The AMC Test for Maritime Autonomous Navigation Systems

6 pages•Published: January 5, 2024

Abstract

The rapid development and testing of autonomous navigation technologies in the maritime industry requires standardised evaluation methods to ensure safe and efficient operations. This paper highlights examples of class approvals granted to autonomous technologies, underscoring the industry's progress in adopting these systems and introduces the AMC Test, a comprehensive assessment framework for Maritime Autonomous Navigation Systems (ANS). The paper argues for the need for an in-depth standardised test to evaluate compliance with the International Regulations for the Prevention of Collisions at Sea (ColRegs). The proposed AMC Test consists of 80 simulator scenarios categorised into Power Driven Vessel (PDV) Open Sea, Restricted Visibility, Coastal, and Complex Navigation sections. The testbed, built upon the Frazer Nash ColRegs framework, assesses the ANS system's understanding of the situation, adherence to ColRegs, consideration of the impact on other vessels, and anticipation of their actions. Assumptions based on relevant research support the realistic scenarios created during the test. By providing a comprehensive evaluation framework, the AMC Test enables stakeholders to assess the performance and safety of ANS systems in accordance with established regulations and industry accepted practice.

Keyphrases: amc test, autonomous navigation, colregs compliance, maritime safety, simulator evaluation

In: G. Reza Emad and Aditi Kataria (editors). Proceedings of the International Conference on Maritime Autonomy and Remote Navigation 2023, vol 2, pages 53-58.

Links:	https://easychair.org/publications/paper/MqlQ
	https://doi.org/10.29007/hswk

BibTeX entry

@inproceedings{ICMARNAV2023:AMC_Test_Maritime_Autonomous,
  author    = {Nick Bonser},
  title     = {The AMC Test for Maritime Autonomous Navigation Systems},
  booktitle = {Proceedings of the International Conference on Maritime Autonomy and Remote Navigation 2023},
  editor    = {G. Reza Emad and Aditi Kataria},
  series    = {EPiC Series in Technology},
  volume    = {2},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2516-2322},
  url       = {/publications/paper/MqlQ},
  doi       = {10.29007/hswk},
  pages     = {53-58},
  year      = {2024}}

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