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Risk-based Autonomous Maritime Collision Avoidance Considering Obstacle Intentions

Tengesdal, Trym; Johansen, Tor Arne; Brekke, Edmund Førland
Chapter
Accepted version
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Tengesdal (749.7Kb)
URI
https://hdl.handle.net/11250/2687056
Date
2020
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  • Institutt for teknisk kybernetikk [2238]
  • Publikasjoner fra CRIStin - NTNU [20804]
Original version
10.23919/FUSION45008.2020.9190212
Abstract
A robust and efficient Collision Avoidance (COLAV) system for autonomous ships is dependent on a high degree of situational awareness. This includes inference of the intent of nearby obstacles, including compliance with traffic rules such as COLREGS, in order to enable more intelligent decision making for the autonomous agent. Here, a generalized framework for obstacle intent inference is introduced. Different obstacle intentions are then considered in the Probabilistic Scenario-Based Model Predictive Control (PSB-MPC) COLAV algorithm using an examplatory intent model, when statistics about traffic rules compliance and the next waypoint for an obstacle are assumed known. Simulation results show that the resulting COLAV system is able to make safer decisions when utilizing the extra intent information
Publisher
IEEE

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