Evaluating the distraction potential of connected vehicles

Connected vehicles offer great potential for new sources of information, but may also introduce new sources of distraction. This paper compares three methods to quantify distraction, and focuses on one method: computational models of driver behavior. An integration of a saliency map and the Distract-R prototyping and evaluation system is proposed as a potential model. The saliency map captures the bottom-up influences of visual attention and this influence is integrated with top-down influences captured by Distract-R. The combined model will assess the effect of coordinating salient visual features and drivers' expectations, and in using both together, generate more robust predictions of performance.

[1]  Christopher D. Wickens,et al.  Driving and Side Task Performance: The Effects of Display Clutter, Separation, and Modality , 2004, Hum. Factors.

[2]  Christopher D. Wickens,et al.  Examining the Impact of Cell Phone Conversations on Driving Using Meta-Analytic Techniques , 2006, Hum. Factors.

[3]  William H. Levison.  Interactive Highway Safety Design Model: Issues Related to Driver Modeling , 1998 .

[4]  C. Koch,et al.  Computational modelling of visual attention , 2001, Nature Reviews Neuroscience.

[5]  John D. Lee,et al.  Sources of Driver Distraction , 2009 .

[6]  Mike McDonald,et al.  Car-following: a historical review , 1999 .

[7]  William H. Levison,et al.  On-Road Versus Simulator Data in Driver Model Development Driver Performance Model Experience , 2002 .

[8]  Dario D. Salvucci.  A Multitasking General Executive for Compound Continuous Tasks , 2005, Cogn. Sci..

[9]  William J. Horrey,et al.  Driver-initiated distractions: examining strategic adaptation for in-vehicle task initiation. , 2009, Accident; analysis and prevention.

[10]  Thomas J Triggs,et al.  Driver distraction: the effects of concurrent in-vehicle tasks, road environment complexity and age on driving performance. , 2006, Accident; analysis and prevention.

[11]  Christopher D. Wickens,et al.  Modeling the Control of Attention in Visual Workspaces , 2011, Hum. Factors.

[12]  Dario D. Salvucci,et al.  Threaded cognition: an integrated theory of concurrent multitasking. , 2008, Psychological review.

[13]  Edmund Donges,et al.  A Two-Level Model of Driver Steering Behavior , 1978 .

[14]  John R. Anderson.  How Can the Human Mind Occur in the Physical Universe , 2007 .

[15]  Christopher D. Wickens,et al.  Pilot Task Management : Testing an Attentional Expected Value Model of Visual Scanning , 2001 .

[16]  David Gittins,et al.  Icon-Based Human-Computer Interaction , 1986, Int. J. Man Mach. Stud..

[17]  M. Posner,et al.  Orienting of Attention* , 1980, The Quarterly journal of experimental psychology.

[18]  Laurent Itti,et al.  Realistic avatar eye and head animation using a neurobiological model of visual attention , 2004, SPIE Optics + Photonics.

[19]  Eric Rodgman,et al.  Driver's exposure to distractions in their natural driving environment. , 2005, Accident; analysis and prevention.

[20]  G. R. J. Hockey,et al.  Applied Attention Theory , 2009 .

[21]  Dario D. Salvucci.  An integrated model of eye movements and visual encoding , 2001, Cognitive Systems Research.

[22]  John D. Lee,et al.  Driver Distraction : Theory, Effects, and Mitigation , 2008 .

[23]  Frank Drews,et al.  Profiles in Driver Distraction: Effects of Cell Phone Conversations on Younger and Older Drivers , 2004, Hum. Factors.

[24]  Dario D. Salvucci.  Predicting the effects of in-car interface use on driver performance: an integrated model approach , 2001, Int. J. Hum. Comput. Stud..

[25]  Antonio Torralba,et al.  Contextual guidance of eye movements and attention in real-world scenes: the role of global features in object search. , 2006, Psychological review.

[26]  Brett R Fajen,et al.  Behavioral dynamics of steering, obstacle avoidance, and route selection. , 2003, Journal of experimental psychology. Human perception and performance.

[27]  Moshe Eizenman,et al.  An on-road assessment of cognitive distraction: impacts on drivers' visual behavior and braking performance. , 2007, Accident; analysis and prevention.

[28]  Pietro Perona,et al.  Graph-Based Visual Saliency , 2006, NIPS.

[29]  Christopher D. Wickens,et al.  In-Vehicle Glance Duration , 2007 .

[30]  Richard Wilkie,et al.  Controlling steering and judging heading: retinal flow, visual direction, and extraretinal information. , 2003, Journal of experimental psychology. Human perception and performance.

[31]  Christof Koch,et al.  Modeling attention to salient proto-objects , 2006, Neural Networks.

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

[33]  William H. Levison,et al.  Computational Techniques Used in the Driver Performance Model of the Interactive Highway Safety Design Model , 2001 .

[34]  J. Theeuwes.  Endogenous and Exogenous Control of Visual Selection , 1994, Perception.

[35]  Cher Carney,et al.  Human Factors Design Guidelines for Advanced Traveler Information Systems (ATIS) and Commercial Vehicle Operations (CVO) , 1998 .

[36]  Dario D. Salvucci,et al.  Effects of Memory Rehearsal on Driver Performance: Experiment and Theoretical Account , 2008, Hum. Factors.

[37]  A. Torralba,et al.  The role of context in object recognition , 2007, Trends in Cognitive Sciences.

[38]  H Godthelp,et al.  Vehicle Control During Curve Driving , 1986, Human factors.

[39]  Dario D. Salvucci.  Modeling Driver Behavior in a Cognitive Architecture , 2006, Hum. Factors.

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

[41]  J. Wolfe,et al.  Guided Search 2.0 A revised model of visual search , 1994, Psychonomic bulletin & review.

[42]  S Ullman,et al.  Shifts in selective visual attention: towards the underlying neural circuitry. , 1985, Human neurobiology.

[43]  J. C. Stutts,et al.  Driver inattention, driver distraction and traffic crashes , 2003 .

[44]  Richard J. Hanowski,et al.  IN-VEHICLE INFORMATION SYSTEMS BEHAVIORAL MODEL AND DESIGN SUPPORT: IVIS DEMAND PROTOTYPE SOFTWARE USER'S MANUAL , 2000 .