No abstract

No abstract

The paper discusses the possibilities of objective assessment of military flight training quality based on statistical evaluation of pilot’s behavior models parameters. For these purposes, the pilots’ responses to non-standard flight situations were measured by using a fixed-base and a moving-base engineering flight simulator. Tens of military pilots at different training stages were tested. By exploiting real-life tests, we established that the given pilot models provide sufficiently accurate approximation of realistic human responses. Importantly, the models are relatively easy to use, and the individual parameters can be unambiguously interpreted, i.e., the time constants of the pilot behavior model are obtainable, representing the pilot’s current psychological and physiological state of mind. The parameters lay in the defined ranges, and they characterize the ability of the human/pilot to adapt to a controlled dynamic system. Consequently, a fundamental statistical analysis based on pilot’s behavioral model parameters was conducted, using the acquired test data representing the pilot’s behavior during repeated measuring. The initial results indicate the possibility to use the results for objective assessment the military flight training level.

This paper summarises many years of the results of the development and modelling of human behaviour while flying an aircraft, from a flight automation point of view. The introduction presents the challenges of describing and modelling human behaviour. Based on that knowledge, options for acquiring parameters for a pilot behaviour model are described. Then, analysis of pilot response is presented, acquired from many tests on two simulators (stationary and motion-platform). These experimental tests are pilot responses to a visual stimulus and also partially to motion stimulus-step change in flight altitude where the task of the pilot is to return the flight, as quickly as possible to the original flight altitude. Due to the vast amount of test data files-missions from each test-the authors rewrote the identification algorithms for batch data processing and utilised a Salamon supercomputer located at Technical University of Ostrava. In the first phase of implementation of the identification algorithms, the calculations were 4 times faster, and after rewriting the algorithms for parallel calculations, the authors expect the speed to increase more than 10 times.

No abstract