IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v243y2024ics0951832023007305.html

A Bayesian network-based model for risk modeling and scenario deduction of collision accidents of inland intelligent ships

Author

Listed:
  • Zhang, Jinfeng
  • Jin, Mei
  • Wan, Chengpeng
  • Dong, Zhijie
  • Wu, Xiaohong

Abstract

Safety is an important premise and foundation for the operation of intelligent ships. This paper introduces a novel scenario analysis framework that employs disaster system theory to produce more comprehensive results for identifying scenario elements and calculating collision risks for inland intelligent ships. The framework is utilized to investigate the collision accident risk evolution mechanism. This process is incorporated into Bayesian Network (BN) modeling for ship collisions on inland rivers. By comparing the change in occurrence probability and consequence severity of risk factors for inland ship collision accidents with and without selected intelligent technologies, the collision risk of intelligent ships is quantified. The results indicate that the application of intelligent technologies, such as ship speed optimization and situational awareness, can reduce the occurrence probability of collision accidents and mitigate the severity of their consequences. Moreover, it has been discovered that such intelligent technologies have a greater impact on accidents with severe consequences than those with minor consequences. This research provides a framework for the preliminary safety evaluation of inland intelligent ships. It is of great significance to accelerate the improvement of navigational risk prevention and response-ability of inland intelligent ships in the future.

