Skip to main content
SpringerLink
Log in
Book cover

International Conference on Computational Logistics

ICCL 2018: Computational Logistics pp 106–123Cite as

Survey on Short-Term Technology Developments and Readiness Levels for Autonomous Shipping

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11184))

Abstract

Recently, Autonomous Surface Vessels (ASVs) have attracted a lot of attention. Developing a fully autonomous vessel is challenging. Existing research provides a track from existing manned vessels to a remote-controlled vessel with reduced crews, an unmanned remote-controlled vessel, and at the end, a fully autonomous vessel. The first step is to equip existing vessels to realize autonomous sailing. In this paper, we focus on the technologies that make existing vessels “smarter”. A categorization of technologies is provided based on the basic architecture of ASV: Navigation, Guidance, Control and Hardware. An overview of the technology developments in each category is presented. The Technology Readiness Level (TRL) is applied to indicate whether these technologies could become commercial in the short term.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Situation awareness (2018). https://en.wikipedia.org/wiki/Situation_awareness

  2. Alfi, A., Shokrzadeh, A., Asadi, M.: Reliability analysis of h-infinity control for a container ship in way-point tracking. Appl. Ocean Res. 52, 309–316 (2015)

    Article  Google Scholar 

  3. All about AIS: History of AIS (2012). http://www.allaboutais.com/index.php/en/aisbasics1/ais-history

  4. AMS Transport Crewing Solutions: Factsheet AMS (2017). https://ams-bv.com/images/pdf/Factsheet-NL-AMS-DEF.pdf

  5. Asvadi, A., Premebida, C., Peixoto, P., Nunes, U.: 3D Lidar-based static and moving obstacle detection in driving environments: an approach based on voxels and multi-region ground planes. Robot. Auton. Syst. 83, 299–311 (2016)

    Article  Google Scholar 

  6. Brodkin, J.: SpaceX plans worldwide satellite internet with low latency, gigabit speed (2016). https://arstechnica.com/information-technology/2016/11/spacex-plans-worldwide-satellite-internet-with-low-latency-gigabit-speed/

  7. Campbell, S., Naeem, W., Irwin, G.: A review on improving the autonomy of unmanned surface vehicles through intelligent collision avoidance manoeuvres. Annu. Rev. Control 36(2), 267–283 (2012)

    Article  Google Scholar 

  8. Challenge, S.S.: Covadem: coöperatieve vaardieptemetingen (2017). https://smartshippingchallenge.nl/initiatieven-en-innovaties/covadem-cooperatieve-vaardieptemetingen

  9. Chen, L., Negenborn, R.R., Lodewijks, G.: Path planning for autonomous inland vessels using A*BG. In: Paias, A., Ruthmair, M., Voß, S. (eds.) ICCL 2016. LNCS, vol. 9855, pp. 65–79. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-44896-1_5

    Chapter  Google Scholar 

  10. Chen, L., Hopman, H., Negenborn, R.R.: Distributed model predictive control for vessel train formations of cooperative multi-vessel systems. Transp. Res. Part C Emerg. Technol. 92, 101–118 (2018)

    Article  Google Scholar 

  11. Christiansen, M., Fagerholt, K., Nygreen, B., Ronen, D.: Ship routing and scheduling in the new millennium. Eur. J. Oper. Res. 228(3), 467–483 (2013)

    Article  MathSciNet  Google Scholar 

  12. Christiansen, M., Fagerholt, K., Ronen, D.: Ship routing and scheduling: status and perspectives. Transp. Sci. 38(1), 1–18 (2004)

    Article  Google Scholar 

  13. Das, B., Subudhi, B., Pati, B.B.: Cooperative formation control of autonomous underwater vehicles: an overview. Int. J. Autom. Comput. 13(3), 199–225 (2016)

    Article  Google Scholar 

  14. Ejaz, W., Manzoor, K., Kim, H.J., Jang, B.T., Jin, G.J., Kim, H.S.: Two-state routing protocol for maritime multi-hop wireless networks. Comput. Electr. Eng. 39(6), 1854–1866 (2013)

    Article  Google Scholar 

  15. Escario, J., Jimenez, J., Giron-Sierra, J.: Optimization of autonomous ship maneuvers applying swarm intelligence. In: Proceedings of 2010 IEEE International Conference on Systems Man and Cybernetics, pp. 2603–2610 (2010)

