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Driving Behavior Based Relative Risk Evaluation Using a Nonparametric Optimization Method

Author

Listed:
  • Qiong Bao

    (School of Transportation, Southeast University, Nanjing 210096, China)

  • Hanrun Tang

    (School of Transportation, Southeast University, Nanjing 210096, China)

  • Yongjun Shen

    (School of Transportation, Southeast University, Nanjing 210096, China)

Abstract

Evaluating risks when driving is a valuable method by which to make people better understand their driving behavior, and also provides the basis for improving driving performance. In many existing risk evaluation studies, however, most of the time only the occurrence frequency of risky driving events is considered in the time dimension and fixed weights allocation is adopted when constructing a risk evaluation model. In this study, we develop a driving behavior-based relative risk evaluation model using a nonparametric optimization method, in which both the frequency and the severity level of different risky driving behaviors are taken into account, and the concept of relative risk instead of absolute risk is proposed. In the case study, based on the data from a naturalistic driving experiment, various risky driving behaviors are identified, and the proposed model is applied to assess the overall risk related to the distance travelled by an individual driver during a specific driving segment, relative to other drivers on other segments, and it is further compared with an absolute risk evaluation. The results show that the proposed model is superior in avoiding the absolute risk quantification of all kinds of risky driving behaviors, and meanwhile, a prior knowledge on the contribution of different risky driving behaviors to the overall risk is not required. Such a model has a wide range of application scenarios, and is valuable for feedback research relating to safe driving, for a personalized insurance assessment based on drivers’ behavior, and for the safety evaluation of professional drivers such as ride-hailing drivers.

Suggested Citation

  • Qiong Bao & Hanrun Tang & Yongjun Shen, 2021. "Driving Behavior Based Relative Risk Evaluation Using a Nonparametric Optimization Method," IJERPH, MDPI, vol. 18(23), pages 1-15, November.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:23:p:12452-:d:688655
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    References listed on IDEAS

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    2. Bian, Yiyang & Yang, Chen & Zhao, J. Leon & Liang, Liang, 2018. "Good drivers pay less: A study of usage-based vehicle insurance models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 107(C), pages 20-34.
    3. Dulebenets, Maxim A. & Abioye, Olumide F. & Ozguven, Eren Erman & Moses, Ren & Boot, Walter R. & Sando, Thobias, 2019. "Development of statistical models for improving efficiency of emergency evacuation in areas with vulnerable population," Reliability Engineering and System Safety, Elsevier, vol. 182(C), pages 233-249.
    4. Abioye, Olumide F. & Dulebenets, Maxim A. & Ozguven, Eren Erman & Moses, Ren & Boot, Walter R. & Sando, Thobias, 2020. "Assessing perceived driving difficulties under emergency evacuation for vulnerable population groups," Socio-Economic Planning Sciences, Elsevier, vol. 72(C).
    5. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, July.
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    Cited by:

    1. Walaa Othman & Alexey Kashevnik & Ammar Ali & Nikolay Shilov, 2022. "DriverMVT: In-Cabin Dataset for Driver Monitoring including Video and Vehicle Telemetry Information," Data, MDPI, vol. 7(5), pages 1-13, May.

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