Suggested Citation

  • Zhang, Jinfeng & Jin, Mei & Wan, Chengpeng & Dong, Zhijie & Wu, Xiaohong, 2024. "A Bayesian network-based model for risk modeling and scenario deduction of collision accidents of inland intelligent ships," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    • Handle: RePEc:eee:reensy:v:243:y:2024:i:c:s0951832023007305
    DOI: 10.1016/j.ress.2023.109816
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832023007305
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2023.109816?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Shiqi Fan & Zaili Yang & Eduardo Blanco-Davis & Jinfen Zhang & Xinping Yan, 2020. "Analysis of maritime transport accidents using Bayesian networks," Journal of Risk and Reliability, , vol. 234(3), pages 439-454, June.
    2. Chang, Chia-Hsun & Kontovas, Christos & Yu, Qing & Yang, Zaili, 2021. "Risk assessment of the operations of maritime autonomous surface ships," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    3. Wang, Huanxin & Liu, Zhengjiang & Wang, Xinjian & Graham, Tony & Wang, Jin, 2021. "An analysis of factors affecting the severity of marine accidents," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    4. Yang, Zaili & Yang, Zhisen & Smith, John & Robert, Bostock Adam Peter, 2021. "Risk analysis of bicycle accidents: A Bayesian approach," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    5. Chen, Tianyi & Wong, Yiik Diew & Shi, Xiupeng & Wang, Xueqin, 2022. "Optimized structure learning of Bayesian Network for investigating causation of vehicles’ on-road crashes," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    6. Zijun Qie & Lili Rong, 2017. "An integrated relative risk assessment model for urban disaster loss in view of disaster system theory," 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(1), pages 165-190, August.
    7. Elidolu, Gizem & Sezer, Sukru Ilke & Akyuz, Emre & Arslan, Ozcan & Arslanoglu, Yasin, 2023. "Operational risk assessment of ballasting and de-ballasting on-board tanker ship under FMECA extended Evidential Reasoning (ER) and Rule-based Bayesian Network (RBN) approach," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    8. Utne, Ingrid Bouwer & Rokseth, Børge & Sørensen, Asgeir J. & Vinnem, Jan Erik, 2020. "Towards supervisory risk control of autonomous ships," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    9. Liu, Jin & Zhai, Changhai & Yu, Peng, 2022. "A Probabilistic Framework to Evaluate Seismic Resilience of Hospital Buildings Using Bayesian Networks," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    10. Asadayoobi, N. & Taghipour, S. & Jaber, M.Y., 2022. "Predicting human reliability based on probabilistic mission completion time using Bayesian Network," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    11. Wróbel, Krzysztof & Montewka, Jakub & Kujala, Pentti, 2017. "Towards the assessment of potential impact of unmanned vessels on maritime transportation safety," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 155-169.
    12. Fan, Shiqi & Blanco-Davis, Eduardo & Yang, Zaili & Zhang, Jinfen & Yan, Xinping, 2020. "Incorporation of human factors into maritime accident analysis using a data-driven Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    13. Garg, Vipul & Vinod, Gopika & Prasad, Mahendra & Chattopadhyay, J. & Smith, Curtis & Kant, Vivek, 2023. "Human reliability analysis studies from simulator experiments using Bayesian inference," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    14. Yildiz, Serdar & Uğurlu, Özkan & Wang, Jin & Loughney, Sean, 2021. "Application of the HFACS-PV approach for identification of human and organizational factors (HOFs) influencing marine accidents," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    15. Fu, Shanshan & Yu, Yuerong & Chen, Jihong & Xi, Yongtao & Zhang, Mingyang, 2022. "A framework for quantitative analysis of the causation of grounding accidents in arctic shipping," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    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. She, Jianjun & Guo, Zihao & Li, Zhijian & Liang, Shuwei & Zhou, Yilun, 2024. "Research on scenario deduction and emergency decision-making evaluation for construction safety accidents," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
    2. Wang, Yuhong & Li, Pengchang & Hong, Cheng & Yang, Zaili, 2025. "Causation analysis of ship collisions using a TM-FRAM model," Reliability Engineering and System Safety, Elsevier, vol. 260(C).
    3. Li, Huanhuan & Ren, Xujie & Yang, Zaili, 2023. "Data-driven Bayesian network for risk analysis of global maritime accidents," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    4. Xiaoyuan Zhao & Haiwen Yuan & Qing Yu, 2021. "Autonomous Vessels in the Yangtze River: A Study on the Maritime Accidents Using Data-Driven Bayesian Networks," Sustainability, MDPI, vol. 13(17), pages 1-17, September.
    5. Fan, Shiqi & Yang, Zaili, 2024. "Accident data-driven human fatigue analysis in maritime transport using machine learning," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    6. Cao, Yuhao & Iulia, Manole & Majumdar, Arnab & Feng, Yinwei & Xin, Xuri & Wang, Xinjian & Wang, Huanxin & Yang, Zaili, 2025. "Investigation of the risk influential factors of maritime accidents: A novel topology and robustness analytical framework," Reliability Engineering and System Safety, Elsevier, vol. 254(PB).
    7. Zhang, Hengqi & Geng, Hua, 2023. "A methodology to identify and assess high-risk causes for electrical personal accidents based on directed weighted CN," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    8. Obeng, Francis & Domeh, Daniel & Khan, Faisal & Bose, Neil & Sanli, Elizabeth, 2024. "An operational risk management approach for small fishing vessel," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
    9. Liu, Zhichen & Li, Ying & Zhang, Zhaoyi & Yu, Wenbo, 2022. "A new evacuation accessibility analysis approach based on spatial information," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    10. Cheng, Tingting & Veitch, Erik A. & Utne, Ingrid Bouwer & Ramos, Marilia A. & Mosleh, Ali & Alsos, Ole Andreas & Wu, Bing, 2024. "Analysis of human errors in human-autonomy collaboration in autonomous ships operations through shore control experimental data," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
    11. Wang, Xinjian & Liu, Zhengjiang & Loughney, Sean & Yang, Zaili & Wang, Yanfu & Wang, Jin, 2022. "Numerical analysis and staircase layout optimisation for a Ro-Ro passenger ship during emergency evacuation," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    12. Lan, He & Ma, Xiaoxue & Qiao, Weiliang & Ma, Laihao, 2022. "On the causation of seafarers’ unsafe acts using grounded theory and association rule," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    13. Wang, Nanxi & Yuen, Kum Fai & Li, Duowei & Wong, Yiik Diew & Tan, Kim Hock, 2026. "A bayesian network approach to ship safety assessment: integrating machine learning and expert opinions," Reliability Engineering and System Safety, Elsevier, vol. 266(PA).
    14. Liu, Guanyi & Liu, Shifeng & Li, Xuewei & Li, Xueyan & Gong, Daqing, 2025. "Multiscenario deduction analysis for railway emergencies using knowledge metatheory and dynamic Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 255(C).
    15. Guo, Yunlong & Jin, Yongxing & Hu, Shenping & Yang, Zaili & Xi, Yongtao & Han, Bing, 2023. "Risk evolution analysis of ship pilotage operation by an integrated model of FRAM and DBN," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    16. Fan, Cunlong & Montewka, Jakub & Zhang, Di, 2022. "A risk comparison framework for autonomous ships navigation," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    17. Fu, Shanshan & Yu, Yuerong & Chen, Jihong & Xi, Yongtao & Zhang, Mingyang, 2022. "A framework for quantitative analysis of the causation of grounding accidents in arctic shipping," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    18. Abreu, Danilo T.M.P. & Maturana, Marcos C. & Droguett, Enrique Lopez & Martins, Marcelo R., 2022. "Human reliability analysis of conventional maritime pilotage operations supported by a prospective model," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    19. Zhang, Mingyang & Taimuri, Ghalib & Zhang, Jinfen & Zhang, Di & Yan, Xinping & Kujala, Pentti & Hirdaris, Spyros, 2025. "Systems driven intelligent decision support methods for ship collision and grounding prevention: Present status, possible solutions, and challenges," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
    20. Wang, Hong & Chen, Ning & Wu, Bing & Guedes Soares, C., 2024. "Human and organizational factors analysis of collision accidents between merchant ships and fishing vessels based on HFACS-BN model," Reliability Engineering and System Safety, Elsevier, vol. 249(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:eee:reensy:v:243:y:2024:i:c:s0951832023007305. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    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.