TY - JOUR

T1 - Predicting ship trajectory based on neural networks using AIS data

AU - Volkova, Tamara A.

AU - Balykina, Yulia E.

AU - Bespalov, Alexander

N1 - Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

PY - 2021/3

Y1 - 2021/3

N2 - To create an autonomously moving vessel, it is necessary to know exactly how to determine the current coordinates of the vessel in the selected coordinate system, determine the actual trajectory of the vessel, estimate the motion trend to predict the current coordinates, and calculate the course correction to return to the line of the specified path. The navigational and hydrographic conditions of navigation on each section of the route determine the requirements for the accuracy of observations and the time spent on locating the vessel. The problem of predicting the trajectory of the vessel's motion in automatic mode is especially important for river vessels or river-sea vessels, predicting the trajectory of the route sections during the maneuvering of the vessel. At the moment, one of the most accurate ways of determining the coordinates of the vessel is by reading the satellite signal. However, when a vessel is near hydraulic structures, problems may arise connected with obtaining a satellite signal due to interference and, therefore, the error in measuring the coordinates of the vessel increases. The likelihood of collisions and various kinds of incidents increases. In such cases, it is possible to correct the trajectory of the movement using an autonomous navigation sys-tem. In this work, opportunities of the possible application of artificial neural networks to create such a corrective system using only the coordinates of the ship's position are discussed. It was found that this is possible on sections of the route where the ship does not maneuver.

AB - To create an autonomously moving vessel, it is necessary to know exactly how to determine the current coordinates of the vessel in the selected coordinate system, determine the actual trajectory of the vessel, estimate the motion trend to predict the current coordinates, and calculate the course correction to return to the line of the specified path. The navigational and hydrographic conditions of navigation on each section of the route determine the requirements for the accuracy of observations and the time spent on locating the vessel. The problem of predicting the trajectory of the vessel's motion in automatic mode is especially important for river vessels or river-sea vessels, predicting the trajectory of the route sections during the maneuvering of the vessel. At the moment, one of the most accurate ways of determining the coordinates of the vessel is by reading the satellite signal. However, when a vessel is near hydraulic structures, problems may arise connected with obtaining a satellite signal due to interference and, therefore, the error in measuring the coordinates of the vessel increases. The likelihood of collisions and various kinds of incidents increases. In such cases, it is possible to correct the trajectory of the movement using an autonomous navigation sys-tem. In this work, opportunities of the possible application of artificial neural networks to create such a corrective system using only the coordinates of the ship's position are discussed. It was found that this is possible on sections of the route where the ship does not maneuver.

KW - AIS Data

KW - Autonomous navigation

KW - Neural networks

KW - Trajectory prediction

KW - Waterway transportation

UR - http://www.scopus.com/inward/record.url?scp=85102264606&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/12083886-9801-3a81-a0a6-193e9ab5f0c8/

U2 - 10.3390/jmse9030254

DO - 10.3390/jmse9030254

M3 - Article

AN - SCOPUS:85102264606

VL - 9

JO - Journal of Marine Science and Engineering

JF - Journal of Marine Science and Engineering

SN - 2077-1312

IS - 3

M1 - 254

ER -