Conditional Variational Autoencoder Networks for Autonomous Vehicle Path Prediction

Mobility of autonomous vehicles is a challenging task to implement. Under the given traffic circumstances, all agent vehicles’ behavior is to be understood and their paths for a short future needs to be predicted to decide upon the maneuver of the ego vehicle. We explore variational autoencoder netw...

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Veröffentlicht in:	Neural processing letters Jg. 54; H. 5; S. 3965 - 3978
Hauptverfasser:	Jagadish, D. N., Chauhan, Arun, Mahto, Lakshman
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.10.2022 Springer Nature B.V
Schlagworte:	Artificial Intelligence Complex Systems Computational Intelligence Computer Science Networks Neural networks Path predictors Semantics Sensors Traffic control Traffic flow Vehicles Conditional variational autoencoder Deep learning Autonomous vehicle path
ISSN:	1370-4621, 1573-773X
Online-Zugang:	Volltext
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