ORIGINAL PAPER
Tracking risk-taking behind the wheel: Which indicator of risky driving is the most useful in driving simulator studies? A pilot study
 
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1
Military Institute of Aviation Medicine, Warsaw, Poland (Department of Psychophysiological Measurements and Human Factor Research)
 
2
Military Institute of Aviation Medicine, Warsaw, Poland (Department of Aviation Psychology)
 
3
Military Institute of Aviation Medicine, Warsaw, Poland (Department of Simulator Studies and Aeromedical Training)
 
 
Online publication date: 2026-05-11
 
 
Corresponding author
Paulina Baran   

Military Institute of Aviation Medicine, Department of Psychophysiological Measurements and Human Factor Research, Krasińskiego 54/56, 01-755 Warszawa, Poland
 
 
 
HIGHLIGHTS
  • Maximum-minimum speed difference is the most reliable risky driving indicator.
  • Dynamic speed change indicators are more useful than simple speed parameters.
  • Five well-chosen scenarios provided a reliable risky driving assessment.
  • Multi-method assessment with control drives enhances driving interpretation.
  • Risky drivers show smaller speed adjustments in simulator decision-making tasks.
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ABSTRACT
Objectives: This study evaluated the validity and usefulness of selected indicators for assessing risky driving behavior in truck simulator research, which is critical for developing ecologically valid and reliable research methods in the domain of traffic safety and public health. The aims were to present various risky driving indicators, assess their validity, compare their utility, and provide guidance for future simulator-based research. Material and methods: Thirty professional truck drivers took part in experimental and control drives in a truck simulator. The experimental drive contained 12 decision-making situations requiring driver response, while the control scenario followed the same route without these situations. Data included qualitative behavioral indicators assessed by an observer (speed reduction, stopping, bypassing, no reaction) and quantitative speed parameters automatically recorded by the simulator. Participants also provided their traffic violation history. Analyses employed mixed linear models, intraclass correlation coefficients, and reliability testing. Results: Only 5 of 12 decision-making situations demonstrated diagnostic value in differentiating drivers. Among qualitative indicators, speed reduction proved most useful, while among quantitative measures, the difference between maximum and minimum speed showed the highest reliability (α = 0.71). Cluster analysis identified 2 driver groups that significantly differed in their speed adjustment behavior (p = 0.033, d = 0.7), with drivers reporting more traffic violations showing smaller speed adjustments. Conclusions: This pilot study demonstrates that dynamic indicators based on speed changes are more useful for assessing risky driving than simple speed parameters. Acceptable reliability (α > 0.70) was achieved with a set of 5 appropriately selected decision-making situations. Driving simulator research benefits from careful selection of test scenarios and a multi-method approach to evaluation, including control drive comparisons. These preliminary findings provide practical guidance for designing simulator-based assessments of risky driving behavior. Int J Occup Med Environ Health. 2026;39(2)
eISSN:1896-494X
ISSN:1232-1087
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