FOREX Press I. J. of Electrical & Electronics Research
Support Open Access
  • Home/
  • IJEER-120116

Research Article |

A Route Planning Method using Neural Network and HIL Technology Applied for Cargo Ships

Author(s): Huu-Khanh Doan, Anh-Tuan Dinh and Duc-Tuan Hoang

Published In : International Journal of Electrical and Electronics Research (IJEER)        Volume 12, Issue 1

Publisher : FOREX Publication

Published : 05 February 2024

e-ISSN : 2347-470X

Page(s) : 111-118

DOI: https://doi.org/10.37391/IJEER.120116

Abstract

This paper presents the development of a method to find optimal routes for cargo ships with three criteria: fuel consumption, safety, and required time. Unlike most previous works, operational data are used for the studies. In this study, we use data collected from a hardware-in-loop (HIL) simulator, with the plant model being a 3D dynamic model of a bulk carrier designed and programmed from 6 degrees of freedom (6-DOF) equations that can interact with forces and moments from the environmental disturbances. The dataset generated from the HIL simulator with various operating scenarios is used to train an artificial neural network (ANN) model. This predictive model then combines the A* algorithm, weather forecast data, ship parameters, and waypoint coordinates to find the optimal routes for ships before each voyage. The test results show that the proposed method works reliably, helping to improve fuel efficiency and enhance the safety of the ships.

Keywords: route planning, A* algorithm, HIL simulator, artificial neural network .




Huu-Khanh Doan*, Faculty of Electrical – Electronics Engineering, Vietnam Maritime University, Hai Phong, Vietnam; Email: khanhdh.ddt@vimaru.edu.vn

Anh-Tuan Dinh, Faculty of Electrical – Electronics Engineering, Vietnam Maritime University, Hai Phong, Vietnam

Duc-Tuan Hoang, Faculty of Electrical – Electronics Engineering, Vietnam Maritime University, Hai Phong, Vietnam

