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The project is sponsored by the NASA Aviation Safety Program and is being conducted by a research team comprised of ATAC Corporation as the prime contractor, and the Massachusetts Institute of Technology (MIT) and the University of California at Berkeley (UCB) as subcontractors.  Teams of researchers at San Jose State University and Georgia Institute of Technology, funded under separate NASA grants, also collaborated with the ATAC team and played an integral role in this phase of the project.
Conclusions from the first two phases of the research, which laid the groundwork for the Phase III work reported here, were as follows:
The application of the Simmod PRO! air traffic simulation model to the runway incursion problem clearly demonstrated that human performance factors can be incorporated into an existing fast-time simulation model, and the resulting simulation can be applied to obtain valuable results for addressing a critical aviation safety issue.

To enable fast-time simulation tools to meet general-purpose needs for safety analysis, significant enhancements to existing simulation capabilities will be required.  These enhancements need to address the implementation of open architecture concepts in model and program design, the representation of aircraft performance, the modeling of the behavior of the human agents involved, and the representation of the communication processes among controllers, pilots, and other system components.

Developments in the field of cognitive modeling have reached the point where a carefully designed model can be expected to give reasonable and useful results.  Furthermore, a growing number of such models have been implemented in a form that could be integrated or interfaced with a fast-time air traffic simulation model.

Given the lack of understanding of practical issues involved with combining cognitive models with air traffic simulations, it would be advantageous for future research efforts to involve combining several promising cognitive models with a selected air traffic simulation and applying the alternatives to a common problem.  This should provide valuable insights into the strengths and weaknesses of modeling alternatives.

Neural network modeling techniques may hold considerable promise for efficient and realistic modeling of human cognitive and decision-making behavior, and warrant consideration for future research.

Implementation of the static, partial linkage accomplished in Phase II of the research demonstrated that full, dynamic linkage between a human performance model and an air traffic operations simulation model is essential for useful safety analysis.

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.
　
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