Great expectations: A predictive processing account of automobile driving
Journal article, 2018

Predictive processing has been proposed as a unifying framework for understanding brain function, suggesting that cognition and behaviour can be fundamentally understood based on the single principle of prediction error minimisation. According to predictive processing, the brain is a statistical organ that continuously attempts get a grip on states in the world by predicting how these states cause sensory input and minimising the deviations between the predicted and actual input. While these ideas have had a strong influence in neuroscience and cognitive science, they have so far not been adopted in applied human factors research. The present paper represents a first attempt to do so, exploring how predictive processing concepts can be used to understand automobile driving. It is shown how a framework based on predictive processing may provide a novel perspective on a range of driving phenomena and offer a unifying framework for traditionally disparate human factors models.


Predictive processing


driver behaviour




Johan A Skifs Engström

Virginia Polytechnic Institute and State University

Jonas Bärgman

Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Safety

Daniel Nilsson

Volvo Cars

Bobbie Seppelt

Touchstone Evaluations Inc

Gustav M Markkula

University of Leeds

Giulio Bianchi Piccinini

Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Safety

Trent Victor

Volvo Cars

Theoretical Issues in Ergonomics Science

1463-922X (ISSN) 1464-536X (eISSN)

Vol. 19 2 156-194

Areas of Advance


Subject Categories

Psychology (excluding Applied Psychology)

Vehicle Engineering



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