Human Behaviour Models within a Future Armoured Vehicle System (FAVS) Framework

摘要

This paper presents the results of a Future Armoured Vehicle Systems (FAVS) project that was designed to assess the impact of advanced armoured vehicle technologies on operator performance and workload. As part of this project, Task Network Models were developed to predict the impact of FAVS technologies on operator performance and workload prior to experiments conducted live and virtual simulations. The FAVS project also provided the opportunity to validate the FAVS TNMs with the results of the live and virtual simulations. Baseline TNMs were developed and validated from performance data drawn from previous armoured vehicle performance data, and were then modified to match the requirements of the FAVS. The FAVS TNM was then used to predict crew behaviour and system performance, the results of which were then compared to actual human behaviour captured during virtual simulation trials, leading to an evaluation and update of the model. The results from the study produced faster engagement times and reduced operator workload for the FAVS compared to traditional armoured vehicle systems. However, due to the high level of systems failure in the FAVS LE, the performance data generated from the FAVS model could not be accurately validated against the virtual simulations. Improvements to the validation process were identified in order to facilitate future validation efforts between human behaviour models and human-in-the-loop simulations.