Driving errors, estimated performance and individual characteristics under simulated and real road traffic conditions – A validation study

The suitability of driving simulators for the prediction of driving behavior 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 the driving simulator in respect of its ability to predict driving behavior based on participants‘ observed driving errors and driver’s individual characteristics. 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 behavior as well as individual parameters (education and training; driving history) were analyzed. 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 behavior, 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. In general, the results confirmed the validity of the driving simulator with regard to observed and self-reported driving behavior. 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 behavioral regulation is challenged by additional cognitive demands as opposed to behavioral 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.

• Record URL:
  https://doi.org/10.1016/j.trf.2021.07.018
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S1369847821001881
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/13698478
• Supplemental Notes:
  • © 2021 Silvia Faschina, et al. Published by Elsevier Ltd. Abstract reprinted with permission of Elsevier.
• Authors:
  • Faschina, Silvia
  • Stieglitz, Rolf-Dieter
  • Muri, Raphaela
  • Strohbeck-Kühner, Peter
  • Graf, Marc
  • Mager, Ralph
  • Pflueger, Marlon O
• Publication Date: 2021-10

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 221-237
• Serial:
  • Transportation Research Part F: Traffic Psychology and Behaviour
  • Volume: 82
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 1369-8478
  • Serial URL: http://www.sciencedirect.com/science/journal/13698478

Subject/Index Terms

• TRT Terms: Behavior; Cognition; Driver performance; Driving simulators; Validation
• Subject Areas: Highways; Safety and Human Factors;

Filing Info

• Accession Number: 01783605
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 28 2021 3:49PM