte of information and the challenge of analyzing those numbers to produce reliable safety action plan pose daunting goals.

The report, 80 pages, explodes the quantum of data collected today for all of the information which the FAA and all segments are already accumulating. The present data storage captures:

• ACAS (AirCraft Analytical System),
• ASAP (Aviation Safety Action Program),
• ASDE–X (Airport Surface Detection Equipment–Model X),
• ASPM (Airspace Performance Metrics),
• ASRS (Aviation Safety Reporting System),
• ATSAP (Air Traffic Safety Action Program),
• FOQA (Flight Operational Quality Assurance),
• METAR (Meteorological Aviation Report),
• MOR (Mandatory Occurrence Reports),
• NFDC (National Flight Data Center),
• NOP (National Offload Program office track data),
• SDR (Service Difficulty Reports), and
• TFMS (Traffic Flow Management System).

 

The NASEM (ASAC) recommendations contemplate a massive expansion, integration and real time processing of the numbers:

The report envisions an IASMS that can collect data on the status of aircraft, air traffic management systems, airports, and weather, 
and then assess the data second by second, minute by minute, and hour by hour to detect or predict elevated risks quickly. Additionally, 
the IASMS would focus on risks that require safety assurance action in-flight or prior to flight, such as making a decision to postpone 
or cancel a flight until flight conditions change or equipment is repaired, for example. Safety assurance actions generated by an 
IASMS may take the form of recommendations that operators take action upon or, when urgent action is required, IASMS may be designated 
to initiate safety assurance actions autonomously.

 



Successful development of an IASMS will require overcoming key technical and economic challenges, and the task of maintaining a high level 
of safety for commercial airlines is complicated by the dynamic nature of the national airspace system—the common network of U.S. airspace, 
airports or landing areas, aeronautical information, rules, regulations, and procedures, technical information, and manpower and material. 
As the national airspace system evolves to accommodate the increase in number of flights and numerous new entrants, such as increasingly 
autonomous systems, aviation safety programs must also evolve to ensure that changes to the national airspace system do not inadvertently 
introduce new risks.”

Here are a few major points/challenges/research projects identified of/by the study:

 

• Real-time Aviation Safety Assurance System
• In-time Aviation Safety Management System
• Prioritization Process
• A Concept of Operation

 

 

 

 

 

• Identifying and prioritizing risks
• NAS evolution/NextGen/Growth in traffic
• UAS and autonomous aerial vehicles
• Commercial Space Flights
• Data completion and quality

 

 

 

 

 

[SMS Big Data: Dealing with 20 terabytes per hour CLICK]

• Data fusion
• Protecting personally identifiable information
• In-time algorithms
• Emergent risks
• Computational Architectures

 

 

 

 

 

[Microsoft & Boeing plan to automate the data rich environment of planes; add SMS’s unique window on SAFETY CLICK]

• In-time Mitigation Strategies
• Unintended Consequences of IASMS
• Trust in IASMS Safety Assurance Actions
• System Verification, Validation and Certification
• Adaptive/Non-deterministic systems
• Economic Challenges: Costs v. Benefits

Findings, Recommendations and Organizational Roles and Resources is the title of the last chapter and it is a realistic plan for managing the research from conceptualization to implementation.

As with other visionary projects, the process of converting innovative concepts to practical systems will be a challenge. IASMS’s advocates must learn from the history of NextGen—promises of great future efficiencies must be supported by hard data proof before the users will pay. Scientists, engineers, computer wizards, etc. will face the technical tests, but the IASMS project roster must include real world economists who can justify the benefits of the R&D before significant investments/commitments are made.

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