Investigation of different LSTM-based encoder-decoder neural networks for vehicle speed prediction

Abstract In this work, different Long Short-Term Memory (LSTM) encoder-decoder artificial neural networks are investigated. These networks differ in their complexity. The aim of this work is to evaluate whether complex networks are necessary for vehicle speed predictions or whether simple and less c...

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Bibliographic Details

Published in:	Scientific Reports
Main Authors:	Paul Heckelmann, Sandro Chris Breuer, Stephan Rinderknecht
Format:	Article
Language:	English
Published:	Nature Portfolio 2025-09-01
Subjects:	Long short-term memory Artificial neural networks Speed prediction Intelligent vehicles V2X Traffic simulation
Online Access:	https://doi.org/10.1038/s41598-025-19592-5