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A Comprehensive Review of Driving Style Evaluation Approaches and Product Designs Applied to Vehicle Usage-Based Insurance

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  • Wei Nai

    (Department of Electronic and Information Engineering, Tongji Zhejiang College, Jiaxing 314051, China)

  • Zan Yang

    (Faculty of Science, Tongji Zhejiang College, Jiaxing 314051, China)

  • Yinzhen Wei

    (Department of Electronic and Information Engineering, Tongji Zhejiang College, Jiaxing 314051, China)

  • Jierui Sang

    (Department of Electronic and Information Engineering, Tongji Zhejiang College, Jiaxing 314051, China)

  • Jialu Wang

    (Department of Electronic and Information Engineering, Tongji Zhejiang College, Jiaxing 314051, China)

  • Zhou Wang

    (Department of Electronic and Information Engineering, Tongji Zhejiang College, Jiaxing 314051, China)

  • Peiyu Mo

    (Department of Electronic and Information Engineering, Tongji Zhejiang College, Jiaxing 314051, China)

Abstract

Vehicle insurance is a very important source of income for insurance companies, and it is closely related to the driving style performed by driving behavior. Different driving styles can better reflect the driving risk than the number of violations, claims, and other static statistic data. Subdivide the vehicle insurance market according to the personal characteristics and driving habits of the insured vehicles, and studying the personalized vehicle insurance products, will help the insurance companies to improve their income, help the drivers to change their bad driving habits, and thus help to realize the healthy development of the vehicle insurance industry. In the past 20 to 30 years, more and more insurance companies around the world have launched vehicle usage-based insurance (UBI) products based on driving style analysis. However, up to now, there are few comprehensive reports on commercial vehicle UBI products and their core driving risk assessment methods. On the basis of literature indexing on the Web of Science and other academic platforms by using the keywords involved in vehicle UBI, over 100 relevant works of literature were screened in this paper, and a detailed and comprehensive discussion on the driving style evaluation methods and the design of commercial vehicle UBI products during the past 20 to 30 years has been made, hoping to get a full understanding of the possible factors affecting driving style and the collectible data that can reflect these factors, and to get a full grasp of the developing status, challenges and future trends in vehicle insurance branch of the Internet of Vehicles (IoV) industry.

Suggested Citation

  • Wei Nai & Zan Yang & Yinzhen Wei & Jierui Sang & Jialu Wang & Zhou Wang & Peiyu Mo, 2022. "A Comprehensive Review of Driving Style Evaluation Approaches and Product Designs Applied to Vehicle Usage-Based Insurance," Sustainability, MDPI, vol. 14(13), pages 1-20, June.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:13:p:7705-:d:846598
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    References listed on IDEAS

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    1. Aaron S. Edlin & Pinar Karaca-Mandic, 2006. "The Accident Externality from Driving," Journal of Political Economy, University of Chicago Press, vol. 114(5), pages 931-955, October.
    2. Parry, Ian W. H., 2004. "Comparing alternative policies to reduce traffic accidents," Journal of Urban Economics, Elsevier, vol. 56(2), pages 346-368, September.
    3. Desyllas, Panos & Sako, Mari, 2013. "Profiting from business model innovation: Evidence from Pay-As-You-Drive auto insurance," Research Policy, Elsevier, vol. 42(1), pages 101-116.
    4. Philippe Donder & Jean Hindriks, 2009. "Adverse selection, moral hazard and propitious selection," Journal of Risk and Uncertainty, Springer, vol. 38(1), pages 73-86, February.
    5. Alma Cohen, 2005. "Asymmetric Information and Learning: Evidence from the Automobile Insurance Market," The Review of Economics and Statistics, MIT Press, vol. 87(2), pages 197-207, May.
    6. Amy Finkelstein & Kathleen McGarry, 2006. "Multiple Dimensions of Private Information: Evidence from the Long-Term Care Insurance Market," American Economic Review, American Economic Association, vol. 96(4), pages 938-958, September.
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    Cited by:

    1. Yiwen Zhou & Fengxiang Guo & Simin Wu & Wenyao He & Xuefei Xiong & Zheng Chen & Dingan Ni, 2022. "Safety and Economic Evaluations of Electric Public Buses Based on Driving Behavior," Sustainability, MDPI, vol. 14(17), pages 1-17, August.
    2. Tiande Mo & Yu Li & Kin-tak Lau & Chi Kin Poon & Yinghong Wu & Yang Luo, 2022. "Trends and Emerging Technologies for the Development of Electric Vehicles," Energies, MDPI, vol. 15(17), pages 1-34, August.
    3. Maksymilian Mądziel, 2023. "Vehicle Emission Models and Traffic Simulators: A Review," Energies, MDPI, vol. 16(9), pages 1-31, May.
    4. Serkan Eti & Hasan Dinçer & Hasan Meral & Serhat Yüksel & Yaşar Gökalp, 2024. "Insurtech in Europe: identifying the top investment priorities for driving innovation," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-24, December.

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