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Factors Influencing Young Drivers’ Willingness to Engage in Risky Driving Behavior: Continuous Lane-Changing

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  • Xiaoxiao Wang

    (Department of Traffic Engineering, School of Transportation, Wuhan University of Technology, Wuhan 430063, China
    Department of Traffic Engineering, School of Civil and Transportation Engineering, Henan University of Urban Construction, Pingdingshan 467032, China)

  • Liangjie Xu

    (Department of Traffic Engineering, School of Transportation, Wuhan University of Technology, Wuhan 430063, China
    Hubei Key Laboratory of Power System Design and Test for Electrical Vehicle, Hubei University of Arts and Science, Xiangyang 441053, China)

Abstract

Young adults have a tendency to drive unsafely and put themselves at a high level of risk. Continuous lane-changing is one such kind of risky behavior. This study aimed to investigate the factors that influence young drivers based on an integrated model of the prototype willingness model (PWM) and the theory of planned behavior (TPB). The validity of the model was evaluated by data collected from 481 young drivers through an online questionnaire. The structural equation model was used to test the proposed model, and the findings indicated that young drivers’ willingness to engage in continuous lane-changing was influenced by attitude, subjective norms, perceived behavioral control, perceived risk, prototype similarity, and prototype favorability. The integrated model of PWM-TPB accounted for 58.3% of the variance in young drivers’ willingness, and the findings possess implications for designing effective interventions.

Suggested Citation

  • Xiaoxiao Wang & Liangjie Xu, 2021. "Factors Influencing Young Drivers’ Willingness to Engage in Risky Driving Behavior: Continuous Lane-Changing," Sustainability, MDPI, vol. 13(11), pages 1-18, June.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:11:p:6459-:d:569897
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    References listed on IDEAS

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    Cited by:

    1. Guo, Yinjia & Chen, Yanyan & Gu, Xin & Guo, Jifu & Zheng, Shuyan & Zhou, Yuntong, 2024. "Dynamic traffic graph based risk assessment of multivehicle lane change interaction scenarios," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 643(C).
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    3. Nattawut Pumpugsri & Wanchai Rattanawong & Varin Vongmanee, 2023. "Development of a Safety Heavy-Duty Vehicle Model Considering Unsafe Acts, Unsafe Conditions and Near-Miss Events Using Structural Equation Model," Sustainability, MDPI, vol. 15(16), pages 1-20, August.

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