Seafarer training for autonomous shipping: Needs & challenges

autonomous shipping

This qualitative PhD project aims to explore the multi-dimensional impact of autonomous transportation technology resulting from the application of Industry 4.0 on shipping industry with its seafarers as a critical driver of intelligent transport systems (ITS).

In recent years, Industry 4.0 adoption is started to impact different aspects of maritime transport and logistics. The digital transformation in shipping will contribute to the ITS through a series of disruptions by means of automation and changes to ship design, operations, and manning in order to enhance safety, efficiency, and environmental sustainability1.

The future of autonomous shipping is considered to be a potential solution for imminent challenges of ITS by using digital technologies on a large scale in the maritime domain1.The use of digital technologies will impact the role of seafarers on-board with the potential changes to their training requirements. Thus, to manage the development of new capabilities for incoming careers there is a need to develop strategies to engage operators in their transition from conventional to autonomous shipping.

There is a growing body of research in the innovation and adaptation of technology in smart shipping. However, the human element and its role in the new context is largely neglected and needs to be investigated.


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Project background

Recently, the Industry 4.0 has introduced transformative technologies such as Cyber-Physical Systems (CPS), Internet of Things (IoT), Big Data, Artificial Intelligence, Cloud Computing, and automation technologies2, 3.

This technological advancement of Industry 4.0 is revolutionising transportation industry by introducing intelligent transport systems (ITS)4, 5. In this respect, driverless or fully autonomous transportation systems in the air, road, and at sea are becoming a part of everyday life5. Air transport is using drones for delivery services as unmanned aerial vehicles (UAVs)6. On-road transportation companies, such as Tesla, Volvo, and Mercedes-Benz, are designing and testing self-driving vehicles, changing how we navigate and transport6.

The maritime transportation industry is starting to embrace the digital transformation by introducing smart and autonomous shipping7. Shipping, as the world’s economic engine and the most conservative operating industry, has a direct impact on global trade8, 9, 10.

The influx of advance technologies in the maritime transport industry is becoming tangible by introduction of autonomous shipping. The introduction of autonomous shipping is a highly promising development in the maritime industry, and is technologically feasible. However, several challenges still need to be addressed before autonomous shipping can become a reality2. The pace and extent of automation development in shipping and the gradual change from the experimental to the implementation stage may soon negatively impact several areas, including the human element11.

Although research in autonomous shipping technology is maturing, limited research has been undertaken on how this trend will impact human operators and their roles and responsibilities in the new context. Thus, there is a gap in the field of cognitive human element and a critical need to investigate challenges that the seafarers face in future shipping.

Subsequently, the emerging digitalisation pattern in shipping industries has brought different positive and negative challenges that may become a significant issue for existing seafarers that already being licensed through the current education system1. Simultaneously, the beginning of coexistence of the manned, unmanned, and autonomous transportation systems, in the same environment provokes many questions and challenges11, 12. For example, how will marine operators and future seafarers of autonomous vessels perform at least as safe as crew of manned vessels? This will be a challenge for the training providers, but importantly a challenge for regulatory bodies.

New training requirement should address the variety of issues ranging from curriculum design to its development and delivery. The current project aims to investigate the following research questions:

  1. What are the potential characteristics of the future workplace of seafarers?
  2. What would be the role of seafarers in their future workplaces?
  3. What are the future seafaring skills and competencies required for the changing roles and responsibilities?
  4. What is the effective pathway towards the future seafaring training standards for the transition period to autonomous shipping?

Project methods and objectives

To meet the project’s objectives, this research is designed as an exploratory qualitative study. The qualitative method allows to discover, explore, and understand the new concept and the views, and perceptions toward seafarers’ challenges and training requirements as a critical driver of ITS in the autonomous shipping domain.

A pool of in-depth data will be collected and managed through an interactive and semi-structured approach, that includes audio-video recordings, transcripts, semi-structured interviews, focus group discussions. Data collection will encompass both verbal and non-verbal responses. The sampling design will consist of studying a small and representative sub-group of the relevant stakeholders13. The main objective is to collect and generate data from the five main groups of stakeholders, who are the leading players in the autonomous shipping implementation.

