7 papers
Does Latent Context Help? A Controlled Evaluation of Inverse Reinforcement Learning in Arctic Shipping
Vaishnav Vaidheeswaran, Dilith Jayakody, Biruk Ambaw +3
Artificial Intelligence (AI)-assisted navigation can help Arctic shipping adapt to rapidly changing sea-ice conditions, but reliable deployment requires reward models that are inte…
Transferable Dual-Stream Representations for Mesoscale-Preserving Sea Surface Temperature Downscaling
Parth Doshi, Priyanka Aravindan, Vaishnav Vaidheeswaran +2
Deep learning models for scientific spatio-temporal downscaling often minimize reconstruction error while failing to preserve physically meaningful multi-scale structure. For sea s…
MoCo-AIS: A Contrastive Learning Framework for Similarity Computation of Vessel Trajectories
Ruixin Song, Md Mahbub Alam, Zahra Sadeghi +4
Trajectory similarity is a fundamental task in analyzing mobility patterns, essential for applications such as route pattern extraction, mobility prediction, and anomaly detection.…
Modeling Maritime Transportation Behavior Using AIS Trajectories and Markovian Processes in the Gulf of St. Lawrence
Gabriel Spadon, Ruixin Song, Vaishnav Vaidheeswaran +3
Maritime transportation is central to the global economy, and analyzing its large-scale behavioral data is critical for operational planning, environmental stewardship, and governa…
Goal-Conditioned Reinforcement Learning for Data-Driven Maritime Navigation
Vaishnav Vaidheeswaran, Dilith Jayakody, Samruddhi Mulay +3
Routing vessels through narrow and dynamic waterways is challenging due to changing environmental conditions and operational constraints. Existing vessel-routing studies typically…
Multi-vessel Interaction-Aware Trajectory Prediction and Collision Risk Assessment
Md Mahbub Alam, Jose F. Rodrigues-Jr, Gabriel Spadon
Accurate vessel trajectory prediction is essential for enhancing situational awareness and preventing collisions. Still, existing data-driven models are constrained mainly to singl…