Intraindividual variability in driving simulator parameters of healthy drivers of different ages |
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| Institution: | 1. Department of Psychology, School of Philosophy, National and Kapodistrian University of Athens, Athens, Greece;2. 1st University Department of Neurology, Eginiteion Hospital, National and Kapodistrian University of Athens, Athens, Greece;3. Delft University of Technology, Faculty of Technology, Policy and Management, Delft, The Netherlands;4. School of Civil Engineering, Department of Transportation Planning and Engineering, National Technical University of Athens, Athens, Greece;1. Queensland University of Technology (QUT), Centre for Accident Research and Road Safety – Queensland (CARRS-Q), Australia;2. Adolescent Risk Research Unit (ARRU), Sunshine Coast Mind and Neuroscience – Thompson Institute, University of the Sunshine Coast (USC), Australia;3. Consortium of Adolescent Road Safety (cadrosa.org);1. School of Civil and Construction Engineering, Oregon State University, United States;2. Department of Civil and Environmental Engineering, University of Wisconsin Madison, United States;3. College of Transportation Engineering, Tongji University, China;1. LS2N (Laboratoire des Sciences du Numérique de Nantes), UMR CNRS 6004, Nantes, France;2. Institut Ophtamologique de l’Ouest Jules Verne, Nantes, France;1. CARIAD SE, Carnotstraße 4, 10587 Berlin, Germany;2. Elektronikentwicklung Volkswagen Aktiengesellschaft, Brieffach 011/1732, 38436 Wolfsburg, Germany |
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| Abstract: | Intraindividual variability is a fundamental behavioural characteristic of aging but has been examined to a very limited extent in driving. This study investigated intraindividual variability in driving simulator measures in healthy drivers of different ages using the coefficient of variation (COV) as a variability measure. Participants were healthy volunteers who were regular drivers, who were divided into a “young” group, a “middle-aged” group, and an “old” group. They drove in two environments (rural, 72 drivers; urban, 60 drivers), under conditions of moderate and high traffic load, without and with distraction (conversation). Significant differences in COV were observed in the rural condition for headway distance and lateral position as a function of traffic load, with high traffic (without and with distraction) resulting in increased COV of headway and decreased COV of lateral position. Significant differences in COV were observed in the urban condition for headway distance only, with high traffic (without and with distraction) resulting in increased COV of headway. No age effects were found for any of the driving conditions. The results indicate that traffic load affected headway distance and lateral position in opposite directions in all three age groups: high traffic resulted in increased variability of headway in both rural and urban conditions but in decreased variability of lateral position in the rural conditions compared to moderate traffic irrespective of distraction. The study indicates that driving conditions affect the intraindividual variability of driving measures in selective ways, which may be linked to the extent of automatization of the driving variables and to adaptive changes to traffic condition challenges. |
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| Keywords: | Driver behaviour Age Traffic load Distraction Skilled performance |
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