Journal is indexed in following databases:



2022 Journal Impact Factor - 0.6
2022 CiteScore - 1.7



HomePage
 




 


 

ISSN 2083-6473
ISSN 2083-6481 (electronic version)
 

 

 

Editor-in-Chief

Associate Editor
Prof. Tomasz Neumann
 

Published by
TransNav, Faculty of Navigation
Gdynia Maritime University
3, John Paul II Avenue
81-345 Gdynia, POLAND
www http://www.transnav.eu
e-mail transnav@umg.edu.pl
Verification of a Deterministic Ship's Safe Trajectory Planning Algorithm from Different Ships’ Perspectives and with Changing Strategies of Target Ships
Times cited (SCOPUS): 3
ABSTRACT: The paper presents results of a ship's safe trajectory planning method verification - the Trajectory Base Algorithm, which is a deterministic approach for real-time path-planning with collision avoidance. The paper presents results of the algorithm’s verification from different ships’ perspectives and with changing strategies of target ships. Results prove the applicability of the algorithm in the Collision Avoidance Module of the Autonomous Navigation System for Maritime Autonomous Surface Ships.
REFERENCES
ABS: Autonomous Vessels: ABS’ Classification Perspective, http://onlinepubs.trb.org/onlinepubs/mb/2016spring/presentations/jorgensen.pdf, last accessed 2021/02/16.
Bratić, K., Pavić, I., Vukša, S., Stazić, L.: Review of Autonomous and Remotely Controlled Ships in Maritime Sector. Trans. Marit. Sci. 8, 2, 253–265 (2019). - doi:10.7225/toms.v08.n02.011
Brekke, E.F., Wilthil, E.F., Eriksen, B.-O.H., Kufoalor, D.K.M., Helgesen, Ø.K., Hagen, I.B., Breivik, M., Johansen, T.A.: The Autosea project: Developing closed-loop target tracking and collision avoidance systems. Journal of Physics: Conference Series. 1357, 012020 (2019). - doi:10.1088/1742-6596/1357/1/012020
BV: Smart ships. Addressing cyber risk, improving performance, https://marine-offshore.bureauveritas.com/sites/g/files/zypfnx136/files/media/document/%231131_BV_4PagesMARINE_BD_1.pdf, last accessed 2021/02/16.
DNV GL: The ReVolt. A new inspirational ship concept, https://www.dnvgl.com/technology-innovation/revolt/index.html, last accessed 2021/02/16.
EMSA: Annual overview of marine casualties and incidents 2020, http://www.emsa.europa.eu/newsroom/latest-news/item/4266-annual-overview-of-marine-casualties-and-incidents-2020.html, last accessed 2021/02/16.
IAI: Katana - USV System, https://www.iai.co.il/p/katana, last accessed 2021/02/16.
Kalinowski, A., Małecki, J.: Polish USV ‘EDREDON’ and non-European USV: a comparative sketch. null. 16, 4, 416–419 (2017). - doi:10.1080/20464177.2017.1384441
Kang, Y.-T., Chen, W.-J., Zhu, D.-Q., Wang, J.-H.: Collision avoidance path planning in multi-ship encounter situations. Journal of Marine Science and Technology. (2021). - doi:10.1007/s00773-021-00796-z
Kitowski, Z., Soliński, R.: Application of Domestic Unmanned Surface Vessels in the Area of Internal Security and Maritime Economy — Capacities and Directions for Development. Scientific Journal of Polish Naval Academy. 206, 3, 67–83 (2016). - doi:10.5604/0860889x.1224747
Kongsberg: YARA Birkeland – Autonomous ship project, https://www.kongsberg.com/maritime/support/themes/autonomous-ship-project-key-facts-about-yara-birkeland/, last accessed 2021/02/16.
Koszelew, J., Karbowska-Chilinska, J., Ostrowski, K., Kuczyński, P., Kulbiej, E., Wołejsza, P.: Beam Search Algorithm for Anti-Collision Trajectory Planning for Many-to-Many Encounter Situations with Autonomous Surface Vehicles. Sensors. 20, 15, (2020). - doi:10.3390/s20154115
Kuczkowski, Ł., Śmierzchalski, R.: Path planning algorithm for ship collisions avoidance in environment with changing strategy of dynamic obstacles. In: Mitkowski, W., Kacprzyk, J., Oprzędkiewicz, K., and Skruch, P. (eds.) Trends in Advanced Intelligent Control, Optimization and Automation. pp. 641–650 Springer International Publishing, Cham (2017).
Kufoalor, D.K.M., Johansen, T.A., Brekke, E.F., Hepsø, A., Trnka, K.: Autonomous maritime collision avoidance: Field verification of autonomous surface vehicle behavior in challenging scenarios. Journal of Field Robotics. 37, 3, 387–403 (2020). - doi:10.1002/rob.21919
L3 ASV: C-Target 9, https://www.unmannedsystemstechnology.com/company/autonomous-surface-vehicles-ltd/, last accessed 2021/02/16.
