Distributed Multi-Objective Algorithm for Preventing Multi-Ship Collisions at Sea
Avoidance of collisions at sea is crucial to navigational safety. In this paper, we use a distributed algorithm to communicate the entire collision avoidance trajectory information for each ship. In each communication, we suggest a new improvement function considering safety and efficiency to identi...
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| Vydáno v: | Journal of navigation Ročník 73; číslo 5; s. 971 - 990 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Cambridge, UK
Cambridge University Press
01.09.2020
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| ISSN: | 0373-4633, 1469-7785 |
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| Abstract | Avoidance of collisions at sea is crucial to navigational safety. In this paper, we use a distributed algorithm to communicate the entire collision avoidance trajectory information for each ship. In each communication, we suggest a new improvement function considering safety and efficiency to identify the avoidance ship in each cycle. Considering the nonlinear collision avoidance trajectory of ships, a new method for calculating the degree of danger using a velocity obstacle algorithm is proposed. Therefore, in each communication, each ship considers the avoidance behaviours of other ships in planning its avoidance trajectory. Additionally, we combine bi-criterion evolution (BCE) and the ant lion optimiser to plan the entire collision avoidance path. Three scenarios are designed to demonstrate the performance of this method. The results show that the proposed method can find a suitable collision-free solution for all ships. |
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| AbstractList | Avoidance of collisions at sea is crucial to navigational safety. In this paper, we use a distributed algorithm to communicate the entire collision avoidance trajectory information for each ship. In each communication, we suggest a new improvement function considering safety and efficiency to identify the avoidance ship in each cycle. Considering the nonlinear collision avoidance trajectory of ships, a new method for calculating the degree of danger using a velocity obstacle algorithm is proposed. Therefore, in each communication, each ship considers the avoidance behaviours of other ships in planning its avoidance trajectory. Additionally, we combine bi-criterion evolution (BCE) and the ant lion optimiser to plan the entire collision avoidance path. Three scenarios are designed to demonstrate the performance of this method. The results show that the proposed method can find a suitable collision-free solution for all ships. |
| Author | Wang, Hongbo Guan, Zhiying Li, Jinxin Pan, Chong |
| Author_xml | – sequence: 1 givenname: Jinxin orcidid: 0000-0001-8598-2098 surname: Li fullname: Li, Jinxin organization: (State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun, China) – sequence: 2 givenname: Hongbo surname: Wang fullname: Wang, Hongbo email: wang_hongbo@jlu.edu.cn organization: (State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun, China) – sequence: 3 givenname: Zhiying surname: Guan fullname: Guan, Zhiying organization: (State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun, China) – sequence: 4 givenname: Chong surname: Pan fullname: Pan, Chong organization: (State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun, China) |
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| CitedBy_id | crossref_primary_10_1016_j_oceaneng_2023_115888 crossref_primary_10_3390_jmse13050887 crossref_primary_10_1016_j_oceaneng_2023_116038 crossref_primary_10_3390_jmse10060814 crossref_primary_10_3390_jmse8121002 crossref_primary_10_1016_j_oceaneng_2025_122537 crossref_primary_10_1017_S0373463323000012 crossref_primary_10_1007_s00773_021_00796_z crossref_primary_10_1016_j_asoc_2025_113865 crossref_primary_10_1016_j_oceaneng_2024_119512 crossref_primary_10_3233_JCM_247518 crossref_primary_10_1016_j_ocecoaman_2024_107450 crossref_primary_10_1109_ACCESS_2021_3059248 crossref_primary_10_3390_jmse10081047 crossref_primary_10_3390_jmse10060765 crossref_primary_10_1016_j_oceaneng_2023_115510 crossref_primary_10_1016_j_oceaneng_2023_116524 crossref_primary_10_1016_j_apor_2025_104753 crossref_primary_10_3390_jmse10111688 crossref_primary_10_3390_jmse12101719 crossref_primary_10_3390_jmse10111723 crossref_primary_10_3390_jmse11020337 crossref_primary_10_1017_S0373463322000650 crossref_primary_10_1109_TITS_2024_3419046 crossref_primary_10_3389_fmars_2024_1516586 crossref_primary_10_3390_app11167299 crossref_primary_10_1016_j_oceaneng_2022_111666 crossref_primary_10_1109_TTE_2022_3221643 |
| Cites_doi | 10.1016/j.oceaneng.2018.01.001 10.1017/S0373463318000796 10.1109/TEVC.2015.2504730 10.2991/iccse-15.2015.20 10.1080/02533839.2015.1047799 10.1155/2019/4068783 10.2478/pomr-2018-0092 10.12716/1001.09.01.03 10.1109/TITS.2014.2376031 10.1016/j.oceaneng.2018.10.008 10.1007/s10514-016-9580-2 10.1017/S0373463312000483 10.1016/j.oceaneng.2019.106158 10.51400/2709-6998.1929 10.1016/j.advengsoft.2015.01.010 10.1155/2018/7586496 10.20965/jaciii.2014.p0839 10.1007/s10489-011-0319-7 10.1017/S037346331700008X 10.1016/j.oceaneng.2018.07.012 10.1016/j.oceaneng.2016.08.030 10.1016/j.ress.2013.04.006 10.1016/j.jfranklin.2018.07.042 10.1017/S0373463318000048 |
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| SubjectTerms | Algorithms Avoidance behaviour Collision avoidance Collision dynamics Collisions Communication Methods Multiple objective analysis Navigational safety Safety Ships Trajectory planning Velocity |
| Title | Distributed Multi-Objective Algorithm for Preventing Multi-Ship Collisions at Sea |
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