Great expectations: a predictive processing account of automobile driving

ABSTRACT 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.

[1]  Johan Engström,et al.  Analysis of the role of inattention in road crashes based on naturalistic on-board safety monitoring data , 2013 .

[2]  Raymond J. Dolan,et al.  Model averaging, optimal inference, and habit formation , 2014, Front. Hum. Neurosci..

[3]  Marco Dozza,et al.  Analysis of Naturalistic Driving Study Data: Safer Glances, Driver Inattention, and Crash Risk , 2014 .

[4]  Bobbie Seppelt,et al.  Potential Solutions to Human Factors Challenges in Road Vehicle Automation , 2016 .

[5]  Tuomo Kujala,et al.  The Attentional Demand of Automobile Driving Revisited , 2016, Hum. Factors.

[6]  T M Allen,et al.  DRIVER INFORMATION NEEDS , 1971 .

[7]  Karl J. Friston.  Hierarchical Models in the Brain , 2008, PLoS Comput. Biol..

[8]  M. Ljung Aust,et al.  A conceptual framework for requirement specification and evaluation of active safety functions , 2011 .

[9]  Wynn C. Stirling,et al.  Satisficing Revisited , 2000, Minds and Machines.

[10]  M. Endsley.  Situation Awareness Misconceptions and Misunderstandings , 2015 .

[11]  J. Wann,et al.  Steering with or without the flow: is the retrieval of heading necessary? , 2000, Trends in Cognitive Sciences.

[12]  Neville Moray.  Monitoring, complacency, scepticism and eutactic behaviour , 2003 .

[13]  David Badre,et al.  Cognitive control, hierarchy, and the rostro–caudal organization of the frontal lobes , 2008, Trends in Cognitive Sciences.

[14]  Karl J. Friston,et al.  Action and behavior: a free-energy formulation , 2010, Biological Cybernetics.

[15]  Karl J. Friston.  The free-energy principle: a unified brain theory? , 2010, Nature Reviews Neuroscience.

[16]  David N. Lee,et al.  A Theory of Visual Control of Braking Based on Information about Time-to-Collision , 1976, Perception.

[17]  William J Horrey,et al.  Modeling drivers' visual attention allocation while interacting with in-vehicle technologies. , 2006, Journal of experimental psychology. Applied.

[18]  Karl J. Friston,et al.  Computational psychiatry: the brain as a phantastic organ. , 2014, The lancet. Psychiatry.

[19]  Heikki Summala,et al.  Top-Down and Bottom-Up Processes in Driver Behavior at Roundabouts and Crossroads , 2000 .

[20]  A. Seth.  Interoceptive inference, emotion, and the embodied self , 2013, Trends in Cognitive Sciences.

[21]  Floris P. de Lange,et al.  How Prediction Errors Shape Perception, Attention, and Motivation , 2012, Front. Psychology.

[22]  John W. Senders,et al.  Visual Sampling Processes , 1984 .

[23]  Jonathan D. Cohen,et al.  An integrative theory of locus coeruleus-norepinephrine function: adaptive gain and optimal performance. , 2005, Annual review of neuroscience.

[24]  René van Paassen,et al.  The importance of including knowledge of neuromuscular behaviour in haptic shared control , 2012, 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[25]  Karl J. Friston,et al.  Active inference and epistemic value , 2015, Cognitive neuroscience.

[26]  D. Knill,et al.  The Bayesian brain: the role of uncertainty in neural coding and computation , 2004, Trends in Neurosciences.

[27]  Christopher D. Wickens,et al.  Attentional Models of Multitask Pilot Performance Using Advanced Display Technology , 2003, Hum. Factors.

[28]  Marc Green,et al.  "How Long Does It Take to Stop?" Methodological Analysis of Driver Perception-Brake Times , 2000 .

[29]  ChrisD . Frith,et al.  Perceiving is believing: a Bayesian approach to explaining the positive symptoms of schizophrenia , 2009, Nature Reviews Neuroscience.

[30]  Jonathan D. Cohen,et al.  Computational roles for dopamine in behavioural control , 2004, Nature.

[31]  Rajesh P. N. Rao,et al.  Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects. , 1999 .

[32]  Bilge Mutlu,et al.  Situation Awareness, Scenarios, and Secondary Tasks: Measuring Driver Performance and Safety Margins in Highly Automated Vehicles , 2016 .

[33]  R. Proctor,et al.  Control of cognitive processes: attention and performance XVIII. Stephen Monsell and John Driver (eds). MIT Press, Cambridge, MA, 2000. No. of pages 779. ISBN 0‐262‐13367‐9. Price: $90.00 (hardback). , 2002 .

[34]  Jens Rasmussen,et al.  Skills, rules, and knowledge; signals, signs, and symbols, and other distinctions in human performance models , 1983, IEEE Transactions on Systems, Man, and Cybernetics.

[35]  J. Gold,et al.  Neural computations that underlie decisions about sensory stimuli , 2001, Trends in Cognitive Sciences.

