IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i23p12452-d688655.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/23/12452/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/18/23/12452/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yongjun Shen & Onaira Zahoor & Xu Tan & Muhammad Usama & Tom Brijs, 2020. "Assessing Fitness-To-Drive among Older Drivers: A Comparative Analysis of Potential Alternatives to on-Road Driving Test," IJERPH, MDPI, vol. 17(23), pages 1-18, November.
    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, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Juan F. Dols & Jaime Molina & F. Javier Camacho-Torregrosa & David Llopis-Castelló & Alfredo García, 2021. "Development of Driving Simulation Scenarios Based on Building Information Modeling (BIM) for Road Safety Analysis," Sustainability, MDPI, vol. 13(4), pages 1-21, February.
    2. Song, Chengcheng & Shao, Quan & Zhu, Pei & Dong, Min & Yu, Wenfei, 2023. "An emergency aircraft evacuation simulation considering passenger overtaking and luggage retrieval," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    3. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499, April.
    4. Alperovych, Yan & Hübner, Georges & Lobet, Fabrice, 2015. "How does governmental versus private venture capital backing affect a firm's efficiency? Evidence from Belgium," Journal of Business Venturing, Elsevier, vol. 30(4), pages 508-525.
    5. Oliver Stein & Nathan Sudermann-Merx, 2016. "The Cone Condition and Nonsmoothness in Linear Generalized Nash Games," Journal of Optimization Theory and Applications, Springer, vol. 170(2), pages 687-709, August.
    6. Anastasiou Athanasios & Kalligosfyris Charalampos & Kalamara Eleni, 2022. "Assessing the effectiveness of tax administration in macroeconomic stability: evidence from 26 European Countries," Economic Change and Restructuring, Springer, vol. 55(4), pages 2237-2261, November.
    7. Peter Fernandes Wanke & Rebecca de Mattos, 2014. "Capacity Issues and Efficiency Drivers in Brazilian Bulk Terminals," Brazilian Business Review, Fucape Business School, vol. 11(5), pages 72-98, October.
    8. Mohammad Nourani & Qian Long Kweh & Evelyn Shyamala Devadason & V.G.R. Chandran, 2020. "A decomposition analysis of managerial efficiency for the insurance companies: A data envelopment analysis approach," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(6), pages 885-901, September.
    9. Matthias Klumpp & Dominic Loske, 2021. "Sustainability and Resilience Revisited: Impact of Information Technology Disruptions on Empirical Retail Logistics Efficiency," Sustainability, MDPI, vol. 13(10), pages 1-20, May.
    10. George Halkos & Roman Matousek & Nickolaos Tzeremes, 2016. "Pre-evaluating technical efficiency gains from possible mergers and acquisitions: evidence from Japanese regional banks," Review of Quantitative Finance and Accounting, Springer, vol. 46(1), pages 47-77, January.
    11. Duk Hee Lee & Il Won Seo & Ho Chull Choe & Hee Dae Kim, 2012. "Collaboration network patterns and research performance: the case of Korean public research institutions," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(3), pages 925-942, June.
    12. A. M. Aldanondo & V. L. Casasnovas, 2015. "Input aggregation bias in technical efficiency with multiple criteria analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 22(6), pages 430-435, April.
    13. Khushalani, Jaya & Ozcan, Yasar A., 2017. "Are hospitals producing quality care efficiently? An analysis using Dynamic Network Data Envelopment Analysis (DEA)," Socio-Economic Planning Sciences, Elsevier, vol. 60(C), pages 15-23.
    14. Mehdiloozad, Mahmood & Zhu, Joe & Sahoo, Biresh K., 2018. "Identification of congestion in data envelopment analysis under the occurrence of multiple projections: A reliable method capable of dealing with negative data," European Journal of Operational Research, Elsevier, vol. 265(2), pages 644-654.
    15. Subhash C. Ray & Lei Chen, 2015. "Data Envelopment Analysis for Performance Evaluation: A Child’s Guide," Springer Books, in: Subhash C. Ray & Subal C. Kumbhakar & Pami Dua (ed.), Benchmarking for Performance Evaluation, edition 127, chapter 0, pages 75-116, Springer.
    16. Amir B. Ferreira Neto & Joshua C. Hall, 2019. "Economies of scale and governance of library systems: evidence from West Virginia," Economics of Governance, Springer, vol. 20(3), pages 237-253, September.
    17. Halkos, George E. & Tzeremes, Nickolaos G., 2011. "Oil consumption and economic efficiency: A comparative analysis of advanced, developing and emerging economies," Ecological Economics, Elsevier, vol. 70(7), pages 1354-1362, May.
    18. Md Aslam Mia & V. G. R. Chandran, 2016. "Measuring Financial and Social Outreach Productivity of Microfinance Institutions in Bangladesh," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 127(2), pages 505-527, June.
    19. Simon, Jose & Simon, Clara & Arias, Alicia, 2011. "Changes in productivity of Spanish university libraries," Omega, Elsevier, vol. 39(5), pages 578-588, October.
    20. Danijela Tuljak-Suban & Patricija Bajec, 2022. "A Hybrid DEA Approach for the Upgrade of an Existing Bike-Sharing System with Electric Bikes," Energies, MDPI, vol. 15(21), pages 1-23, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:18:y:2021:i:23:p:12452-:d:688655. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.