A machine learning method to support shipping operations in ice: applications to tactical voyage routing and strategic regulatory assessment

Principal Investigator
Dr. Brian Veitch, Memorial University of Newfoundland, Faculty of Engineering and Applied Science

Email: bveitch@mun.ca
Website: https://www.mun.ca/engineering/about/people/brianveitch.php

NRC Collaborator
Matthew Garvin  M.Eng., MBA, P.Eng. Team Lead, Marine Operations Autonomy & Safety | Ocean, Coastal, and River Engineering National Research Council Canada

Project description

The goal of the proposed work is to develop a decision support tool to improve shipping operations in ice covered waters. In particular, the tool will support tactical navigation decisions to optimize on a time horizon of a couple of hours to a few days.

The tool can be used to support decision making across a range of levels of ship autonomy, from providing on-demand routing advice to a bridge crew on board, to serving as a primary source of tactical decisions that the bridge crew can implement, whether they are on board or in a remote control centre, to acting autonomously to navigate an optimal route from departure to destination. Reinforcement learning, an unsupervised machine learning method, is well suited to complex problems that have competing goals, such as shipping operations.

The proposed work is well aligned with OFI’s overarching theme of Safe and Sustainable Development of the Ocean Frontier and with NRC’s Intelligent Marine Assets vision.


We are recruiting a PhD student who will join Memorial University’s School of Graduate Studies and the Faculty of Engineering and Applied Science. Candidates must have a Master’s degree in engineering or computer science. Strong communication skills are important, as well as recent experience with programming. The candidate is expected to work largely independently while in a team context, with a supervisory team from Memorial University and the National Research Council. Familiarity with shipping is an asset, but not essential. The position can start any time between April and September 2021.

Position has been filled.