[36]  Mark Mulder,et al.  Haptic shared control: smoothly shifting control authority? , 2012, Cognition, Technology & Work.

[37]  Karl J. Friston,et al.  Attention, Uncertainty, and Free-Energy , 2010, Front. Hum. Neurosci..

[38]  Fridulv Sagberg,et al.  A Review of Research on Driving Styles and Road Safety , 2015, Hum. Factors.

[39]  Gregory T. Huang.  Essence of thought , 2008 .

[40]  Gustav Markkula,et al.  Modeling driver control behavior in both routine and near-accident driving , 2014 .

[41]  Heikki Summala,et al.  Towards Understanding Motivational and Emotional Factors in Driver Behaviour: Comfort Through Satisficing , 2007 .

[42]  John H. Holland,et al.  Induction: Processes of Inference, Learning, and Discovery , 1987, IEEE Expert.

[43]  A. Damasio.  Descarte's error : emotion, reason, and the human brain , 1994 .

[44]  Christopher A. Monk,et al.  A conceptual framework and taxonomy for understanding and categorizing driver inattention , 2013 .

[45]  Mica R. Endsley,et al.  The Out-of-the-Loop Performance Problem and Level of Control in Automation , 1995, Hum. Factors.

[46]  H Summala,et al.  Attention and expectation problems in bicycle-car collisions: an in-depth study. , 1998, Accident; analysis and prevention.

[47]  Sir Frederic Bartlett.  Schema Theory , 2017 .

[48]  I. Lau.  A SYSTEMIC MODEL FOR DRIVER-IN-CONTROL , 2003 .

[49]  Karl J. Friston,et al.  A theory of cortical responses , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

[50]  John D. Lee,et al.  Trust in Automation: Designing for Appropriate Reliance , 2004, Hum. Factors.

[51]  John P. Wann,et al.  How do we control high speed steering , 2004 .

[52]  Jan Theeuwes,et al.  Self-explaining roads , 1995 .

[53]  P. Carlo Cacciabue,et al.  Modelling Driver Behaviour in Automotive Environments: Critical Issues in Driver Interactions with Intelligent Transport Systems , 2007 .

[54]  Gustav Markkula,et al.  Answering questions about consciousness by modeling perception as covert behavior , 2015, Front. Psychol..

[55]  Bobbie D. Seppelt,et al.  Making adaptive cruise control (ACC) limits visible , 2007, Int. J. Hum. Comput. Stud..

[56]  A. Clark.  Whatever next? Predictive brains, situated agents, and the future of cognitive science. , 2013, The Behavioral and brain sciences.

[57]  R Fuller,et al.  A conceptualization of driving behaviour as threat avoidance. , 1984, Ergonomics.

[58]  T A Ranney,et al.  Models of driving behavior: a review of their evolution. , 1994, Accident; analysis and prevention.

[59]  T. Victor,et al.  Attention selection and multitasking in everyday driving: A conceptual model , 2013 .

[60]  E. Rolls,et al.  Attention, short-term memory, and action selection: A unifying theory , 2005, Progress in Neurobiology.

[61]  Karl J. Friston,et al.  Predictions not commands: active inference in the motor system , 2012, Brain Structure and Function.

[62]  H. Simon,et al.  A Behavioral Model of Rational Choice , 1955 .

[63]  Gustav Markkula,et al.  A farewell to brake reaction times? Kinematics-dependent brake response in naturalistic rear-end emergencies. , 2016, Accident; analysis and prevention.

[64]  Karl J. Friston,et al.  Perceptions as Hypotheses: Saccades as Experiments , 2012, Front. Psychology.

[65]  Klaus Bengler,et al.  “Take over!” How long does it take to get the driver back into the loop? , 2013 .

[66]  E. Miller,et al.  An integrative theory of prefrontal cortex function. , 2001, Annual review of neuroscience.

[67]  Giovanni Pezzulo,et al.  Why do you fear the bogeyman? An embodied predictive coding model of perceptual inference , 2013, Cognitive, Affective, & Behavioral Neuroscience.

[68]  John D. Lee,et al.  Modeling Driver Response to Imperfect Vehicle Control Automation , 2015 .

[69]  D. Ballard,et al.  Eye movements in natural behavior , 2005, Trends in Cognitive Sciences.

[70]  Walter Schneider,et al.  Controlled and automatic human information processing: II. Perceptual learning, automatic attending and a general theory. , 1977 .

[71]  Karl J. Friston,et al.  Active inference, sensory attenuation and illusions , 2013, Cognitive Processing.

[72]  Ola Benderius,et al.  Modelling driver steering and neuromuscular behaviour , 2014 .

[73]  R. Rescorla,et al.  A theory of Pavlovian conditioning : Variations in the effectiveness of reinforcement and nonreinforcement , 1972 .

[74]  P L Olson,et al.  Perception-Response Time to Unexpected Roadway Hazards , 1986, Human factors.

