Institute for Transport Studies (ITS)

The impact of cognitive distractions on driving with and without automation

Supervisor: Dr Gustav Markkula (possible co-supervisor Professor Natasha Merat)

One of the most elusive phenomena in driving safety research is the role of cognitive distraction in crash causation, i.e. to what extent loading a driver with cognitively demanding tasks such as talking, focused thinking, or daydreaming, makes the driver less safe. It is well known that cognitive distractions have an effect on observable driver behaviour in routine driving conditions, but it has been less clear how this translates to real-world safety. This research project will aim to increase knowledge in this field in two main directions: (1) Leveraging emerging results from psychology and neuroscience to better characterise the underlying mechanisms behind effects of cognitive distractions on driving performance. Such developments, together with likewise emerging findings from large-scale naturalistic studies, will allow (2) a better account of the real implications of cognitive distraction for traffic safety under various circumstances, not least in transitions out of automated driving.

The exact scope and approach can be tailored to the background and interests of the PhD candidate, but one important part of the method should be to leverage existing quantitative models of driving control, and to extend these to account for effects of cognitive load. This is an active area of work for the research group at ITS Leeds. The project will also include analysis of existing data sets of driving under cognitive load, as well as design and analysis of new experiments at the University of Leeds Driving Simulator (the most capable of its kind in the UK).

The suitable candidate will either have a degree in Psychology, Human Factors, or similar, with a quantitative and applied penchant, or vice versa a degree in Engineering or similar, coupled with a strong interest in human psychology and behaviour. Relevant skills include: psychology and neuroscience (esp. relating to perception and movement), programming (esp. MATLAB), mathematics, data analysis, control theory.

Suggested reading:

G.K. Kountouriotis, G. K., and Merat, N. (2016). Leading to distraction: Driver distraction, lead car, and road environment. Accident Analysis & Prevention, 89, 22-30.

Markkula, G. (2014). Modeling driver control behavior in both routine and near-accident driving. Proceedings of the HFES Annual Meeting, 58(1), 879-883.

Simmons, S, M., Hicks, A and Caird, J. K. (2016). Safety-critical event risk associated with cell phone tasks as measured in naturalistic driving studies: A systematic review and meta-analysis. Accident Analysis and Prevention 87,161–169.

Search site