    Google Scholar 

  16. GE Corperation: GE’s marine solutions (2016). http://www.gepowerconversion.com/industries/marine/vessel-automation

  17. Geertsma, R.D., Negenborn, R.R., Visser, K., Hopman, J.J.: Design and control of hybrid power and propulsion systems for smart ships: a review of developments. Appl. Energy 194, 30–54 (2017)

    Article  Google Scholar 

  18. Hermann, D., Galeazzi, R., Andersen, J.C., Blanke, M.: Smart sensor based obstacle detection for high-speed unmanned surface vehicle. In: Proceedings of 10th IFAC Conference on Manoeuvring and Control of Marine Craft, MCMC 2015, Copenhagen, 24–26 August 2015, vol. 48, pp. 190–197 (2015)

    Article  Google Scholar 

  19. Hu, L., Naeem, W., Rajabally, E., Watson, G., Mills, T., Bhuiyan, Z., Salter, I.: COLREGs-compliant path planning for autonomous surface vehicles: a multiobjective optimization. In: Proceedings of 20th IFAC World Congress, vol. 50, pp. 13662–13667 (2017)

    Google Scholar 

  20. Hyundai Heavy Industries Co.: Hyundai heavy develops new collision avoidance system for ships (2014). http://www.ship-technology.com/news/newshyundai-heavy-develops-new-collision-avoidance-system-for-ships-4326091/

  21. Im, N.K., Nguyen, V.S.: Artificial neural network controller for automatic ship berthing using head-up coordinate system. Int. J. Naval Architect. Ocean Eng. 10(3), 235–249 (2018)

    Article  Google Scholar 

  22. Johansen, T.A., Cristofaro, A., Perez, T.: Ship collision avoidance using scenario-based model predictive control. In: Proceedings of 10th IFAC Conference on Control Applications in Marine Systems, CAMS 2016, Trondheim, Norway, 13–16 September, vol. 49, pp. 14–21 (2016)

    Google Scholar 

  23. Khatib, O.: Real-time obstacle avoidance for manipulators and mobile robots. Int. J. Robot. Res. 5(1), 90–98 (1986)

    Article  Google Scholar 

  24. Lazakis, I., Dikis, K., Michala, A.L., Theotokatos, G.: Advanced ship systems condition monitoring for enhanced inspection, maintenance and decision making in ship operations. Transp. Res. Procedia 14(Suppl. C), 1679–1688 (2016)

    Article  Google Scholar 

  25. Lazarowska, A.: A trajectory base method for ship’s safe path planning. Procedia Comput. Sci. 96(2016), 1022–1031 (2016)

    Article  Google Scholar 

  26. Leary, K.: China has launched the world’s first all-electric cargo ship (2017). https://futurism.com/china-launched-worlds-first-all-electric-cargo-ship/

  27. Liu, Z., Zhang, Y., Yu, X., Yuan, C.: Unmanned surface vehicles: an overview of developments and challenges. Annu. Rev. Control 41, 71–93 (2016)

    Article  Google Scholar 

  28. Ma, F., Wu, Q., Yan, X., Chu, X., Zhang, D.: Classification of automatic radar plotting aid targets based on improved fuzzy c-means. Transp. Res. Part C Emerg. Technol. 51(2015), 180–195 (2015)

    Article  Google Scholar 

  29. Mediamobil Communication GmbH and ESA: SASS@Sea - satellite based system and services for broadband applications at sea (2014). https://business.esa.int/projects/sasssea

  30. Mizuno, N., Uchida, Y., Okazaki, T.: Quasi real-time optimal control scheme for automatic berthing. In: Proceedings of 10th IFAC Conference on Manoeuvring and Control of Marine Craft, MCMC 2015, Copenhagen, 24–26 August 2015, vol. 48, pp. 305–312 (2015)

    Article  Google Scholar 

  31. Mu, L.: A hybrid network for maritime on-board communications. In: 2012 IEEE 8th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), pp. 761–768 (2012)

    Google Scholar 

  32. Mu, L., Prinz, A.: Delay-oriented data traffic migration in maritime mobile communication environments. In: Proceedings of 4th International Conference on Ubiquitous and Future Networks (ICUFN 2012), Phuket, Thailand, pp. 417–422 (2012)

    Google Scholar 

  33. Naeem, W., Sutton, R., Ahmad, M.: LQG/LTR control of an autonomous underwater vehicle using a hybrid guidance law. In: Proceedings of 1st IFAC Workshop on Guidance and Control of Underwater Vehicles, Newport, UK, pp. 31–36 (2003)

