Human Factors Engineering

The Human Factors Engineering group investigates the effects of specific designs for computer and engineering systems on the people who are responsible for operating the systems. We are interested in such issues as the amount of cognitive workload that these operators experience, and the degree of trust that they feel for these systems (especially in cases where the technology fails). This research will tell us more about how to design systems that work naturally with their human operators, thereby helping, rather than hindering them in their tasks.


Current Projects

Human Factors in Supervising Semi-Autonomous Vehicle Convoys

Convoys of robot vehicles that can travel along urban roads with little or no intervention from human drivers are becoming more viable every day, and have great potential in critical application areas such as emergency services and defense. Drivers, who are a costly resource, would be replaced by human supervisors responsible for the convoy as a whole, operating technical systems that monitor and control the robot vehicles. This project investigates how best to divide tasks and coordinate communication between human supervisors and technical systems, to allow the whole team to perform their task safely and effectively.

Workload Estimation Using EEG Signals

This project investigates on-line methods to analyse brain signals (in the form of electroencephalographic, or EEG, data) to determine the amount of mental workload that a person is experiencing from one moment to the next. The aim is to provide a real-time indication of the amount of load a person is under while they are performing a task. This research could potentially be used in systems that support people performing complex and dangerous tasks, by automatically recruiting support from additional team members when workload becomes too intense, or by activating automated systems that can take over some portion of the task.


For More Information...

For more information on these projects, or if you're interested in joining the group, please contact Dr Richard Leibbrandt.





Refereed journal articles

Pfitzner, D.M., Leibbrandt, R.E., & Powers, D.M.W., 2009. Characterization and evaluation of similarity measures for pairs of clusterings. Knowledge and Information Systems, 19(3), 361-394.

Pfitzner, D.M., Treharne, K., & Powers, D.M.W., 2008. User Keyword Preference: the Nwords and Rwords Experiments. International Journal of Internet Protocol Technology, 3(3), 149-158.

Refereed conference papers

Powers, D.M.W., Luerssen, M.H., Lewis, T.W., Leibbrandt, R.E., Milne, M.K., Pashalis, J., & Treharne, K., 2010. MANA for the Ageing. Proceedings of the 2010 Workshop on Companionable Dialogue Systems, ACL 2010, 7-12.

Treharne, K., Pfitzner, D.M., Leibbrandt, R.E., & Powers, D.M.W., 2008. A lean online approach to human factors research. Proceedings of the 1st International Conference on PErvasive Technologies Related to Assistive Environments (PETRA 2008), (57).