Vessel Trajectory Prediction

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Vessel trajectory prediction estimates where ships will move, supporting navigation, traffic management, and collision avoidance. Most approaches learn from Automatic Identification System (AIS) histories using LSTMs, Transformers, or attention models; newer methods also incorporate maps, weather, nearby vessels, route intent, and visual data, or retrieve similar historical movements. Forecasts may be deterministic or probabilistic, and some systems add navigational rules or feasibility constraints to produce safer, more realistic routes. A central challenge is balancing accurate short-term forecasts with stable long-horizon predictions, while evaluations must guard against data leakage and test generalization to unfamiliar regions and vessels.

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21 papers1 paper in the last four weeks, down 67% on the four weeks before. 0.0% of all new papers.

Probabilistic Ship Trajectory Forecasting using Transformer Models on AIS Data
Oct 9, 2026Frederik E. T. SchöllerVessel Trajectory Prediction Probabilistic Forecasting
Automation and Control Group, Department of Electrical Engineering, Technical University of Denmark, Kgs. Lyngby, Denmark · Technical University of Denmark
Protocol before progress: leakage-aware evaluation of AIS trajectory prediction
Sep 22, 2026Zobeir Raisi, Vali Mohammad Nazarzehi HadData Leakage Domain Generalization
Marine Engineering Faculty, Chabahar Maritime University, Shahid Rigi Blvd., Chabahar, 99717778631, Iran
M3-Former: Multimodal Transformer with Mixture-of-Experts for Long-Term Vessel Trajectory Prediction
Sep 11, 2026Wenzhe Jin, Haina TangMixture of Experts Vessel Trajectory Prediction
School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
TempTPI: Informer-Based trajectory prediction for maritime vessels
Sep 9, 2026Kevin Ferneding, Veronika Lietavcova, Aleksandra M. Blachowiak +1Vessel Trajectory Prediction Maritime Transportation
Technical University of Denmark Anker Engelunds Vej 101 2800 Kongens Lyngby, Denmark
Mix&Fix-Net: A Dual-Stage Trajectory Prediction Model for AIS and Vision-Derived Vessel Data
Aug 20, 2026Md Mahmuddun Nabi Murad, Bora San Turgut, Yasin YilmazVessel Trajectory Prediction
Department of Electrical Engineering, University of South Florida, Tampa, FL, 33647, USA · College of Transportation and Logistics, Istanbul University, Istanbul, Turkey
Non-Parametric Spatiotemporal Trajectory Prediction via State-Conditioned Transition Sampling
Aug 14, 2026Michael Fore, Akshay Jain, Justin Downes +2Trajectory Generation Vessel Trajectory Prediction
Amazon Web Services
CRHT: A Continuous Regression Hybrid Transformer for Vessel Trajectory Prediction with Online Cluster Sampling
Aug 10, 2026Alexander Schiøtz, Bertram Hage, Christian Rand +2Hybrid CNN-Transformer Architectures Maritime Surveillance
Technical University of Denmark Anker Engelunds Vej 101 2800 Kongens Lyngby, Denmark
Context-Informed Ship Trajectory Prediction via Conditional Attention
Jul 29, 2026Yuan Guan, Chandler Squires, Timothy Hu +1Cross-Attention Vessel Trajectory Prediction
Machine Learning Department, Carnegie Mellon University · Advanced Technology Laboratories Lockheed Martin
NaviAIS: A Scenario-Level Vessel Trajectory Prediction Dataset withVectorized Lane Priors and the NaviLane Forecasting Framework
Jul 21, 2026Yuan Gui, Hongchen Luo, Liqi Qu +2Vessel Trajectory Prediction Multimodal Trajectory Prediction
Northeastern University, Shenyang 110819, China
Vessel Trajectory Prediction using COLREGs-aware Optimal Planning
Jul 17, 2026David Kaikkonen, Fredrik Ljungberg, Erik FriskTrajectory Prediction Trajectory Generation
ABB Corporate Research, Västerås, Sweden · Department of Electrical Engineering, Linköping University, Sweden
EnvShip-Bench: An Environment-Enhanced Benchmark for Short-Term Vessel Trajectory Prediction
Jun 13, 2026Kun Ma, Qilong Han, Chengjing Song +3Forecasting Benchmarks Vessel Trajectory Prediction
Harbin Engineering University Harbin, China · Politecnico di Torino Turin, Italy · Institute of Software, Chinese Academy of Sciences Beijing, China
HARBOR: Heading Analysis and Reconstruction from Behavioral Observation and Radar
Jun 12, 2026Joao P. A. Dantas, Paulo F. Silva Filho, Jelton A. Cunha +1Remote Sensing Image Understanding Maritime Surveillance
Institute for Advanced Studies, São José dos Campos, São Paulo, Brazil
Towards Long-Horizon Vessel Trajectory and Destination Forecasting with Reasoning Large Language Models
Jun 7, 2026Hongwei Wang, Miao Zhou, Fengde Wang +10RL for Language Models Vessel Trajectory Prediction
Institute of High Performance Computing (IHPC), A*STAR, Singapore 138632, Singapore. · The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, Shanghai 201804, China. · Meituan Inc., Shenzhen, China. +3
Function-Space Priors for Bayesian Neural ODEs with Application to Vessel Trajectory Prediction
Jun 4, 2026Jaeyeong Lee, Wonmo Koo, Heeyoung KimBayesian Neural Networks Probabilistic Forecasting
aDepartment of Industrial and Systems Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
AIS-Based Vessel Trajectory Prediction Using Memory-Augmented Neural Networks
Jun 4, 2026Wonmo Koo, Sanha Chang, Heeyoung KimMemory-Augmented Neural Networks Vessel Trajectory Prediction
Department of Industrial and Systems Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
CmIVTP: Cross-modal Interaction-based Vessel Trajectory Prediction for Maritime Intelligence
May 26, 2026Yuxu Lu, Dong Yang, Xiaoyu Li +2Intelligent Transportation Systems Vessel Trajectory Prediction
Department of Logistics and Maritime Studies, the Hong Kong Polytechnic University, Hong Kong 999077 · Department of Logistics and Maritime Studies and the Research Centre for ESG Advancement (RCESGA), the Hong Kong Polytechnic University, Hong Kong 999077 · Department of Logistics and Maritime Studies, the Hong Kong Polytechnic University, Hong Kong 999077, and also with the School of Navigation, Wuhan University of Technology, Wuhan 430063
A Retrieval-Enhanced Transformer for Multi-Step Port-of-Call Sequence Prediction in Global Liner Shipping
May 15, 2026Yanzhao Su, Fang He, Yineng WangTransformer Vessel Trajectory Prediction
Department of Industrial Engineering, Tsinghua University, Beijing 100084, P.R. China · Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hong Kong
Hierarchical Two-Stage Framework for Environment-Aware Long-Horizon Vessel Trajectory Prediction
May 15, 2026Ganeshaaraj Gnanavel, Tharindu Fernando, Sridha Sridharan +1Vessel Trajectory Prediction Maritime Navigation
SAIVT Research Group, Queensland University of Technology, Brisbane, QLD 4000, Australia
Towards Explainable Deep Learning for Ship Trajectory Prediction in Inland Waterways
Mar 4, 2026Tom Legel, Dirk Söffker, Roland Schätzle +1Vessel Trajectory Prediction Multi-Agent Trajectory Prediction
Department Hydraulic Engineering in Inland Areas, Federal Waterways Engineering and Research Institute, Germany · Chair of Dynamics and Control, University of Duisburg-Essen, Germany · Department of Technology (Computer Science), Baden-Wuerttemberg Cooperative State University, Germany +1
ShipTraj-R1: Reinforcing Ship Trajectory Prediction in Large Language Models via Group Relative Policy Optimization
Mar 3, 2026Yang Zhan, Yunhao Li, Zhang Chao +2Vessel Trajectory Prediction Trajectory Prediction
School of Artificial Intelligence, Optics, and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an 710072, China · Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hong Kong 999077, China · State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
SpecFuse: A Spectral-Temporal Fusion Predictive Control Framework for UAV Landing on Oscillating Marine Platforms
Feb 17, 2026Haichao Liu, Yufeng Hu, Shuang Wang +3UAV Landing on Moving Platforms Aerial Robotics
The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511453, China · The Hong Kong University of Science and Technology, Hong Kong SAR, China

