Towards adaptive trajectories for mixed autonomous and human-operated ships

TL;DR

This paper discusses the challenges and initial ideas for developing adaptive trajectory planning for mixed autonomous and human-operated ships, considering the complex maritime environment and decentralized communication.

Contribution

It highlights the unique challenges in maritime autonomous navigation and proposes initial approaches for trajectory prediction and adaptation in mixed ship environments.

Findings

Identified key challenges in maritime autonomous navigation.

Proposed initial ideas for trajectory prediction and adaptation.

Addressed decentralized communication issues in maritime settings.

Abstract

We are witnessing the rise of autonomous cars, which will likely revolutionize the way we travel. Arguably, the maritime domain lags behind, as ships operate on many more degrees of freedom (thus, a much larger search space): there is less physical infrastructure, and rules are less consistent and constraining than what is found on roads. The problem is further complicated by the inevitable co-existence of autonomous and human-operated ships: the latter may take unpredictable decisions, which require adjustments on the autonomous ones. Finally, the problem is inherently decentralised, there is no central authority, and communication means can be very diverse in terms of communication distance and performance, mandating special care on which information is shared and how. In this work, we elaborate on the challenges of trajectory prediction and adaptation for mixed autonomous and human-operated ships, and we propose initial ideas on potential approaches to address them.