BEVSeg2GTA: Joint Vehicle Segmentation and Graph Neural Networks for Ego Vehicle Trajectory Prediction in Bird's-Eye-View

Predicting the trajectory of the ego vehicle is a critical task for autonomous vehicles. Even though traffic regulations have defined boundaries, various behaviors of the agents in real-life situations introduce complexities that are hard to capture comprehensively. This has led to a rising curiosit...

Full description

Saved in:

Bibliographic Details
Published in:	IEEE access Vol. 12; pp. 132159 - 132174
Main Authors:	Sharma, Sushil, Das, Arindam, Sistu, Ganesh, Halton, Mark, Eising, Ciaran
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Accuracy Algorithms Autonomous vehicles Bird’s-Eye-View Cameras encoder-decoder transformer Encoders-Decoders Encoding Feature extraction graph neural network Graph neural networks Image segmentation Multi-view camera Neural networks Pedestrians Perception Predictions Probabilistic logic Semantic segmentation Spatial temporal resolution spatio-temporal probabilistic network State-of-the-art reviews Task complexity Trajectory trajectory prediction Transformers Vehicles
ISSN:	2169-3536, 2169-3536
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!