Volume 21 Issue 5
Nov.  2021
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HE Yi-xiong, LIANG Yu, XIONG Yong, MOU Jun-min, LI Meng-xia, ZHANG Ke. Dynamic adaptive intelligent navigation method for multi-object situation in open water[J]. Journal of Traffic and Transportation Engineering, 2021, 21(5): 297-308. doi: 10.19818/j.cnki.1671-1637.2021.05.025
Citation: HE Yi-xiong, LIANG Yu, XIONG Yong, MOU Jun-min, LI Meng-xia, ZHANG Ke. Dynamic adaptive intelligent navigation method for multi-object situation in open water[J]. Journal of Traffic and Transportation Engineering, 2021, 21(5): 297-308. doi: 10.19818/j.cnki.1671-1637.2021.05.025
shu

Dynamic adaptive intelligent navigation method for multi-object situation in open water

doi: 10.19818/j.cnki.1671-1637.2021.05.025
  • 1.

    School of Navigation, Wuhan University of Technology, Wuhan 430063, Hubei, China

  • 2.

    Hubei Key Laboratory of Inland Shipping Technology, Wuhan University of Technology, Wuhan 430063, Hubei, China

Funds:

National Key Research and Development Program of China 2019YFB1600603

National Natural Science Foundation of China 52071249

Major Special Projects of Transportation Science and Technology of Jiangsu Province 2018Z01

More Information
  • Author Bio:

    HE Yi-xiong(1976-), male, associate professor, captain, PhD, heyixiong7@whut.edu.cn

  • Corresponding author: MOU Jun-min (1974-), male, professor, PhD, moujm@whut.edu.cn
  • Received Date: 2021-05-12
  • Publish Date: 2021-10-25
    Abstract
  • An intelligent navigation method of dynamic adaptive target ship collision avoidance action in open water was proposed considering the ship maneuvering characteristics, the requirements of International Regulations for Preventing Collisions at Sea 1972 and good seamanship. The digital twin traffic environment was constructed by classifying and modeling objects. An automatic navigation model was developed by combination of course control method, ship maneuvering motion and sailing resuming model, and ship's nonlinear maneuvering motion was deduced. The requirements of International Regulations for Preventing Collisions at Sea 1972 were quantitatively analyzed based on the automatic navigation model, and the dynamic collision avoidance mechanism was studied. The method to calculate applicable course was established. In the multi-target environment, the maneuvering discrimination method of target ship was proposed. The method to obtain the factors such as the course changing time, amplitude and sailing resuming time which constitute the autonomous navigation scheme under the constraint of rules was studied. Simulation results show that the intelligent navigation method can adapt to the residual error and random motion of the target ships based on the rolling calculations of the information update at the second-level. The proposed intelligent navigation method can accurately achieve the feasible course range and course change amplitude of 1°. The calculation step lengths of program and sailing resumption time are set to 1 and 10 s, respectively, and multiple static objects and six target ships maintaining the course and speed are established in this simulation environment. Own ship remains clear from all targets and sails autonomously to the destination after a series of maneuverings of 9° to starboard, sailing resuming, keeping course and speed, sailing resuming at 640, 1 053, 2 561 and 3 489 s, respectively. Target ships are set to perform uncoordinated collision avoidance actions at 300 s, and own ship remains clear from all targets and sails autonomously to the destination after a series of maneuverings of 9° to starboard, 12° to port, 17° to starboard, and sailing resuming at 980, 2 790, 3 622 and 5 470 s, respectively. Therefore, a ship in any initial states can automatically sail along a planned route to its destination. The proposed method is suitable for intelligent navigation in actual open sea areas with multiple and multiple dynamic and static objects. 5 tabs, 13 figs, 30 refs.

