IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i10p1546-d1395318.html
   My bibliography  Save this article

A Dynamic Programming Approach to the Collision Avoidance of Autonomous Ships

Author

Listed:
  • Raphael Zaccone

    (Dipartimento di Ingegneria Navale, Elettrica, Elettronica e delle Telecompunicazioni (DITEN), Scuola Politecnica, Università degli Studi di Genova, Via Montallegro 1, 16145 Genova, Italy)

Abstract

The advancement of autonomous capabilities in maritime navigation has gained significant attention, with a trajectory moving from decision support systems to full autonomy. This push towards autonomy has led to extensive research focusing on collision avoidance, a critical aspect of safe navigation. Among the various possible approaches, dynamic programming is a promising tool for optimizing collision avoidance maneuvers. This paper presents a DP formulation for the collision avoidance of autonomous vessels. We set up the problem framework, formulate it as a multi-stage decision process, define cost functions and constraints focusing on the actual requirements a marine maneuver must comply with, and propose a solution algorithm leveraging parallel computing. Additionally, we present a greedy approximation to reduce algorithm complexity. We put the proposed algorithms to the test in realistic navigation scenarios and also develop an extensive test on a large set of randomly generated scenarios, comparing them with the RRT* algorithm using performance metrics proposed in the literature. The results show the potential benefits of an autonomous navigation or decision support framework.

Suggested Citation

  • Raphael Zaccone, 2024. "A Dynamic Programming Approach to the Collision Avoidance of Autonomous Ships," Mathematics, MDPI, vol. 12(10), pages 1-22, May.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:10:p:1546-:d:1395318
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/10/1546/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/12/10/1546/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Richard Bellman, 1954. "On some applications of the theory of dynamic programming to logistics," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 1(2), pages 141-153, June.
    2. Richard Bellman, 1954. "Some Applications of the Theory of Dynamic Programming---A Review," Operations Research, INFORMS, vol. 2(3), pages 275-288, August.
    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. Xiaoyue Li & John M. Mulvey, 2023. "Optimal Portfolio Execution in a Regime-switching Market with Non-linear Impact Costs: Combining Dynamic Program and Neural Network," Papers 2306.08809, arXiv.org.
    2. Mahmoud Mahfouz & Angelos Filos & Cyrine Chtourou & Joshua Lockhart & Samuel Assefa & Manuela Veloso & Danilo Mandic & Tucker Balch, 2019. "On the Importance of Opponent Modeling in Auction Markets," Papers 1911.12816, arXiv.org.
    3. Dawei Chen & Fangxu Mo & Ye Chen & Jun Zhang & Xinyu You, 2022. "Optimization of Ramp Locations along Freeways: A Dynamic Programming Approach," Sustainability, MDPI, vol. 14(15), pages 1-13, August.
    4. Harrold, Daniel J.B. & Cao, Jun & Fan, Zhong, 2022. "Data-driven battery operation for energy arbitrage using rainbow deep reinforcement learning," Energy, Elsevier, vol. 238(PC).
    5. Vanvuchelen, Nathalie & De Boeck, Kim & Boute, Robert N., 2024. "Cluster-based lateral transshipments for the Zambian health supply chain," European Journal of Operational Research, Elsevier, vol. 313(1), pages 373-386.
    6. Wadi Khalid Anuar & Lai Soon Lee & Hsin-Vonn Seow & Stefan Pickl, 2021. "A Multi-Depot Vehicle Routing Problem with Stochastic Road Capacity and Reduced Two-Stage Stochastic Integer Linear Programming Models for Rollout Algorithm," Mathematics, MDPI, vol. 9(13), pages 1-44, July.
    7. Matthias Breuer & David Windisch, 2019. "Investment Dynamics and Earnings‐Return Properties: A Structural Approach," Journal of Accounting Research, Wiley Blackwell, vol. 57(3), pages 639-674, June.
    8. Diefenbach, Heiko & Emde, Simon & Glock, Christoph H., 2020. "Loading tow trains ergonomically for just-in-time part supply," European Journal of Operational Research, Elsevier, vol. 284(1), pages 325-344.
    9. Michael J. Pennock & William B. Rouse & Diane L. Kollar, 2007. "Transforming the Acquisition Enterprise: A Framework for Analysis and a Case Study of Ship Acquisition," Systems Engineering, John Wiley & Sons, vol. 10(2), pages 99-117, June.
    10. Quetschlich, Mathias & Moetz, André & Otto, Boris, 2021. "Optimisation model for multi-item multi-echelon supply chains with nested multi-level products," European Journal of Operational Research, Elsevier, vol. 290(1), pages 144-158.
    11. Sasanka Adikari & Norou Diawara, 2024. "Utility in Time Description in Priority Best–Worst Discrete Choice Models: An Empirical Evaluation Using Flynn’s Data," Stats, MDPI, vol. 7(1), pages 1-18, February.
    12. Coit, David W. & Zio, Enrico, 2019. "The evolution of system reliability optimization," Reliability Engineering and System Safety, Elsevier, vol. 192(C).
    13. Peng, Hujun & Li, Jianxiang & Löwenstein, Lars & Hameyer, Kay, 2020. "A scalable, causal, adaptive energy management strategy based on optimal control theory for a fuel cell hybrid railway vehicle," Applied Energy, Elsevier, vol. 267(C).
    14. Vincent Huang & James Unwin, 2019. "Markov Chain Models of Refugee Migration Data," Papers 1903.08255, arXiv.org.
    15. Esmaeili Aliabadi, Danial & Chan, Katrina, 2022. "The emerging threat of artificial intelligence on competition in liberalized electricity markets: A deep Q-network approach," Applied Energy, Elsevier, vol. 325(C).
    16. Alex Sharp & Ryan Browne, 2021. "Functional data clustering by projection into latent generalized hyperbolic subspaces," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 15(3), pages 735-757, September.
    17. Thomas L. Magnanti, 2021. "Optimization: From Its Inception," Management Science, INFORMS, vol. 67(9), pages 5349-5363, September.
    18. G., Mauricio Contreras & Peña, Juan Pablo, 2019. "The quantum dark side of the optimal control theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 450-473.
    19. Yann Disser & John Fearnley & Martin Gairing & Oliver Göbel & Max Klimm & Daniel Schmand & Alexander Skopalik & Andreas Tönnis, 2020. "Hiring Secretaries over Time: The Benefit of Concurrent Employment," Mathematics of Operations Research, INFORMS, vol. 45(1), pages 323-352, February.
    20. Sean Williams & Michael Short & Tracey Crosbie & Maryam Shadman-Pajouh, 2020. "A Decentralized Informatics, Optimization, and Control Framework for Evolving Demand Response Services," Energies, MDPI, vol. 13(16), pages 1-30, August.

    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:10:p:1546-:d:1395318. 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.