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...

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Vydáno v:	IEEE access Ročník 12; s. 132159 - 132174
Hlavní autoři:	Sharma, Sushil, Das, Arindam, Sistu, Ganesh, Halton, Mark, Eising, Ciaran
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Piscataway IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	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
On-line přístup:	Získat plný text
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