     

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    • References(30)
  • [1]
    LI Li-na, CHEN Guo-quan, LI Guo-ding, et al. Overview of research on intelligent collision avoidance decision-making method for ships[J]. Navigation, 2014(2): 42-49. (in Chinese) doi: 10.3969/j.issn.1009-8526.2014.02.013
    [2]
    SUN Wu. China Classification Society dispatching the rules of intelligent ship (2020)[J]. Ship Engineering, 2020, 42(3): 13-14. (in Chinese) http://www.cnki.com.cn/Article/CJFDTOTAL-CANB202003007.htm
    [3]
    BI Xiu-ying, LIU Xian-jie. Research on double collision avoidance mechanism of ships at sea[J]. The International Journal on Marine Navigation and Safety of Sea Transportation, 2015, 9(1): 13-16. doi: 10.12716/1001.09.01.01
    [4]
    XIONG Yong, HE Yi-xiong, HUANG Li-wen. Multi-ship collision avoiding control considering velocity obstacle[J]. Navigation of China, 2015, 38(3): 46-51. (in Chinese) doi: 10.3969/j.issn.1000-4653.2015.03.011
    [5]
    WU Bo, XIONG Yong, WEN Yuan-qiao. Automatic collision avoidance algorithm for unmanned surface vessel based on velocity obstacles[J]. Journal of Dalian Maritime University, 2014, 40(2): 13-16.
    [6]
    HUANG Ya-min, VAN GELDER P H A J M, WEN Yuan-qiao. Velocity obstacle algorithms for collision prevention at sea[J]. Ocean Engineering, 2018, 151: 308-321. doi: 10.1016/j.oceaneng.2018.01.001
    [7]
    LAZAROWSKA A. A new deterministic approach in a decision support system for ship's trajectory planning[J]. Expert Systems with Applications, 2016, 71: 469-478.
    [8]
    SANG Hong-qiang, YOU Yu-song, SUN Xiu-jun, et al. The hybrid path planning algorithm based on improved A* and artificial potential field for unmanned surface vehicle formations[J]. Ocean Engineering, 2021, 223: 108-123.
    [9]
    HAN Jun. The design of ship automatic navigation algorithm based on artificial potential field[J]. Ship Science and Technology, 2018, 40(6): 91-93. (in Chinese) http://www.cnki.com.cn/Article/CJFDTOTAL-JCKX201806032.htm
    [10]
    LAZAROWSKA A. Ship's trajectory planning for collision avoidance at sea based on ant colony optimisation[J]. The Journal of Navigation, 2015, 68: 291-307. doi: 10.1017/S0373463314000708
    [11]
    ZHANG Wen-shuan. Research on unmanned surface vehicle path planning based on improved potential field ant colony algorithm[D]. Dalian: Dalian Maritime University, 2020. (in Chinese)
    [12]
    JIANG Guan-chao, XIAO Ying-jie, XU Xiao-feng. Decision support of ship collision avoidance path planning based on improved ant colony algorithm[J]. Shanghai Energy Conservation, 2020(12): 1463-1468. (in Chinese) http://www.cnki.com.cn/Article/CJFDTOTAL-SHJL202012023.htm
    [13]
    ZHANG Guang-yu, WANG Hong-bo, ZHAO Wei, et al. Application of improved multi-objective ant colony optimization algorithm in ship weather routing[J]. Journal of Ocean University of China, 2021, 20(1): 45-55. doi: 10.1007/s11802-021-4436-6
    [14]
    PERERA L P, GUEDES SOARES C. Intelligent ocean navigation and fuzzy-Bayesian decision/action formulation[J]. IEEE Journal of Oceanic Engineering, 2012, 37(2): 204-219. doi: 10.1109/JOE.2012.2184949
    [15]
    TAM C K, BUCKNALL R. Cooperative path planning algorithm for marine surface vessels[J]. Ocean Engineering, 2013, 57: 25-33. doi: 10.1016/j.oceaneng.2012.09.003
    [16]
