IDEAS home Printed from https://ideas.repec.org/r/eee/reensy/v196y2020ics0951832018308160.html
   My bibliography  Save this item

Towards supervisory risk control of autonomous ships

Citations

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


Cited by:

  1. Yuechao Zhao & Haobo Zhao & Zeya Miao & Dihao Ai & Qifei Wang, 2023. "A Numerical Study on the Smoke Dispersion and Temperature Distribution of a Ship Engine Room Fire Based on OpenFOAM," Sustainability, MDPI, vol. 15(20), pages 1-23, October.
  2. Abaei, Mohammad Mahdi & Hekkenberg, Robert & BahooToroody, Ahmad, 2021. "A multinomial process tree for reliability assessment of machinery in autonomous ships," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
  3. Victor Bolbot & Gerasimos Theotokatos & LA Wennersberg & Jerome Faivre & Dracos Vassalos & Evangelos Boulougouris & Ørnulf Jan Rødseth & Pål Andersen & Ann-Sofie Pauwelyn & Antoon Van Coillie, 2023. "A novel risk assessment process: Application to an autonomous inland waterways ship," Journal of Risk and Reliability, , vol. 237(2), pages 436-458, April.
  4. Fonseca, Tiago & Lagdami, Khanssa & Schröder-Hinrichs, Jens-Uwe, 2021. "Assessing innovation in transport: An application of the Technology Adoption (TechAdo) model to Maritime Autonomous Surface Ships (MASS)," Transport Policy, Elsevier, vol. 114(C), pages 182-195.
  5. Yu, Qing & Liu, Kezhong & Yang, Zhisen & Wang, Hongbo & Yang, Zaili, 2021. "Geometrical risk evaluation of the collisions between ships and offshore installations using rule-based Bayesian reasoning," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
  6. Wenjun Zhang & Yingjun Zhang & Weiliang Qiao, 2022. "Risk Scenario Evaluation for Intelligent Ships by Mapping Hierarchical Holographic Modeling into Risk Filtering, Ranking and Management," Sustainability, MDPI, vol. 14(4), pages 1-18, February.
  7. Li, Xue & Oh, Poong & Zhou, Yusheng & Yuen, Kum Fai, 2023. "Operational risk identification of maritime surface autonomous ship: A network analysis approach," Transport Policy, Elsevier, vol. 130(C), pages 1-14.
  8. Murray, Brian & Perera, Lokukaluge Prasad, 2021. "An AIS-based deep learning framework for regional ship behavior prediction," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
  9. Zhang, Hengqi & Geng, Hua & Zeng, Huarong & Jiang, Li, 2023. "Dynamic risk evaluation and control of electrical personal accidents," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
  10. Cheng, Tingting & Utne, Ingrid Bouwer & Wu, Bing & Wu, Qing, 2023. "A novel system-theoretic approach for human-system collaboration safety: Case studies on two degrees of autonomy for autonomous ships," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
  11. 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).
  12. Ismail Kurt & Murat Aymelek, 2022. "Operational and economic advantages of autonomous ships and their perceived impacts on port operations," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 24(2), pages 302-326, June.
  13. de Vos, Jiri & Hekkenberg, Robert G. & Valdez Banda, Osiris A., 2021. "The Impact of Autonomous Ships on Safety at Sea – A Statistical Analysis," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
  14. Abaei, Mohammad Mahdi & Hekkenberg, Robert & BahooToroody, Ahmad & Banda, Osiris Valdez & van Gelder, Pieter, 2022. "A probabilistic model to evaluate the resilience of unattended machinery plants in autonomous ships," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
  15. Xue Li & Kum Fai Yuen, 2022. "Autonomous ships: A study of critical success factors," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 24(2), pages 228-254, June.
  16. Enna Hirata & Annette Skovsted Hansen, 2024. "Identifying Key Issues in Integration of Autonomous Ships in Container Ports: A Machine-Learning-Based Systematic Literature Review," Logistics, MDPI, vol. 8(1), pages 1-15, February.
  17. BahooToroody, Ahmad & Abaei, Mohammad Mahdi & Banda, Osiris Valdez & Kujala, Pentti & De Carlo, Filippo & Abbassi, Rouzbeh, 2022. "Prognostic health management of repairable ship systems through different autonomy degree; From current condition to fully autonomous ship," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
  18. Fan, Cunlong & Montewka, Jakub & Zhang, Di, 2022. "A risk comparison framework for autonomous ships navigation," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
  19. Yu, Qing & Teixeira, Ângelo Palos & Liu, Kezhong & Rong, Hao & Guedes Soares, Carlos, 2021. "An integrated dynamic ship risk model based on Bayesian Networks and Evidential Reasoning," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
  20. Johansen, Thomas & Blindheim, Simon & Torben, Tobias Rye & Utne, Ingrid Bouwer & Johansen, Tor Arne & Sørensen, Asgeir J., 2023. "Development and testing of a risk-based control system for autonomous ships," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
  21. Wang, Yang & Chen, Peng & Wu, Bing & Wan, Chengpeng & Yang, Zaili, 2022. "A trustable architecture over blockchain to facilitate maritime administration for MASS systems," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
  22. Shiokari, Megumi & Itoh, Hiroko & Yuzui, Tomohiro & Ishimura, Eiko & Miyake, Rina & Kudo, Junichi & Kawashima, Sonoko, 2024. "Structure model-based hazard identification method for autonomous ships," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
  23. Mazurek, J. & Lu, L. & Krata, P. & Montewka, J. & Krata, H. & Kujala, P., 2022. "An updated method identifying collision-prone locations for ships. A case study for oil tankers navigating in the Gulf of Finland," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
  24. 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.
  25. Fan, Cunlong & Montewka, Jakub & Bolbot, Victor & Zhang, Yang & Qiu, Yuhui & Hu, Shenping, 2024. "Towards an analysis framework for operational risk coupling mode: A case from MASS navigating in restricted waters," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
  26. Wenjun Zhang & Xiangkun Meng & Xue Yang & Hongguang Lyu & Xiang-Yu Zhou & Qingwu Wang, 2022. "A Practical Risk-Based Model for Early Warning of Seafarer Errors Using Integrated Bayesian Network and SPAR-H," IJERPH, MDPI, vol. 19(16), pages 1-14, August.
  27. Gil, Mateusz, 2021. "A concept of critical safety area applicable for an obstacle-avoidance process for manned and autonomous ships," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
  28. 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).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.