mlsanityData to 7 Oct 2026

Constructing Trajectory and Predicting Estimated Time of Arrival for Long Distance Travelling Vessels: A Probability Density-based Scanning Approach

arXiv 2205.07945 ↗First posted 13 May 2022eess.SY cs.AI cs.CEcited by 1

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Abstract (arXiv)

In this study, a probability density-based approach for constructing trajectories is proposed and validated through an typical use-case application: Estimated Time of Arrival (ETA) prediction given origin-destination pairs. The ETA prediction is based on physics and mathematical laws given by the extracted information of probability density-based trajectories constructed. The overall ETA prediction errors are about 0.106 days (i.e. 2.544 hours) on average with 0.549 days (i.e. 13.176 hours) standard deviation, and the proposed approach has an accuracy of 92.08% with 0.959 R-Squared value for overall trajectories between Singapore and Australia ports selected.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 1 of its 10 references that are in the map. First posted on arXiv 13 May 2022.

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1 of 10 references.

References · 1

  1. 2018Grand Challenge: Real-time Destination and ETA Prediction for Maritime Trafficcited by 3

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