The potential use of fast-time simulation techniques for aviation safety analysis depends on how well the simulation models can address critical aspects of human behavior. A review of the architecture and operation of two representative human performance models suggests that the use of human performance models to provide detailed representation of cognitive processes and sensory constraints within a simulation could well provide a reasonable assessment of the effectiveness of particular measures intended to prevent or mitigate specific hazards. However, the use of such models to predict emergent error behavior with sufficient confidence to produce useful safety assessments is likely to require significant future research efforts.
In order to develop simulation capabilities that can be reliably applied to important safety questions, it will be necessary for the air traffic and human performance models to be developed to appropriate levels of fidelity. This may well require the use of different models, or different versions of the same model, that have the relevant capabilities at appropriate levels of breadth and depth for the particular problem being studied. Thus, linkages between a human performance model and an air traffic simulation should be developed in a way that preserves the ability to utilize different models if the need arises, or to exchange different types of information between the simulation components.
The capability of High Level Architecture (HLA) to support interaction between simulation models and real-world control, communication, and information systems may provide the potential for future integration of fast-time simulation analysis with human performance models as well as with such research resources as aircraft flight simulators, test aircraft, human-in-the-loop real-time simulations, and live NAS operations. While there may be some additional initial effort in configuring the air traffic simulation and human performance models to support HLA standards, the advantages of future interoperability and the ability to interface with a broader range of external models and data sources may justify the effort. At the very least, it offers opportunities worthy of further investigation.
The present report documents the methodology and findings of the third and final year’s research (CY01), which focused on effecting a linkage between a fast-time traffic operations simulation model and a cognitive human performance model. In particular, primary research tasks accomplished included:
Identification of a scenario of air traffic in an en route sector with clear-air turbulence (CAT) and specification of an experimental design of simulation runs to assess the impacts of a CAT sensor technology in that sector. Traffic volumes and routes for the scenario were derived from Enhanced Traffic Management System (ETMS) data for an en route sector in the Boston Air Route Traffic Control Center (ARTCC).
Specification of flight crew and controller procedures, including message communications, related to transit of an en route sector with clear-air turbulence events.
Development of an agent-based simulation model of air traffic in an en route sector with CAT. The model includes agents for controllers, flight crews, aircraft, radar surveillance, communication channels, CAT weather events, and sensors. The simulation is built using the Reconfigurable Flight Simulator (RFS) simulation technology, which implements agent-based, hybrid (continuous time/discrete event) simulations.
Design of detailed human performance models of flight crew and controller behavior in an en route sector with CAT, where the pilot and controller procedure specifications would be coded into the MIDAS human performance model.
Demonstration of linked RFS and MIDAS simulation, with the MIDAS flight crews and controller providing micro-level representations of the corresponding RFS flight crews and controller, implemented on a suite of computer processors using the High-Level Architecture (HLA) interface standards and Run-Time Interface (RTI) software.
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