By analysing these stakeholders’ viewpoints who are directly or indirectly involved with this new technology in their work, the project will be able to have a better understanding of the current condition and what will happen in the future of autonomous shipping. The identified stakeholders are as follows:

  • Technology providers
  • Shipping companies
  • Training institutions
  • Seafarers
  • Regulatory bodies

All research data will be analysed manually, which helps the researchers to be actively involved and being part of data analysis processes. When necessary, the computer aided qualitative data analysis software. All the recorded interviews will be transcribed verbatim. The thematic analysis will be conducted as the process to identify patterns or themes within the data set. Through the theoretical saturation of data, the initial and major codes will be established.

The conceptualisation of patterns will be continued till no new pattern emerges, and the connection between these major codes will be carefully examined to allow identification of the main themes and categories. The next step is to elucidate themes and finally drawing and verifying conclusions in a cohesive manner14, 15.


  1. Shahbakhsh, M., Emad, G., & Cahoon, S. (In press). Industrial Revolutions and Transition of the Maritime Industry: The Case of Seafarer’s Role in Autonomous Shipping. The Asian Journal of Shipping and Logistics.
  2. Emad, G., Khabir, M., & Shahbakhsh, M. (2020). Shipping 4.0 and Training Seafarers for the Future Autonomous and Unmanned Ships. Paper presented at the Proceedings of the 21st Marine Industries Conference (MIC 2019)
  3. Imran, F., & Kantola, J. (2018). Review of Industry 4.0 in the light of Sociotechnical System Theory and Competence-Based View: A Future Research Agenda for the Evolute Approach Paper presented at the Advances in Human Factors, Business Management and Society
  4. Heilig, L., Lalla-Ruiz, E., & Voß, S. (2017). Digital transformation in maritime ports: analysis and a game theoretic framework. NETNOMICS: Economic Research and Electronic Networking, 18(2-3), 227-254.
  5. Felski, A., & Zwolak, K. (2020). The ocean-going autonomous ship—Challenges and threats. Journal of Marine Science and Engineering, 8(1), 41.
  6. Lee, J. (2017). Optimization of a modular drone delivery system. Paper presented at the 2017 Annual IEEE International Systems Conference (SysCon)
  7. Ingle, S., & Phute, M. (2016). Tesla autopilot: Semi autonomous driving, an uptick for future autonomy. International Research Journal of Engineering and Technology, 3(9), 369-372.
  8. Johns, M. (2018). Seafarers and digital disruption – The effect of autonomous ships on the work at sea, the role of seafarers and the shipping industry. Retrieved from ICS (Hamburg/London)
  9. Struck, E. (2020). Digital transformation in the shipping industry: how Industry 4.0 is shaping the shipping industry? (Master Degree). Universidade Católica Portuguesa
  10. Zaman, I., Pazouki, K., Norman, R., Younessi, S., & Coleman, S. (2017). Challenges and Opportunities of Big Data Analytics for Upcoming Regulations and Future Transformation of the Shipping Industry. Procedia Engineering, 194, 537-544. doi:10.1016/j.proeng.2017.08.182
  11. Chen, Z., Chen, D., Zhang, Y., Cheng, X., Zhang, M., & Wu, C. (2020). Deep Learning for Autonomous Ship-Oriented Small Ship Detection. Safety Science, 130.
  12. Jo, S., & D’Agostini, E. (2020). Disrupting technologies in the shipping industry: How will MASS development affect the maritime workforce in Korea. Marine Policy, 120.
  13. Felski, A., & Zwolak, K. (2020). The ocean-going autonomous ship—Challenges and threats. Journal of Marine Science and Engineering, 8(1), 41.
  14. Bryman, A. (2012). Social Research Methods (4th edition ed.). United States: Oxford University Press Inc., New York
  15. Deepak Chawla, & Neena Sondhi. (2015). Research Methodology Concepts and Cases (Second ed.): Vikas Publishing House.

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