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Towards adaptive trajectories for mixed autonomous and human-operated ships

Danilo Pianini, Sven Tomforde

TL;DR

This work elaborate on the challenges of trajectory prediction and adaptation for mixed autonomous and human-operated ships, and proposes initial ideas on potential approaches to address them.

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.

Towards adaptive trajectories for mixed autonomous and human-operated ships

TL;DR

This work elaborate on the challenges of trajectory prediction and adaptation for mixed autonomous and human-operated ships, and proposes initial ideas on potential approaches to address them.

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.
Paper Structure (16 sections, 2 figures)

This paper contains 16 sections, 2 figures.

Table of Contents

  1. Introduction
  2. Current state in autonomous ships
  3. Reference future scenario
  4. Challenges
  5. Heterogeneity
  6. Mixed autonomic and human operation
  7. Partial information
  8. Communication challenges
  9. Safety and security
  10. Promising research directions
  11. Field-based approaches to trajectory computation
  12. Adaptive communication through anisotropic fields
  13. Information dependability through error-aware fields
  14. Runtime reconfiguration via pulverisation
  15. Learning-based approaches
  16. ...and 1 more sections

Figures (2)

  • Figure 1: The "MS Wavelab" -- a test environment for autonomous ferries in Kiel (June 2023).
  • Figure 2: Pictorial representation of the communication technologies aboard a ship. Different colours indicate a different communication technology: short- (purple), mid- (green), and long-range (lime). Dashed lines with coloured shades represent communication ranges, dotted lines represent communication links. Ships may use multiple communication technologies at the same time to communicate with the land station or other ships.