VT-Former: An Exploratory Study on Vehicle Trajectory Prediction for Highway Surveillance through Graph Isomorphism and Transformer

AD Pazho, GA Noghre, V Katariya… - Proceedings of the …, 2024 - openaccess.thecvf.com
Enhancing roadway safety has become an essential computer vision focus area for
Intelligent Transportation Systems (ITS). As a part of ITS Vehicle Trajectory Prediction (VTP) …

VT-Former: A Transformer-based Vehicle Trajectory Prediction Approach For Intelligent Highway Transportation Systems

AD Pazho, V Katariya, GA Noghre, H Tabkhi - arXiv preprint arXiv …, 2023 - arxiv.org
Enhancing roadway safety and traffic management has become an essential focus area for
a broad range of modern cyber-physical systems and intelligent transportation systems …

Interactive Vehicle Trajectory Prediction for Highways Based on a Graph Attention Mechanism

Z Song, Y Qian - World Electric Vehicle Journal, 2024 - mdpi.com
Precise trajectory prediction is pivotal for autonomous vehicles operating in real-world traffic
conditions, and can help them make the right decisions to ensure safety on the road …

LSTM-based graph attention network for vehicle trajectory prediction

J Wang, K Liu, H Li - Computer Networks, 2024 - Elsevier
Abstract Vehicle Trajectory Prediction (VTP) is one of the key technologies for autonomous
driving, which can improve the safety and collaboration of the autonomous driving system …

Spatio-temporal interactive graph convolution network for vehicle trajectory prediction

G Shen, P Li, Z Chen, Y Yang, X Kong - Internet of Things, 2023 - Elsevier
Vehicle trajectory prediction is crucial in achieving safe and reliable autonomous driving
decision-making. The accuracy of the prediction is affected by many different factors, such as …

Vehicle Interactive Dynamic Graph Neural Network Based Trajectory Prediction for Internet of Vehicles

M Yang, H Zhu, T Wang, J Cai, X Weng… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
In the context of the booming Internet of Vehicles, predicting vehicle trajectories is crucial for
intelligent transportation systems. Existing methods, reliant on sensor data and behavior …

Efficient Context-Aware Graph Transformer for Vehicle Motion Prediction

C Gómez-Huélamo, MV Conde… - 2023 IEEE 26th …, 2023 - ieeexplore.ieee.org
Motion Prediction (MP) of multiple surrounding agents, and accurate trajectory forecasting, is
a crucial task for self-driving vehicles and robots. Current techniques tackle this problem …

Interaction-aware personalized vehicle trajectory prediction using temporal graph neural networks

A Abdelraouf, R Gupta, K Han - 2023 IEEE 26th International …, 2023 - ieeexplore.ieee.org
Accurate prediction of vehicle trajectories is vital for advanced driver assistance systems and
autonomous vehicles. Existing methods mainly rely on generic trajectory predictions derived …

Attention-aware Social Graph Transformer Networks for Stochastic Trajectory Prediction

Y Liu, B Li, X Wang, C Sammut… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Trajectory prediction is fundamental to various intelligent technologies, such as autonomous
driving and robotics. The motion prediction of pedestrians and vehicles helps emergency …

Scout: Socially-consistent and understandable graph attention network for trajectory prediction of vehicles and vrus

S Carrasco, DF Llorca, MA Sotelo - 2021 IEEE Intelligent …, 2021 - ieeexplore.ieee.org
Autonomous vehicles navigate in dynamically changing environments under a wide variety
of conditions, being continuously influenced by surrounding objects. Mod-elling interactions …