    XUE Yan-zhuo, CLELLAND D, LEE B S, et al. Automatic simulation of ship navigation[J]. Ocean Engineering, 2011, 38(17): 2290-2305.
    [17]
    HU Hui, HE Jing, HE Xiong-fei, et al. Emergency material scheduling optimization model and algorithms: a review[J]. Journal of Traffic and Transportation Engineering (English Edition), 2019, 6(5): 441-454. doi: 10.1016/j.jtte.2019.07.001
    [18]
    HE Yi-xiong, HUANG Li-wen, MOU Jun-min, et al. A scheme for automatic collision avoidance of a give way vessel in the crossing situation[J]. Journal of Harbin Engineering University, 2015, 36(8): 1024-1029. (in Chinese) http://www.cnki.com.cn/Article/CJFDTOTAL-HEBG201508004.htm
    [19]
    HE Yi-xiong, ZHANG Xiao-han, HU Wei-xuan, et al. The research of ship dynamic collision mechanism based on course control system[J]. Journal of Southwest Jiaotong University, 2020, 55(5): 988-993. (in Chinese) http://www.cnki.com.cn/Article/CJFDTOTAL-XNJT202005011.htm
    [20]
    MOU Jun-min, LI Meng-xia, HU Wei-xuan, et al. Mechanism of dynamic automatic collision avoidance and the optimal route in multi-ship encounter situations[J]. Journal of Marine Science and Technology, 2020, 26(1): 141-158.
    [21]
    HE Yi-xiong, JIN Yi, HUANG Li-wen, et al. Quantitative analysis of COLREG rules and seamanship for autonomous collision avoidance at open sea[J]. Ocean Engineering, 2017, 140: 281-291. doi: 10.1016/j.oceaneng.2017.05.029
    [22]
    HE Yi-xiong. The research of models and simulations about ship autonomous collision avoidance constrained by quantified resolution of rules[D]. Wuhan: Wuhan University of Technology, 2015. (in Chinese)
    [23]
    ZHOU Dan. Research on a novel dynamic and fuzzy ship domain[D]. Dalian: Dalian Maritime University, 2017. (in Chinese)
    [24]
    DAVIS P V, DOVE M J, STOCKEL C T. A computer simulation of marine traffic using domains and arenas[J]. Journal of Navigation, 1980, 33(2): 215-222. doi: 10.1017/S0373463300035220
    [25]
    QI Le, ZHENG Zhong-yi, LI Guo-ping. AIS-data-based ship domain of ships in sight of one another[J]. Journal of Dalian Maritime University, 2011, 37(1): 48-50. (in Chinese) doi: 10.3969/j.issn.1671-7031.2011.01.011
    [26]
    YU Xia, ZHENG Shu-tao, YU Yang, et al. Ship maneuvering performance prediction based on MMG model[J]. IOP Conference Series: Materials Science and Engineering, 2018, 452(4): 42-46.
    [27]
    CHEN Li-jia. Study on multiple objective decision making in collision avoidance at sea[D]. Wuhan: Wuhan University of Technology, 2011. (in Chinese)
    [28]
    WANG Hong-jian. The design of ship course controller controlled by proportional integral derivative[J]. Industrial Control Computer, 2016, 29(3): 86-87. (in Chinese) doi: 10.3969/j.issn.1001-182X.2016.03.039
    [29]
    PENG Xiu-yan, ZHANG Wen-ying, JIA Shu-li. The study of fuzzy self-adjusted PID control for ship course based on back propagation method[J]. Control Engineering of China, 2013, 20(4): 623-626. (in Chinese) doi: 10.3969/j.issn.1671-7848.2013.04.009
    [30]
    QIU Cheng-qun, LIU Cheng-lin, SHEN Fa-hua, et al. The design of automobile cruise control system based on MATLAB and fuzzy PID[J]. Transactions of the Chinese Society of Agricultural Engineering, 2012, 28(6): 197-202. (in Chinese) doi: 10.3969/j.issn.1002-6819.2012.06.032
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