[75]  R. Fuller.  Towards a general theory of driver behaviour. , 2005, Accident; analysis and prevention.

[76]  Mica R. Endsley,et al.  Toward a Theory of Situation Awareness in Dynamic Systems , 1995, Hum. Factors.

[77]  David N. Lee,et al.  Where we look when we steer , 1994, Nature.

[78]  R. G. Morris.  D.O. Hebb: The Organization of Behavior, Wiley: New York; 1949 , 1999, Brain Research Bulletin.

[79]  Christopher D. Wickens,et al.  Multiple resources and performance prediction , 2002 .

[80]  Jonathan D. Cohen,et al.  On the Control of Control: The Role of Dopamine in Regulating Prefrontal Function and Working Memory , 2007 .

[81]  Ray Fuller,et al.  Motivational Determinants of Control in the Driving Task , 2007 .

[82]  Kevin B. Bennett,et al.  Display and Interface Design: Subtle Science, Exact Art , 2011 .

[83]  N. M. Morris,et al.  On Looking into the Black Box: Prospects and Limits in the Search for Mental Models , 1986 .

[84]  Daniel M. Wolpert,et al.  Forward Models for Physiological Motor Control , 1996, Neural Networks.

[85]  Arnaud Koustanaï,et al.  Statistical analysis of "looked-but-failed-to-see" accidents: highlighting the involvement of two distinct mechanisms. , 2008, Accident; analysis and prevention.

[86]  J. Gibson.  The Ecological Approach to Visual Perception , 1979 .

[87]  T. Shallice,et al.  CONTENTION SCHEDULING AND THE CONTROL OF ROUTINE ACTIVITIES , 2000, Cognitive neuropsychology.

[88]  Karl J. Friston,et al.  Active Inference: A Process Theory , 2017, Neural Computation.

[89]  Karl J. Friston,et al.  Predictive coding explains binocular rivalry: An epistemological review , 2008, Cognition.

[90]  Benjamin O. Turner,et al.  Cortical and basal ganglia contributions to habit learning and automaticity , 2010, Trends in Cognitive Sciences.

[91]  John W. Senders,et al.  The Human Operator as a Monitor and Controller of Multidegree of Freedom Systems , 1964 .

[92]  Natasha Merat,et al.  Effects of Cognitive Load on Driving Performance: The Cognitive Control Hypothesis , 2017, Hum. Factors.

[93]  M. Bar.  The proactive brain: using analogies and associations to generate predictions , 2007, Trends in Cognitive Sciences.

[94]  Truls Vaa,et al.  Modelling Driver Behaviour on Basis of Emotions and Feelings: Intelligent Transport Systems and Behavioural Adaptations , 2007 .

[95]  Kim J. Vicente,et al.  Ecological interface design: theoretical foundations , 1992, IEEE Trans. Syst. Man Cybern..

[96]  J. G. Holmes,et al.  Trust in close relationships. , 1985 .

[97]  Johan Engström,et al.  A General Conceptual Framework for Modelling Behavioural Effects of Driver Support Functions , 2007 .

[98]  James L. McClelland,et al.  On the control of automatic processes: a parallel distributed processing account of the Stroop effect. , 1990, Psychological review.

[99]  J. Hohwy.  The Predictive Mind , 2013 .

[100]  J. Engström.  Understanding attention selection in driving: From limited capacity to adaptive behaviour , 2011 .

[101]  E. Boer.  Car following from the driver’s perspective , 1999 .

[102]  Karl J. Friston,et al.  Active Inference, homeostatic regulation and adaptive behavioural control , 2015, Progress in Neurobiology.

[103]  Paul L. Olson,et al.  DRIVER PERCEPTION RESPONSE TIME , 1989 .

[104]  Hermann Winner,et al.  Towards cooperative guidance and control of highly automated vehicles: H-Mode and Conduct-by-Wire , 2014, Ergonomics.

[105]  John A. Michon,et al.  A critical view of driver behavior models: What do we know , 1985 .

[106]  Johan Engström,et al.  Adaptive Behavior in the Simulator: Implications for Active Safety System Evaluation , 2011 .

[107]  Peter Dayan,et al.  A Neural Substrate of Prediction and Reward , 1997, Science.

[108]  Matias Viström,et al.  Effects of forward collision warning and repeated event exposure on emergency braking , 2013 .

[109]  John D. Lee,et al.  Trust, self-confidence, and operators' adaptation to automation , 1994, Int. J. Hum. Comput. Stud..

[110]  Jens Rasmussen,et al.  The role of hierarchical knowledge representation in decisionmaking and system management , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[111]  Richard S. Sutton,et al.  Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.

[112]  Heikki Summala,et al.  RISK CONTROL IS NOT RISK ADJUSTMENT: THE ZERO-RISK THEORY OF DRIVER BEHAVIOUR AND ITS IMPLICATIONS , 1988 .