    Google Scholar 

  34. NASA: Technology readiness level (2012). https://www.nasa.gov/directorates/heo/scan/engineering/technology/txt_accordion1.html

  35. Netherlands Maritime Technology: NMT coördineert nieuw maritiem europees innovatieproject ‘NOVIMAR’ (2017). https://maritimetechnology.nl/nmt-coordineert-nieuw-maritiem-europees-innovatieproject-novimar/

  36. Perkovic, M., Gucma, M., Luin, B., Gucma, L., Brcko, T.: Accommodating larger container vessels using an integrated laser system for approach and berthing. Microprocess. Microsyst. 52, 106–116 (2017)

    Article  Google Scholar 

  37. Rijnmond, R.: Zelfvarend binnenschip komt eraan (2017). https://www.rijnmond.nl/nieuws/161984/Zelfvarend-binnenschip-komt-eraan

  38. RØdseth, H.: Predictive maintenance for autonomous ship - emerging trends in Industrie 4.0 (2016). https://www.cml.fraunhofer.de/content/dam/cml/de/documents/Sonstiges/Autonomous_Ship_Industrie_4.pdf

  39. Rødseth, Ø.J., Burmeister, H.C.: Developments toward the unmanned ship. In: Proceedings of International Symposium Information on Ships-ISIS, vol. 201, pp. 30–31 (2012)

    Google Scholar 

  40. Royal Academy of Engineering: Future ship powering options. Technical report, Royal Academy of Engineering (2013)

    Google Scholar 

  41. Sakib, S.: Implementation of digital imu for increasing the accuracy of hydrographic survey. Procedia Eng. 194, 386–393 (2017)

    Article  Google Scholar 

  42. Sariff, N., Buniyamin, N.: An overview of autonomous mobile robot path planning algorithms. In: Proceedings of the 4th Student Conference on Research and Development, Selangor, Malaysia, pp. 183–188 (2006)

    Google Scholar 

  43. Schiaretti, M., Chen, L., Negenborn, R.R.: Survey on autonomous surface vessels: Part I - a new detailed definition of autonomy levels. In: Bektaş, T., Coniglio, S., Martinez-Sykora, A., Voß, S. (eds.) Computational Logistics. LNCS, vol. 10572, pp. 219–233. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-68496-3_15

    Chapter  Google Scholar 

  44. Schiaretti, M., Chen, L., Negenborn, R.R.: Survey on autonomous surface vessels: Part II - categorization of 60 prototypes and future applications. In: Bektaş, T., Coniglio, S., Martinez-Sykora, A., Voß, S. (eds.) Computational Logistics. LNCS, vol. 10572, pp. 234–252. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-68496-3_16

    Chapter  Google Scholar 

  45. Sørensen, M.E.N., Breivik, M.: Comparing nonlinear adaptive motion controllers for marine surface vessels. In: Proceedings of 10th IFAC Conference on Manoeuvring and Control of Marine Craft, MCMC 2015, Copenhagen, 24–26 August 2015, vol. 48, pp. 291–298 (2015)

    Article  Google Scholar 

  46. Statheros, T., Howells, G., Maier, K.M.: Autonomous ship collision avoidance navigation concepts, technologies and techniques. J’. Navig. 61(1), 129–142 (2008). https://doi.org/10.1017/S037346330700447X

    Article  Google Scholar 

  47. Sumić, D., Peraković, D., Jurcević, M.: Optimizing data traffic route for maritime vessels communications. Procedia Eng. 100, 1286–1293 (2015)

    Article  Google Scholar 

  48. Tesla: Autopilot (2017). https://www.tesla.com/en_GB/autopilot?redirect=no

  49. The Guardian: Facebook drone that could bring global internet access completes test flight (2017). https://www.theguardian.com/technology/2017/jul/02/facebook-drone-aquila-internet-test-flight-arizona

  50. Tran, V.L., Im, N.: A study on ship automatic berthing with assistance of auxiliary devices. Int. J. Naval Archit. Ocean Eng. 4(3), 199–210 (2012)

    Article  Google Scholar 

  51. Tsou, M.C.: Multi-target collision avoidance route planning under an ECDIS framework. Ocean Eng. 121, 268–278 (2016)

    Article  Google Scholar 

  52. United Nations Conference on Trade and Development: Merchant fleet by flag of registration and by type of ship, annual, 1980–2018 (2018). http://unctadstat.unctad.org/wds/TableViewer/tableView.aspx?ReportId=93

