An Investigation of the Effects of Driver Age When Using Novel Navigation Systems in a Head-Up Display

Although drivers gain experience with age, many older drivers are faced with age-related deteriorations that can lead to a higher crash risk. Head-Up Displays (HUDs) have been linked to significant improvements in driving performance for older drivers by tackling issues related to aging. For this study, two Augmented Reality (AR) HUD virtual car navigation solutions were tested (one screen-fixed, one world-fixed), aiming to improve navigation performance and reduce the discrepancy between younger and older drivers by aiding the appropriate allocation of attention and easing interpretation of navigational information. Twenty-five participants (12 younger, 13 older) undertook a series of drives within a medium-fidelity simulator with three different navigational conditions (virtual car HUD, static HUD arrow graphic, and traditional head-down satnav). Results showed that older drivers tended to achieve navigational success rates similar to the younger group, but experienced higher objective mental workload. Solely for the static HUD arrow graphic, differences in most workload questionnaire items and objective workload between younger and older participants were not significant. The virtual car led to improved navigation performance of all drivers, compared to the other systems. Hence, both AR HUD systems show potential for older drivers, which needs to be further investigated in a real-world driving context.

[1]  B. Fildes,et al.  Distraction and the Older Driver , 2009 .

[2]  Raymond J. Kiefer.  QUANTIFYING HEAD-UP DISPLAY (HUD) PEDESTRIAN DETECTION BENEFITS FOR OLDER DRIVERS , 1998 .

[3]  David Crundall,et al.  Effects of experience and processing demands on visual information acquisition in drivers , 1998 .

[4]  Gudrun Klinker,et al.  Perception thresholds for augmented reality navigation schemes in large distances , 2008, 2008 7th IEEE/ACM International Symposium on Mixed and Augmented Reality.

[5]  Steven J Kass,et al.  Age differences in cognitive and psychomotor abilities and simulated driving. , 2010, Accident; analysis and prevention.

[6]  Alois Ferscha,et al.  Augmented reality navigation systems , 2006, Universal Access in the Information Society.

[7]  Sandra G. Hart,et al.  Nasa-Task Load Index (NASA-TLX); 20 Years Later , 2006 .

[8]  Mark J. Rapoport,et al.  Impact of Psychotropic Medications on Simulated Driving , 2007, CNS drugs.

[9]  Alain Muzet,et al.  Sleepiness in professional drivers: effect of age and time of day. , 2005, Accident; analysis and prevention.

[10]  Anind K. Dey,et al.  Simulated augmented reality windshield display as a cognitive mapping aid for elder driver navigation , 2009, CHI.

[11]  Rob Gray,et al.  I’ll Show You the Way: Risky Driver Behavior When “Following a Friend” , 2017, Front. Psychol..

[12]  Stephen A. Brewster,et al.  Using Landmarks to Support Older People in Navigation , 2004, Mobile HCI.

[13]  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.

[14]  S. Geisser,et al.  On methods in the analysis of profile data , 1959 .

[15]  Marlos Viana,et al.  SHORT NOTE Relative Effects of Age and Compromised Vision on Driving Performance , 1995, Hum. Factors.

[16]  Normand Teasdale,et al.  Mental workload when driving in a simulator: effects of age and driving complexity. , 2009, Accident; analysis and prevention.

[17]  F. Craik.  Levels of processing: Past, present... and future? , 2002, Memory.

[18]  Beth T. Stalvey,et al.  Driving avoidance and functional impairment in older drivers. , 1998, Accident; analysis and prevention.

[19]  M. M. Johnson,et al.  Age differences in decision making: a process methodology for examining strategic information processing. , 1990, Journal of gerontology.

[20]  Tim Paek,et al.  Augmented reality vs. street views: a driving simulator study comparing two emerging navigation aids , 2011, Mobile HCI.

[21]  Joseph L. Gabbard,et al.  Behind the Glass: Driver Challenges and Opportunities for AR Automotive Applications , 2014, Proceedings of the IEEE.

[22]  E. Braver,et al.  Fragility versus excessive crash involvement as determinants of high death rates per vehicle-mile of travel among older drivers. , 2003, Accident; analysis and prevention.

[23]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[24]  L. Cermak,et al.  Age Differences in Memory: The Roles of Attention and Depth of Processing , 2014 .

[25]  Thierry Bellet,et al.  Cognitive Modelling and Computational Simulation of Drivers Mental Activities , 2007 .

[26]  Christopher D. Wickens,et al.  Object versus space-based models of visual attention: Implications for the design of head-up displays , 1995 .

[27]  P. Chapman,et al.  Visual Search of Driving Situations: Danger and Experience , 1998, Perception.

[28]  Yung-ching Liu.  Effects of using head-up display in automobile context on attention demand and driving performance , 2003 .

[29]  Frederick C. Harris,et al.  ARS VEHO: Augmented Reality System for VEHicle Operation , 2005, Computers and Their Applications.

[30]  Alain Muzet,et al.  Influence of age, speed and duration of monotonous driving task in traffic on the driver’s useful visual field , 2004, Vision Research.

[31]  Gary E. Burnett.  'Turn right at the King's Head' : drivers' requirements for route guidance information , 1998 .

[32]  David R. Large,et al.  Augmenting Landmarks During the Head-Up Provision of In-Vehicle Navigation Advice , 2017, Int. J. Mob. Hum. Comput. Interact..

[33]  A. R. Dobbs,et al.  Age differences in the interpretation of misaligned "You-Are-Here" maps. , 1994, Journal of gerontology.

[34]  Shinyoung Park,et al.  Influences of personal preference on product usability , 2006, CHI Extended Abstracts.

[35]  D. Shinar,et al.  Aggressive driving: an observational study of driver, vehicle, and situational variables. , 2004, Accident; analysis and prevention.

[36]  Ronald R. Mourant,et al.  Measuring Divided-Attention Capability of Young and Older Drivers , 2001 .

[37]  David Crundall,et al.  Driver's visual attention as a function of driving experience and visibility. Using a driving simulator to explore drivers' eye movements in day, night and rain driving. , 2010, Accident; analysis and prevention.

[38]  Peter Chapman,et al.  Prefrontal Cortex Activation and Young Driver Behaviour: A fNIRS Study , 2016, PloS one.

[39]  David R. Large,et al.  An investigation of augmented reality presentations of landmark-based navigation using a head-up display , 2015, AutomotiveUI.

[40]  Ming-Hui Wen,et al.  Comparison of head-up display (HUD) vs. head-down display (HDD): driving performance of commercial vehicle operators in Taiwan , 2004, Int. J. Hum. Comput. Stud..

[41]  S. Hart,et al.  Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research , 1988 .

[42]  Amanda N Stephens,et al.  Prospective memory while driving: comparison of time- and event-based intentions , 2017, Ergonomics.