Lazarowska, A.: A Discrete Artificial Potential Field for Ship Trajectory Planning. Journal of Navigation. 73, 1, 233–251 (2020). - doi:10.1017/S0373463319000468
Lazarowska, A.: A new deterministic approach in a decision support system for ship’s trajectory planning. Expert Systems with Applications. 71, 469–478 (2017). - doi:10.1016/j.eswa.2016.11.005
Lisowski, J.: Game Control Methods Comparison when Avoiding Collisions with Multiple Objects Using Radar Remote Sensing. Remote Sensing. 12, 10, (2020). - doi:10.3390/rs12101573
Lisowski, J., Mohamed-Seghir, M.: Comparison of Computational Intelligence Methods Based on Fuzzy Sets and Game Theory in the Synthesis of Safe Ship Control Based on Information from a Radar ARPA System. Remote Sensing. 11, 1, (2019). - doi:10.3390/rs11010082
Mohamed-Seghir, M.: The fuzzy properties of the ship control in collision situations. In: 2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA). pp. 107–112 (2017). - doi:10.1109/INISTA.2017.8001141
Munim, Z.H.: Autonomous ships: a review, innovative applications and future maritime business models. null. 20, 4, 266–279 (2019). - doi:10.1080/16258312.2019.1631714
MUNIN: Maritime Unmanned Navigation through Intelligence in Networks, http://www.unmanned-ship.org/munin/about/, last accessed 2021/02/16.
MUNIN: Maritime Unmanned Navigation through Intelligence in Networks. D8.6: Final Report: Autonomous Bridge, http://www.unmanned-ship.org/munin/wp-content/uploads/2015/09/MUNIN-D8-6-Final-Report-Autonomous-Bridge-CML-final.pdf, last accessed 2021/02/16.
NTNU: Autoferry – Autonomous all-electric passenger ferries for urban water transport, https://www.ntnu.edu/autoferry, last accessed 2021/02/16.
NTNU: Autosea – Sensor fusion and collision avoidance for autonomous surface vehicles, https://www.ntnu.edu/autosea/, last accessed 2021/02/16.
Rolls-Royce: Remote and Autonomous Ship - The next step, https://www.rolls-royce.com/~/media/Files/R/Rolls-Royce/documents/customers/marine/ship-intel/aawa-whitepaper-210616.pdf, last accessed 2021/02/16.
Rolls-Royce: SVAN – Safer Vessel with Autonomous Navigation, https://breakingwaves.fi/wp-content/uploads/2019/06/SVAN-presentation.pdf, last accessed 2021/02/16.
Szłapczynśki, R., Szłapczyńska, J.: Customized crossover in evolutionary sets of safe ship trajectories. International Journal of Applied Mathematics and Computer Science. 22, 4, 999–1009 (2012). - doi:10.2478/v10006-012-0074-x
Szlapczynski, R., Szlapczynska, J.: On evolutionary computing in multi-ship trajectory planning. Applied Intelligence. 37, 2, 155–174 (2012). - doi:10.1007/s10489-011-0319-7
Tam, C., Bucknall, R.: Cooperative path planning algorithm for marine surface vessels. Ocean Engineering. 57, 25–33 (2013). - doi:10.1016/j.oceaneng.2012.09.003
Tam, C., Bucknall, R.: Path-planning algorithm for ships in close-range encounters. Journal of Marine Science and Technology. 15, 4, 395–407 (2010). - doi:10.1007/s00773-010-0094-x
Tianxing-1: Unmanned Surface Vehicle, https://www.defenseworld.net/news/21536/China_Unveils_New_Unmanned_Surface_Vehicle_Tianxing_1#.YCurbKvPxPY, last accessed 2021/02/16.
W. Zhang, C. Yan, H. Lyu, P. Wang, Z. Xue, Z. Li, B. Xiao: COLREGS-based Path Planning for Ships at Sea Using Velocity Obstacles. IEEE Access. 9, 32613–32626 (2021). - doi:10.1109/ACCESS.2021.3060150
Wróbel, K., Montewka, J., Kujala, P.: Towards the assessment of potential impact of unmanned vessels on maritime transportation safety. Reliability Engineering & System Safety. 165, 155–169 (2017). - doi:10.1016/j.ress.2017.03.029
Citation note:
Lazarowska A.: Verification of a Deterministic Ship's Safe Trajectory Planning Algorithm from Different Ships’ Perspectives and with Changing Strategies of Target Ships. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 15, No. 3, doi:10.12716/1001.15.03.17, pp. 623-628, 2021
Authors in other databases:

Other publications of authors:


File downloaded 243 times








Important: TransNav.eu cookie usage
The TransNav.eu website uses certain cookies. A cookie is a text-only string of information that the TransNav.EU website transfers to the cookie file of the browser on your computer. Cookies allow the TransNav.eu website to perform properly and remember your browsing history. Cookies also help a website to arrange content to match your preferred interests more quickly. Cookies alone cannot be used to identify you.
Akceptuję pliki cookies z tej strony