Age and cross-cultural comparison of drivers’ cognitive workload and performance in simulated urban driving

Driving demands significant psychomotor attention and requires even more when drivers are engaged in secondary tasks that increase cognitive workload and divert attention. It is well established that age influences driving risk. Less is known about how culture impacts changes in attention. We conducted parallel driving simulations in the US and Korea to measure the extent to which age and culture influence dual-task performance. There were 135 participants divided into two groups: a younger group aged 20∼29, and an older group aged 60∼69. Whereas some differences by culture appeared in absolute control measures, the younger participants showed similar mean velocity and compensatory patterns associated with increased cognitive load in the urban setting; however, the results from the older samples were less similar.

[1]  H. Johnson,et al.  A comparison of 'traditional' and multimedia information systems development practices , 2003, Inf. Softw. Technol..

[2]  S. Folstein,et al.  "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. , 1975, Journal of psychiatric research.

[3]  Denise C. Park,et al.  Handbook of the Psychology of Aging , 1979 .

[4]  Lisbeth Harms,et al.  Variation in drivers' cognitive load. Effects of driving through village areas and rural junctions , 1991 .

[5]  D. Damos Multiple-task performance , 2020 .

[6]  Lawrence R. Zeitlin Subsidiary task measures of driver mental workload: a long-term field study , 1993 .

[7]  S Dienstfrey,et al.  NATIONAL SURVEY OF SPEEDING AND OTHER UNSAFE DRIVING ACTIONS. VOLUME I: METHODOLOGY , 1998 .

[8]  Gerald Matthews,et al.  Individual differences in driver stress vulnerability in a Japanese sample , 1999 .

[9]  D. E Haigney,et al.  Concurrent mobile (cellular) phone use and driving performance: task demand characteristics and compensatory processes , 2000 .

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

[11]  P. Park,et al.  SIMULATOR-BASED HUMAN FACTORS EVALUATION OF AUTOMATED HIGHWAY SYSTEM , 2006 .

[12]  B. Reimer,et al.  Using self-reported data to assess the validity of driving simulation data , 2006, Behavior research methods.

[13]  Bryan Reimer,et al.  The Use of Heart Rate in a Driving Simulator as an Indicator of Age-Related Differences in Driver Workload , 2006 .

[14]  B. Reimer,et al.  Task-Induced Fatigue and Collisions in Adult Drivers with Attention Deficit Hyperactivity Disorder , 2007, Traffic injury prevention.

[15]  A. Pohlmeyer,et al.  The association between heart rate reactivity and driving performance under dual task demands in late middle age drivers , 2008 .

[16]  Ying Wang,et al.  A Comparison of the Effect of a Low to Moderately Demanding Cognitive Task on Simulated Driving Performance and Heart Rate in Middle Aged and Young Adult Drivers , 2008, 2008 International Conference on Cyberworlds.

[17]  Bryan Reimer,et al.  Impact of Cognitive Task Complexity on Drivers’ Visual Tunneling , 2009 .

[18]  Timo Lajunen,et al.  Cross-cultural differences in drivers' speed choice. , 2009, Accident; analysis and prevention.

[19]  T. Rundmo,et al.  Perceptions of traffic risk in an industrialised and a developing country , 2009 .

[20]  J. Dusek,et al.  Impact of Incremental Increases in Cognitive Workload on Physiological Arousal and Performance in Young Adult Drivers , 2009 .