Predicting the Voyage of a Vessel in a Dynamic Environment

Project Type: Reinforcement Learning Model
Area/Sector: Marine Operations
Company/Partner: Ocean Data Science Inc./Institute for Big Data Analytics
Academic Institution: Dalhousie University
Lead Investigator: Dr. Stan Matwin

In busy ports with daily visitor vessels, it is important to have an efficient monitoring system in place. Assigning human resources (coast guard) to monitor all vessel’s activities is sometimes impossible or a waste of resources.

In this research, we are going to solve this problem by designing an intelligent system to aid monitoring vessels. we are going to train a reinforcement learning model for the Halifax area so that an unmanned vessel (our agent) is able to voyage safely and efficiently from a starting point to a defined destination while there are other vessels moving in the environment (in this case only one moving ship). After training this model, all visiting vessel movements will compare with the predicted trajectory. A deviation in the trajectory of a visiting vessel from the predicted trajectory by our RL model will be considered as a monitoring alert signal.