Three-Dimensional Multiple Object Tracking Speed Thresholds are Associated with Measures of Simulated Driving Performance in Older Drivers

We assessed the relationship between three-dimensional multiple-object-tracking (3D-MOT) ability and older driver simulated driving performance. Participants included 30 older drivers from the local community who completed two experimental driving scenarios, as well as a three-dimensional multiple object tracking task, called the 3D-MOT task. The speed thresholds on the 3D-MOT task were strongly negatively associated with lane deviation and crash rates during a simulated highway drive. Our findings help to expand the existing knowledge regarding multiple object tracking and driving, as it is commonly assumed that some aspects of driving include the ability to track the movement of many objects. Our findings further elucidate the relationship that motion processing has with driving performance in the older driver population.

[1]  J. Enns,et al.  Paying attention behind the wheel: a framework for studying the role of attention in driving , 2004 .

[2]  C. Feria.  Speed has an effect on multiple-object tracking independently of the number of close encounters between targets and distractors , 2013, Attention, perception & psychophysics.

[3]  Lana M Trick,et al.  Multiple-object tracking while driving: the multiple-vehicle tracking task , 2014, Attention, perception & psychophysics.

[4]  T. Horowitz,et al.  The role of location and motion information in the tracking and recovery of moving objects , 2007, Perception & psychophysics.

[5]  J. Hyönä,et al.  Is multiple object tracking carried out automatically by an early vision mechanism independent of higher‐order cognition? An individual difference approach , 2004 .

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

[7]  R. Allard,et al.  Healthy Older Observers Show Equivalent Perceptual-Cognitive Training Benefits to Young Adults for Multiple Object Tracking , 2013, Front. Psychol..

[8]  L. Trick,et al.  Age-related differences in multiple-object tracking. , 2005, The journals of gerontology. Series B, Psychological sciences and social sciences.

[9]  J. Hyönä,et al.  Position tracking and identity tracking are separate systems: Evidence from eye movements , 2016, Cognition.

[10]  Z W Pylyshyn,et al.  Tracking multiple independent targets: evidence for a parallel tracking mechanism. , 1988, Spatial vision.

[11]  E. Mingolla,et al.  Dynamics of Attention in Depth: Evidence from Multi-Element Tracking , 2002, Perception.

[12]  Alex R Bowers,et al.  Can we improve clinical prediction of at-risk older drivers? , 2013, Accident; analysis and prevention.

[13]  Rui Ni,et al.  MOT Capacity is Compromised in Ecological 3D Environments. , 2015, Journal of vision.

[14]  Cary S Feria.  The distribution of attention within objects in multiple-object scenes: Prioritization by spatial probabilities and a center bias , 2008, Perception & psychophysics.

[15]  J. Cummings,et al.  The Montreal Cognitive Assessment, MoCA: A Brief Screening Tool For Mild Cognitive Impairment , 2005, Journal of the American Geriatrics Society.

[16]  J. Faubert,et al.  Perceptual-Cognitive Training of Athletes , 2012 .

[17]  Rémy Allard,et al.  Impact of stereoscopic vision and 3D representation of visual space on multiple object tracking performance , 2010 .

[18]  F. Previc.  The neuropsychology of 3-D space. , 1998, Psychological bulletin.

[19]  Janine G. Walker,et al.  Cognitive, sensory and physical factors enabling driving safety in older adults. , 2005, Clinical psychology review.

[20]  J. Wolfe,et al.  Tracking unique objects , 2007, Perception & psychophysics.

[21]  Steve Brown,et al.  Cognitive screening tools for predicting unsafe driving behavior among senior drivers , 2014 .