Measuring driving styles

van Huysduynen, Hanneke Hooft; Terken, Jacques; Martens, Jean-Bernard; Eggen, Berry · 2015 · OpenAlex-citations

DOI: 10.1145/2799250.2799266

archive: archived pipeline: cataloged verified

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Summary

This study validates the Multidimensional Driving Style Inventory (MDSI), a self-report questionnaire originally developed in Israel, for use in the Netherlands and Belgium. The research is motivated by the need to understand driver compliance with Advanced Driver Assistance Systems (ADAS). Since ADAS effectiveness depends on how well systems align with individual behavioral patterns, accurately measuring driving styles is crucial for tailoring interventions to specific driver groups. The authors review existing questionnaires, noting that many focus narrowly on stress, aberrant behavior, or risk-taking rather than comprehensive driving styles, leading them to validate the broader MDSI. The methodology involved an online survey distributed via social media and automotive forums. The final sample consisted of 364 participants, predominantly from the Netherlands (54%) and Belgium (32%), with a mean age distribution spanning 17 to over 65 years. Participants completed the 44-item MDSI, rating statements on a six-point scale. The researchers conducted three statistical analyses: a Varimax rotation factor analysis targeting eight factors, a second Varimax analysis targeting six factors, and an Oblique Principal Component Cluster Analysis (OPCCA) to check for non-orthogonal dimensions. One item was excluded due to missing data, and one participant was removed for inconsistent responses. The results indicated that the original eight-factor structure did not fully replicate. The initial eight-factor analysis revealed two factors with insufficient items and low reliability. The subsequent six-factor analysis identified six distinct styles: Angry driving (14% variance), Risky driving (11%), Anxious driving (6%), Dissociative driving (5%), Careful driving (4%), and Distress-reduction driving (3%). However, further refinement using OPCCA and item removal based on reliability constraints resulted in a stable five-factor model comprising 24 items: Angry, Anxious, Dissociative, Distress-reduction, and Careful driving. The "Risky" and "Careful" factors merged in the OPCCA analysis. The study also explored driver profiling, finding that simple averaging methods lacked discriminating power, while a threshold-based method successfully categorized 75% of participants into profiles consisting of one or two dominant driving styles. The significance of this work lies in providing a validated, shorter version of the MDSI for Western European populations. By establishing five stable factors, the study offers a reliable tool for categorizing drivers into specific profiles. This enables researchers and engineers to better predict how different driver groups will interact with ADAS, facilitating the development of systems that respect individual driving styles to enhance acceptance and safety. The findings support the concept of multidimensional driver profiles rather than single-style classifications, suggesting that future ADAS design should account for complex behavioral combinations.

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.

Topics

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• dbq psychometrics
• personality driving
• anger road rage
• cultural cross national
• stress driving
• sensation seeking

Information type

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• Methodological Resource: validation psychometrics