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The Emergence Characteristics of Driver’s Intentions Influenced by Different Emotions

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  • Xiaoyuan Wang

    (College of Electromechanical Engineering, Qingdao University of Science & Technology, Qingdao 266000, China
    Joint Laboratory for Internet of Vehicles, Ministry of Education-China Mobile Communications Corporation, Tsinghua University, Beijing 100084, China)

  • Yongqing Guo

    (Joint Laboratory for Internet of Vehicles, Ministry of Education-China Mobile Communications Corporation, Tsinghua University, Beijing 100084, China
    School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China)

  • Chenglin Bai

    (School of Physics Science and Communication Engineering, Liaocheng University, Liaocheng 252000, China)

  • Quan Yuan

    (State Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China)

  • Shanliang Liu

    (College of Electromechanical Engineering, Qingdao University of Science & Technology, Qingdao 266000, China)

  • Xuegang (Jeff) Ban

    (Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195, USA)

Abstract

Drivers’ behavioral intentions can affect traffic safety, vehicle energy use, and gas emission. Drivers’ emotions play an important role in intention generation and decision making. Determining the emergence characteristics of driver intentions influenced by different emotions is essential for driver intention recognition. This study focuses on developing a driver’s intention emergence model with the involvement of driving emotion on two-lane urban roads. Driver emotions were generated using various ways, including visual stimuli (video and picture), material incentives, and spiritual rewards. Real and virtual driving experiments were conducted to collect the multi-source dynamic data of human–vehicle–environment. The driver intention emergence model was constructed based on an artificial neural network, to identify the influences of drivers’ emotions on intention, as well as the evolution characteristics of drivers’ intentions in different emotions. The results show that the proposed model can make accurate predictions on driver intention emergence. The findings of this study can be used to improve drivers’ behavior, in order to create more efficient and safe driving. It can also provide a theoretical foundation for the development of an active safety system for vehicles and an intelligent driving command system.

Suggested Citation

  • Xiaoyuan Wang & Yongqing Guo & Chenglin Bai & Quan Yuan & Shanliang Liu & Xuegang (Jeff) Ban, 2021. "The Emergence Characteristics of Driver’s Intentions Influenced by Different Emotions," Sustainability, MDPI, vol. 13(23), pages 1-13, December.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:23:p:13292-:d:692444
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    References listed on IDEAS

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    2. Chen, Hung-Bin & Yeh, Shih-Shuo & Huan, Tzung-Cheng, 2014. "Nostalgic emotion, experiential value, brand image, and consumption intentions of customers of nostalgic-themed restaurants," Journal of Business Research, Elsevier, vol. 67(3), pages 354-360.
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