  53. Uras, T., Koenig, S.: An empirical comparison of any-angle path-planning algorithms. In: Proceedings of the 8th Annual Symposium on Combinatorial Search, Ein Gedi, Israel, pp. 206–210 (2015)

    Google Scholar 

  54. Wang, X., Liu, Z., Cai, Y.: The ship maneuverability based collision avoidance dynamic support system in close-quarters situation. Ocean Eng. 146, 486–497 (2017)

    Article  Google Scholar 

  55. Wolken-Möhlmann, G., Gottschall, J., Lange, B.: First verification test and wake measurement results using a Ship-LIDAR system. Energy Procedia 53, 146–155 (2014)

    Article  Google Scholar 

  56. Xu, Q.: Collision avoidance strategy optimization based on danger immune algorithm. Comput. Ind. Eng. 76, 268–279 (2014)

    Article  Google Scholar 

  57. Xue, Y., Clelland, D., Lee, B., Han, D.: Automatic simulation of ship navigation. Ocean Eng. 38(17–18), 2290–2305 (2011)

    Article  Google Scholar 

  58. Yalcin, O., Sayar, A., Arar, O., Akpinar, S., Kosunalp, S.: Approaches of road boundary and obstacle detection using LIDAR. In: Proceedings of 1st IFAC Workshop on Advances in Control and Automation Theory for Transportation Applications, vol. 46, pp. 211–215 (2013)

    Article  Google Scholar 

  59. Young, J., Simic, M.: Lidar and monocular based overhanging obstacle detection. Procedia Comput. Sci. 60, 1423–1432 (2015)

    Article  Google Scholar 

  60. Zhang, J., Zhang, D., Yan, X., Haugen, S., Soares, C.G.: A distributed anti-collision decision support formulation in multi-ship encounter situations under COLREGs. Ocean Eng. 105, 336–348 (2015)

    Article  Google Scholar 

  61. Zheng, H., Negenborn, R.R., Lodewijks, G.: Robust distributed predictive control of waterborne AGVs–a cooperative and cost-effective approach. IEEE Trans. Cybern. 48(8), 2449–2461 (2018)

    Article  Google Scholar 

  62. Zhou, M.T., Harada, H.: Cognitive maritime wireless mesh/ad hoc networks. J. Netw. Comput. Appl. 35(2), 518–526 (2012)

    Article  Google Scholar 

  63. Zhu, M., Hahn, A., Wen, Y.Q., Bolles, A.: Identification-based simplified model of large container ships using support vector machines and artificial bee colony algorithm. Appl. Ocean Res. 68, 249–261 (2017)

    Article  Google Scholar 

  64. Zolfagharifard, E.: Now Google is going to dominate space: search giant to launch 180 satellites to provide internet access for the entire planet, sources claim (2014). http://www.dailymail.co.uk/sciencetech/article-2646039/Googles-plans-world-domination-Search-giant-launch-180-satallites-bring-internet-access-ENTIRE-planet.html

Download references

Acknowledgment

This research is partially supported by SmartPort project ‘TET-SP: Autonomous shipping in the Port of Rotterdam’ 2017 and the China Scholarship Council under Grant 201406950041.

Author information

Authors and Affiliations

  1. Department of Maritime and Transport Technology, Delft University of Technology, Delft, The Netherlands

    Laurien E. van Cappelle, Linying Chen & Rudy R. Negenborn

Authors
  1. Laurien E. van Cappelle
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Linying Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rudy R. Negenborn
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Linying Chen .

Editor information

Editors and Affiliations

  1. University of Salerno, Fisciano, Italy

    Raffaele Cerulli

  2. University of Salerno, Fisciano, Italy

    Andrea Raiconi

  3. Institute of Information Systems, University of Hamburg, Hamburg, Germany

    Stefan Voß

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

van Cappelle, L.E., Chen, L., Negenborn, R.R. (2018). Survey on Short-Term Technology Developments and Readiness Levels for Autonomous Shipping. In: Cerulli, R., Raiconi, A., Voß, S. (eds) Computational Logistics. ICCL 2018. Lecture Notes in Computer Science(), vol 11184. Springer, Cham. https://doi.org/10.1007/978-3-030-00898-7_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-00898-7_7

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00897-0

  • Online ISBN: 978-3-030-00898-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation