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Does the Familiarity of Road Regulation Contribute to Driving Violation? A Simulated Study on Familiar and Unfamiliar Road Intersections among Young Chinese Drivers

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Advances in Human Aspects of Transportation (AHFE 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 597))

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Abstract

Road accidents represent the primary cause of death among young drivers. To understand the emerging issue of young drivers’ involvement in traffic accidents abroad, risk-taking behaviors were investigated in familiar and unfamiliar driving situations. Twenty-two young Chinese drivers completed a road regulation test followed by a simulated test drive. The number of traffic violations and accidents in familiar and unfamiliar driving intersections were correlated to road regulation knowledge, risk perception scores and to self-assessment of driving skills. Significant number of mistakes was found in risk-taking situations, regardless of the familiarity of the situation, especially for drivers that presented high ratings of self-assessed driving skills. Results show that risk-taking behaviors while driving in unfamiliar conditions are mediated by psychological factors, like self-assessment of being a good driver, more than the actual knowledge of road regulation rules. Implications for international driving can be considered for future research development.

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Acknowledgments

The authors are grateful to the participants for investing their efforts in this study, also thanks to the support of I.DRIVE Lab (Interaction Between Driver, Road Infrastructure, Vehicle, And Environment – Politecnico di Milano - www.idrive.polimi.it) and Chinese Scholarship Council.

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Correspondence to Jun Yi .

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Huang, S., Ruscio, D., Ariansyah, D., Yi, J., Bordegoni, M. (2018). Does the Familiarity of Road Regulation Contribute to Driving Violation? A Simulated Study on Familiar and Unfamiliar Road Intersections among Young Chinese Drivers. In: Stanton, N. (eds) Advances in Human Aspects of Transportation. AHFE 2017. Advances in Intelligent Systems and Computing, vol 597. Springer, Cham. https://doi.org/10.1007/978-3-319-60441-1_31

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  • DOI: https://doi.org/10.1007/978-3-319-60441-1_31

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