    [1] C. de Wit, "Proposal for Low Cost Ocean Weather Routeing," J. Navig., vol. 43, no. 3, pp. 428–439, 1990, doi: 10.1017/S0373463300014053. [CrossRef]
    [2] A. Anel, "optimum track ship routing NAVAL POSTGRADUATE," 2005.
    [3] J. Bekker and J. Schmid, "Planning the safe transit of a ship through a mapped minefield," ORiON, vol. 22, no. 1, 2006, doi: 10.5784/22-1-30. [CrossRef]
    [4] C. P. Padhy, D. Sen, and P. K. Bhaskaran, "Application of wave model for weather routing of ships in the North Indian Ocean," Nat. Hazards, vol. 44, no. 3, pp. 373–385, 2008, doi: 10.1007/s11069-007-9126-1. [CrossRef]
    [5] D. Sen and C. P. Padhy, "An approach for development of a ship routing algorithm for application in the North Indian Ocean region," Appl. Ocean Res., vol. 50, pp. 173–191, 2015, doi: 10.1016/j.apor.2015.01.019. [CrossRef]
    [6] C. Diakaki et al., "A decision support system for the development of voyage and maintenance plans for ships," Int. J. Decis. Support Syst., vol. 1, no. 1, p. 42, 2015, doi: 10.1504/ijdss.2015.067274. [CrossRef]
    [7] M. Bentin, D. Zastrau, M. Schlaak, D. Freye, R. Elsner, and S. Kotzur, "A New Routing Optimization Tool-influence of Wind and Waves on Fuel Consumption of Ships with and without Wind Assisted Ship Propulsion Systems," Transp. Res. Procedia, vol. 14, pp. 153–162, 2016, doi: 10.1016/j.trpro.2016.05.051. [CrossRef]
    [8] R. Vettor and C. Guedes Soares, "Development of a ship weather routing system," Ocean Eng., vol. 123, pp. 1–14, 2016, doi: 10.1016/j.oceaneng.2016.06.035. [CrossRef]
    [9] R. Zaccone, M. Figari, M. Altosole, and E. Ottaviani, "Fuel saving-oriented 3D dynamic programming for weather routing applications," Proc. 3rd Int. Conf. Marit. Technol. Eng. MARTECH 2016, vol. 1, no. June 2016, pp. 183–192, 2016, doi: 10.1201/b21890-26. [CrossRef]
    [10] R. Zaccone, M. Figari, and M. Martelli, "An optimization tool for ship route planning in real weather scenarios," Proc. Int. Offshore Polar Eng. Conf., vol. 2018-June, no. February 2019, pp. 738–744, 2018.
    [11] S. Pennino, S. Gaglione, A. Innac, V. Piscopo, and A. Scamardella, "Development of a new ship adaptive weather routing model based on seakeeping analysis and optimization," J. Mar. Sci. Eng., vol. 8, no. 4, 2020, doi: 10.3390/JMSE8040270. [CrossRef]
    [12] W. Zhao, Y. Wang, Z. Zhang, and H. Wang, "Multicriteria ship route planning method based on improved particle swarm optimization–genetic algorithm," J. Mar. Sci. Eng., vol. 9, no. 4, 2021, doi: 10.3390/jmse9040357. [CrossRef]
    [13] J. Yang, L. Wu, and J. Zheng, "Multi-Objective Weather Routing Algorithm for Ships: The Perspective of Shipping Company's Navigation Strategy," J. Mar. Sci. Eng., vol. 10, no. 9, 2022, doi: 10.3390/jmse10091212. [CrossRef]
    [14] Y. W. Shin et al., "Near-optimal weather routing by using improved A* algorithm," Appl. Sci., vol. 10, no. 17, pp. 1–23, 2020, doi: 10.3390/app10176010.
    [15] X. Jin, J. Xiong, D. Gu, C. Yi, and Y. Jiang, "Research on Ship Route Planning Method Based on Neural Network Wave Data Forecast," IOP Conf. Ser. Earth Environ. Sci., vol. 638, no. 1, 2021, doi: 10.1088/1755-1315/638/1/012033. [CrossRef]
    [16] M. Grifoll, C. Borén, and M. Castells-Sanabra, "A comprehensive ship weather routing system using CMEMS products and A* algorithm," Ocean Eng., vol. 255, no. May, 2022, doi: 10.1016/j.oceaneng.2022.111427. [CrossRef]
    [17] Y. Li, J. Cui, X. Zhang, and X. Yang, "A Ship Route Planning Method under the Sailing Time Constraint," J. Mar. Sci. Eng., vol. 11, no. 6, p. 1242, 2023, doi: 10.3390/jmse11061242.
    [18] T.I. Fossen, Marine Control Systems, vol. 3, no. April. 2002.
    [19] K. D. Huu, T. D. Anh, and T. H. Duc, "A 3D dynamic model applied for cargo ships to study ship motion control," [CrossRef]
    [20] K. D. Huu, T. D. Anh, and T. H. Duc, "A Real-Time Model Using Interpolation Method and Semi-Empirical Formulas to Estimate Fuel Consumption for Cargo Ships," Proc. - 2023 Int. Conf. Ind. Eng. Appl. Manuf. ICIEAM 2023, pp. 932–937, 2023, doi: 10.1109/ICIEAM57311.2023.10139155. [CrossRef]
    [21] W. M. Organization, Guide to Wave Analysis and Forecasting, vol. 1998, no. 702. 1998.
    [22] I. M. Zidane and K. Ibrahim, "Wavefront and a-star algorithms for mobile robot path planning," Adv. Intell. Syst. Comput., vol. 639, no. May, pp. 69–80, 2018, doi: 10.1007/978-3-319-64861-3_7.
    [23] K. D. Huu, T. D. Anh, and T. H. Duc, "A Neural Network-Based Model to Predict Fuel Consumption and Sailing Time for Cargo Ships," Proc. - 2023 Int. Russ. Autom. Conf. RusAutoCon 2023, pp. 386–391, 2023, doi: 10.1109/RusAutoCon58002.2023.10272784. [CrossRef]
    [24] Y. A. Ahmed and K. Hasegawa, "Fuzzy Reasoned Waypoint Controller for Automatic Ship Guidance," in IFAC-PapersOnLine, Elsevier B.V., 2016, pp. 604–609. doi: 10.1016/j.ifacol.2016.10.501. [CrossRef]
    [25] L. T. Le, G. Lee, K. S. Park, and H. Kim, "Neural network-based fuel consumption estimation for container ships in Korea," Marit. Policy Manag., vol. 47, no. 5, pp. 615–632, 2020, doi: 10.1080/03088839.2020.1729437. [CrossRef]

Huu-Khanh Doan, Anh-Tuan Dinh and Duc-Tuan Hoang (2024), A Route Planning Method using Neural Network and HIL Technology Applied for Cargo Ships. IJEER 12(1), 111-118. DOI: 10.37391/IJEER.120116.