IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i8p1144-d1373474.html
   My bibliography  Save this article

Fuzzy-Based Road Accident Risk Assessment

Author

Listed:
  • Péter Mogyorósi

    (Doctoral School of Applied Informatics and Applied Mathematics, Óbuda University, H-1034 Budapest, Hungary)

  • Sándor Szénási

    (John von Neumann Faculty of Informatics, Óbuda University, H-1034 Budapest, Hungary
    Current address: Faculty of Economics and Informatics, J. Selye University, P.O. Box 54, Komarno, Slovakia.)

  • Edit Laufer

    (Bánki Donát Faculty of Mechanical and Safety Engineering, Óbuda University, H-1034 Budapest, Hungary)

Abstract

It is necessary to extensively investigate the causes of road accidents with the utmost precision to harness future technological advancements, such as autonomous driving and intelligent accident prevention systems. Nevertheless, since most accidents are attributed to simple human errors, unraveling the complex root-cause factors poses a considerable challenge. This is where fuzzy logic can offer a potential solution: it is essential to understand even seemingly straightforward errors, such as speeding, to identify external factors that could play a pivotal role in future accident prevention. A more in-depth examination and comprehension of elements like road curvature, slope, and their correlation with accidents are necessary. Additionally, it is crucial to explore how the frequency of accidents on specific road segments varies under diverse weather conditions. This article analyzes which curves can be considered more dangerous and the factors that render them risky. The fuzzy model presented in this article is primarily capable of estimating the risk of a given road segment based on its curvature characteristics. The model results presented in the article indicate that sections of the road can become more risky due to multiple curves and curves with a radius of less than 80 m. The model assesses risk based on the physical characteristics of road segments, primarily the curvature radius, while, typically, other road risk assessment models rely on traffic volume and accident counts.

Suggested Citation

  • Péter Mogyorósi & Sándor Szénási & Edit Laufer, 2024. "Fuzzy-Based Road Accident Risk Assessment," Mathematics, MDPI, vol. 12(8), pages 1-18, April.
  • Handle: RePEc:gam:jmathe:v:12:y:2024:i:8:p:1144-:d:1373474
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/8/1144/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/12/8/1144/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yaolong Liu & Xiaoli Huang & Jin Duan & Huaming Zhang, 2017. "The assessment of traffic accident risk based on grey relational analysis and fuzzy comprehensive evaluation method," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 88(3), pages 1409-1422, September.
    Full references (including those not matched with items on IDEAS)

    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. Wei Wang & Chenhong Xia & Chaofeng Liu & Ziyi Wang, 2020. "Study of double combination evaluation of urban comprehensive disaster risk," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 104(2), pages 1181-1209, November.
    2. Teng Wang & Jingjing Yan & Jinlong Ma & Fei Li & Chaoyang Liu & Ying Cai & Si Chen & Jingjing Zeng & Yu Qi, 2018. "A Fuzzy Comprehensive Assessment and Hierarchical Management System for Urban Lake Health: A Case Study on the Lakes in Wuhan City, Hubei Province, China," IJERPH, MDPI, vol. 15(12), pages 1-16, November.
    3. Zhuguang Lan & Ming Huang, 2018. "Safety assessment for seawall based on constrained maximum entropy projection pursuit model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 91(3), pages 1165-1178, April.
    4. Bo Shao & Zhigen Hu & Dawei Liu, 2019. "Using Improved Principal Component Analysis to Explore Construction Accident Situations from the Multi-Dimensional Perspective: A Chinese Study," IJERPH, MDPI, vol. 16(18), pages 1-18, September.
    5. Fei Li & Minsi Xiao & Jingdong Zhang & Chaoyang Liu & Zhenzhen Qiu & Ying Cai, 2018. "Spatial Distribution, Chemical Fraction and Fuzzy Comprehensive Risk Assessment of Heavy Metals in Surface Sediments from the Honghu Lake, China," IJERPH, MDPI, vol. 15(2), pages 1-17, January.
    6. Yucui Ning & Xu Wang & Yanna Yang & Xu Cao & Yulong Wu & Detang Zou & Dongxing Zhou, 2022. "Studying the Effect of Straw Returning on the Interspecific Symbiosis of Soil Microbes Based on Carbon Source Utilization," Agriculture, MDPI, vol. 12(7), pages 1-16, July.
    7. Zhiqiang Liu & Hejun Liang & Dongping Pu & Fei Xie & E Zhang & Qi Zhou, 2020. "How Does the Control of Grain Purchase Price Affect the Sustainability of the National Grain Industry? One Empirical Study from China," Sustainability, MDPI, vol. 12(5), pages 1-21, March.
    8. Qingwei Xu & Kaili Xu & Fang Zhou, 2020. "Safety Assessment of Casting Workshop by Cloud Model and Cause and Effect–LOPA to Protect Employee Health," IJERPH, MDPI, vol. 17(7), pages 1-18, April.

    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:jmathe:v:12:y:2024:i:8:p:1144-:d:1373474. 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.