Driving errors, estimated performance and individual characteristics under simulated and real road traffic conditions

• Verfasst von: Faschina, Silvia [VerfasserIn]
• Verfasst von: Stieglitz, Rolf-Dieter [VerfasserIn]
• Verfasst von: Muri, Raphaela [VerfasserIn]
• Verfasst von: Strohbeck-Kühner, Peter [VerfasserIn]
• Verfasst von: Graf, Marc [VerfasserIn]
• Verfasst von: Mager, Ralph [VerfasserIn]
• Verfasst von: Pflueger, Marlon O. [VerfasserIn]
• Titel: Driving errors, estimated performance and individual characteristics under simulated and real road traffic conditions
• Titelzusatz: a validation study
• Verf.angabe: Silvia Faschina, Rolf-Dieter Stieglitz, Raphaela Muri, Peter Strohbeck-Kühner, Marc Graf, Ralph Mager, Marlon O. Pflueger
• E-Jahr: 2021
• Jahr: 8 September 2021
• Umfang: 17 S.
• Fussnoten: Gesehen am 01.12.2021
• Titel Quelle: Enthalten in: Transportation research / F
• Ort Quelle: Amsterdam [u.a.] : Elsevier Science, 1998
• Jahr Quelle: 2021
• Band/Heft Quelle: 82(2021) vom: Okt., Seite 221-237
• ISSN Quelle: 1873-5517
• DOI: doi:10.1016/j.trf.2021.07.018
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Driving behaviour validity
• Sach-SW: Driving errors
• Sach-SW: Driving performance
• Sach-SW: Driving simulator
• Sach-SW: Multiple regression
• K10plus-PPN: 1779949138

Abstract

Background - The suitability of driving simulators for the prediction of driving behaviour in road traffic has been able to be confirmed in respect of individual assessment parameters. However, there is a need for overarching approaches that take into account the interaction between various influencing factors in order to establish proof of validity. The aim of this study was to explore the validity of our driving simulator in respect of its ability to predict driving behaviour based on participants‘ observed driving errors and driver’s individual characteristics. - Method - 41 healthy participants were assessed both in a Smart-Realo-Simulator and on the road. By means of linear modelling, the correlation between observed driving errors was investigated. In addition, the influence of self-reported and externally assessed driving behaviour as well as individual parameters (education and training; driving history) were analysed. - Results - By including these factors, 58% of the variance could be explained. For observed driving errors, a relative validity was established. For self-reported and externally assessed driving behaviour, an absolute to relative validity emerged. The amount of time spent in education and training proved to have a significant influence on driving performance in the simulator, but not on the road. - Discussion - In general, our results confirmed the validity of our driving simulator with regard to observed and self-reported driving behaviour. It emerged that education and training as potential indicators of cognitive resources played a differential role regarding the study conditions. Since real road driving is considerably automated in experienced drivers, this result suggests that simulation-related behavioural regulation is challenged by additional cognitive demands as opposed to behavioural regulation extending to real road driving. However, the source of these additional cognitive demands remains currently elusive and may form the subject of future research.