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Learning Representative Vessel Trajectories Using Behavioral Cloning

Löwenstrom, Jan and Solano Carrillo, Edgardo and Stoppe, Jannis (2022) Learning Representative Vessel Trajectories Using Behavioral Cloning. In: Proceedings of the MARESEC. European Workshop on Maritime Systems Resilience and Security 2022 (MARESEC 2022), Bremerhaven, Germany. doi: 10.5281/zenodo.7143586.

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Abstract

We suggest a data-driven approach to predict vessel trajectories by mimicking the underlying policy of human captains. Decisions made by those experts are recorded by the automatic identification system (AIS) signals and can be fused with additional non-kinematic factors like destination, weather condition, current tide level or ship size to get a more accurate snapshot of the situation that led to chosen maneuvers. In this work, we explore the usage of a method meant for optimal control, namely Behavioral Cloning, in a forecasting problem, in order to generate end-to-end vessel trajectories purely based on a given initial state. The training and test datasets consist of trajectories from the coast of Bremerhaven, having more than one thousand unique ships and different motion clusters. These are processed by a single deep-learning model, showing promising results in terms of accuracy and providing a research avenue for a near real-time application where vessel trajectories are to be forecast from a given snapshot of the situation - not from the costly history of all the vessels present.

Item URL in elib:https://elib.dlr.de/193097/
Document Type:Conference or Workshop Item (Speech)
Title:Learning Representative Vessel Trajectories Using Behavioral Cloning
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Löwenstrom, JanUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Solano Carrillo, EdgardoUNSPECIFIEDhttps://orcid.org/0000-0002-9914-4666UNSPECIFIED
Stoppe, JannisUNSPECIFIEDhttps://orcid.org/0000-0003-2952-3422UNSPECIFIED
Date:4 October 2022
Journal or Publication Title:Proceedings of the MARESEC
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
DOI:10.5281/zenodo.7143586
Status:Published
Keywords:Behavioral cloning, vessel trajectory prediction, imitation, reinforcement learning, maritime situational awareness
Event Title:European Workshop on Maritime Systems Resilience and Security 2022 (MARESEC 2022)
Event Location:Bremerhaven, Germany
Event Type:Workshop
HGF - Research field:other
HGF - Program:other
HGF - Program Themes:other
DLR - Research area:no assignment
DLR - Program:no assignment
DLR - Research theme (Project):no assignment
Location: Bremerhaven
Institutes and Institutions:Institute for the Protection of Maritime Infrastructures > Maritime Security Technologies
Deposited By: Solano Carrillo, Edgardo
Deposited On:13 Jan 2023 09:47
Last Modified:13 Jan 2023 09:47

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