Assessment Brief: Maritime Autonomous Systems – Regulatory Compliance and Operational Safety Analysis

Module: Advanced Maritime Autonomy and Remote Operations

Level: 7 (Postgraduate)
Credit Value: 20 Credits
Assessment Weighting: 50% of module grade
Word Count: 4,000 words (+/- 10%)
Submission Deadline: Week 14, Term 2


Assessment Task

Develop a comprehensive technical analysis examining the regulatory compliance framework and operational safety considerations for Maritime Autonomous Surface Ships (MASS). Your analysis must critically evaluate the integration of autonomous navigation systems within existing maritime regulatory structures, assess human-machine interface requirements, and propose evidence-based recommendations for safe deployment within specified operational design domains.

Select ONE operational scenario from the following categories:

  1. Coastal Autonomous Ferry Operations (Degree of Autonomy 2-3, remote control with onboard seafarers)
  2. Offshore Supply Vessel with Remote Operations Centre (Degree of Autonomy 3, remote control from shore)
  3. Autonomous Container Feeder Service (short-sea trade routes, Degree of Autonomy 2-4)
  4. Unmanned Survey Vessel Operations (oceanographic data collection, Degree of Autonomy 4)
  5. Military Mine Countermeasure Vessel (autonomous navigation in restricted waters)

Learning Outcomes Assessed

LO1: Critically analyze the regulatory frameworks governing Maritime Autonomous Surface Ships (MASS) development and deployment
LO2: Evaluate autonomous navigation system capabilities against COLREGs compliance requirements and collision avoidance protocols
LO3: Assess human factors considerations including Remote Operations Centre (ROC) design, operator competencies, and human-machine interface requirements
LO4: Synthesize technical, regulatory, and operational data to propose safe operational design domains for autonomous maritime systems

✏️ Tackling a Similar Assignment?

Get a Custom-Written Paper Delivered on Time

Our subject-specialist writers craft plagiarism-free, rubric-matched papers from scratch β€” serving students in Australia, UK, UAE, Kuwait, Canada & USA.

Start My Order β†’Use BISHOPS β€” 25% off first order

Assessment Structure

Section 1: Regulatory Framework Analysis (25%)

  • Current IMO MASS Code development status and implementation timeline
  • UK Maritime and Coastguard Agency (MCA) guidance application (MGN 664, MGN 702)
  • Classification society rules and standards (Lloyd’s Register, DNV, etc.)
  • International comparison: EU, US, Japan regulatory approaches
  • Legal considerations: liability, insurance, master responsibility

Section 2: Autonomous System Technical Evaluation (30%)

  • Autonomous navigation system architecture and capabilities
  • Sensor fusion and situational awareness mechanisms
  • COLREGs interpretation algorithms and decision-making logic
  • Operational Design Domain (ODD) definition and boundary recognition
  • Failure mode analysis and fail-safe protocols
  • Cybersecurity considerations for remote operations
  • Communication redundancy and latency management

Section 3: Human Factors and Remote Operations (25%)

  • Remote Operations Centre (ROC) design requirements
  • Operator training, competency standards, and certification pathways
  • STCW Convention applicability to autonomous operations
  • Human-machine interface design and operator workload assessment
  • Crew transition from traditional to autonomous/remote operations
  • Decision authority allocation between onboard systems and ROC

Section 4: Safety Case Development and Recommendations (20%)

  • Risk assessment methodology (HAZID, HAZOP, FMEA)
  • Operational safety case structure for selected scenario
  • Validation and verification testing requirements (synthetic environment testing)
  • Progressive deployment strategy recommendations
  • Future regulatory development needs
  • Barriers to commercial deployment and mitigation strategies

Submission Requirements

  • Technical report with executive summary
  • Minimum 20 references from peer-reviewed sources, regulatory documents, and industry publications (2019-2025)
  • Risk assessment matrix included in appendices
  • Operational Design Domain specification diagram
  • All technical diagrams and system architectures properly referenced
  • Harvard referencing throughout

Assessment Criteria

Distinction (70-100%): Demonstrates sophisticated understanding of MASS regulatory complexity; applies advanced analytical frameworks to autonomous system evaluation; synthesizes international regulatory approaches; provides innovative solutions to human factors challenges; produces detailed, implementable safety case.

Merit (60-69%): Competent analysis of MASS regulatory framework; sound technical evaluation of autonomous systems; appropriate assessment of human factors; well-structured safety recommendations; good engagement with contemporary literature.

Pass (50-59%): Adequate coverage of regulatory requirements; basic technical system analysis; acceptable human factors consideration; meets minimum safety case requirements; demonstrates foundational understanding of MASS operations.

Fail (0-49%): Incomplete regulatory analysis; significant technical evaluation gaps; insufficient human factors assessment; weak or absent safety case development; inadequate engagement with academic and regulatory sources.


Academic Integrity

All submissions undergo Turnitin plagiarism detection. Collusion, contract cheating, or unauthorized AI-generated content constitutes academic misconduct under university regulations.

⏰ Deadline Pressure?

EssayBishops Writers Are Online Right Now

Thousands of students at universities worldwide submit with confidence using our expert writing service. Human-written, Turnitin-safe, on time.


References/Learning Materials

Burmeister, H.C., Bruhn, W., RΓΈdseth, Ø.J. and Porathe, T. (2014) ‘Autonomous unmanned merchant vessel and its contribution towards the e-Navigation implementation: The MUNIN perspective’, International Journal of e-Navigation and Maritime Economy, 1, pp. 1-13. Available at: https://doi.org/10.1016/j.enavi.2014.12.002

Fan, C., WrΓ³bel, K., Montewka, J., Gil, M., Wan, C. and Zhang, D. (2020) ‘A framework to identify factors influencing navigational risk for Maritime Autonomous Surface Ships’, Ocean Engineering, 202, 107188. Available at: https://doi.org/10.1016/j.oceaneng.2020.107188

Mallam, S.C., Nazir, S. and Renganayagalu, S.K. (2019) ‘Rethinking maritime education, training, and operations in the digital era: Applications for emerging immersive technologies’, Journal of Marine Science and Engineering, 7(12), 428. Available at: https://doi.org/10.3390/jmse7120428

WrΓ³bel, K., Montewka, J. and Kujala, P. (2017) ‘Towards the assessment of potential impact of unmanned vessels on maritime transportation safety’, Reliability Engineering & System Safety, 165, pp. 155-169. Available at: https://doi.org/10.1016/j.ress.2017.03.029

Zhou, X.Y., Liu, Z.J., Wang, F.W., Wu, Z.L. and Cui, R.X. (2020) ‘Towards full autonomy of unmanned surface vehicle: A survey on recent progress in automatic path planning’, Journal of Marine Science and Engineering, 8(12), 977. Available at: https://doi.org/10.3390/jmse8120977

βœ“ 100% Plagiarism-Free
βœ“ PhD & Master's Writers
βœ“ On-Time Delivery
βœ“ Free Unlimited Revisions
βœ“ APA / Harvard / MLA
βœ“ 256-bit SSL Secure
Verified Academic Expert
This article was written and reviewed by a verified academic professional with postgraduate qualifications. All content is original, evidence-based, and written to assist students in Australia, UK, UAE, Kuwait, Canada, and USA.

Frequently Asked Questions