Information Requirements for Traffic Awareness in a Free-Flight Environment: An Application of the FAIT Analysis

Uhlarik, John; Comerford, Doreen A. · 2003 · ROSA P / United States. Department of Transportation. Federal Aviation Administration. Office of Aviation. Civil Aerospace Medical Institute

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Summary

This paper addresses the human factors challenges associated with National Airspace System (NAS) modernization, specifically focusing on the information requirements for pilot traffic awareness in a proposed "free-flight" environment. In this future operational concept, pilots are primarily responsible for self-separation, maintaining specific horizontal and vertical distances from other aircraft. The research was motivated by the need to design effective Cockpit Displays of Traffic Information (CDTI) and to evaluate the utility of the Function Allocation Issues and Tradeoffs (FAIT) analysis method. Previous studies were deemed insufficient because they either focused only on general aviation data-link information or excluded static information and specific technological contexts. The authors applied the FAIT analysis, a systematic procedure for examining human-machine systems, to a model involving a pilot, a modernized NAS with Automatic Dependent Surveillance-Broadcast (ADS-B), and a prototype NASA-AMES CDTI. The analysis followed six steps: developing an information flow model, decomposing the system into 68 unique characteristics, creating a matrix of characteristic interactions, estimating relative importance, identifying tradeoffs, and determining information requirements. The CDTI was classified as a "simple aid" with "personalized" intelligence capabilities. The researchers calculated "influence" scores (how much a characteristic affects others) and "sensitivity" scores (how vulnerable a characteristic is to other factors) for each of the 68 characteristics. The results identified seven characteristics as having the highest influence: weather, general piloting skills, time of day, terrain, ownship state, pilot mental workload, and perceived time pressure. The seven most sensitive characteristics were the type of action chosen by the pilot, pilot mental workload, appropriateness of planned action, ownship state, air traffic manager mental workload, accuracy of the machine model, and confidence in planned action. Notably, "ownship state" and "level of pilot mental workload" were both highly influential and highly sensitive. When components related to machine and pilot models were combined into a global "traffic awareness" characteristic, it emerged as one of the most sensitive aspects of the system, indicating high vulnerability to other system factors despite having moderate influence. The study concludes that the FAIT analysis is a valuable tool for identifying information requirements and examining system tradeoffs, offering more detail than traditional task analyses. By highlighting the critical role of pilot mental workload and the sensitivity of traffic awareness, the findings provide specific guidance for the design and certification of CDTIs. The research suggests that interface designs must account for the dynamic interplay between static rules and dynamic environmental factors to support effective self-separation in free-flight operations.

Key finding

Pilot mental workload and ownship state were identified as the most influential and sensitive characteristics in the traffic awareness system, while traffic awareness itself was determined to be a highly vulnerable characteristic requiring robust interface support.

Methodology

modeling

Provenance

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Topics

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• situational awareness
• mode awareness
• situation awareness theory