Oct 9, 2026J/K move · Enter open · S save

Probabilistic Ship Trajectory Forecasting using Transformer Models on AIS Data

Frederik E. T. Schöller

Automation and Control Group, Department of Electrical Engineering, Technical University of Denmark, Kgs. Lyngby, Denmark · Technical University of Denmark

Vessel Trajectory Prediction Probabilistic Forecasting Maritime Navigation Multi-Agent Trajectory Prediction Time Series Transformers

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Anticipation of vessel trajectories is an essential task when navigating at sea. This applies to both human navigators and autonomous surface vessels. Trajectory forecasting enables sub-routines such as collision avoidance to assess the situation and react accordingly in time. This paper investigates Transformer and Performer models for trajectory prediction of surface vessels in confined waters. Using widely available position data from the Automatic Identification System (AIS), candidate models are trained and evaluated. Historical information on how other vessels have moved in the local area surrounding each agent is conveyed using positional heat maps. The heat maps are generated using Kernel Density Estimation (KDE) and encoded with a Convolutional Neural Network (CNN) before entering the Transformer models. The models are trained with quantile loss to efficiently obtain a model-aware prediction interval, as this is crucial for timely collision avoidance. The proposed model architectures are shown to greatly outperform previous work while the inclusion of local heat maps enables the prediction of vessel movement that is not otherwise indicated from the previous positions.