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document type:
congress contribution (original) 
title:
Towards Feature Validation in Time to Lane Change Classification using Deep Neural Networks 
authors:
De Candido, Oliver; Koller, Michael; Gallitz, Oliver; Melz, Ron; Botsch, Michael; Utschick, Wolfgang 
congress title:
The 23rd IEEE International Conference on Intelligent Transportation Systems 
year:
2020 
abstract:
In this paper, we explore different Convolutional Neural Network (CNN) architectures to extract features in a Time to Lane Change (TTLC) classification problem for highway driving functions. These networks are trained using the HighD dataset, a public dataset of realistic driving on German highways. The investigated CNNs achieve approximately the same test accuracy which, at first glance, seems to suggest that all of the algorithms extract features of equal quality. We argue however that the tes...    »
 
remarks:
To be published. 
TUM-institution:
Professur für Methoden der Signalverarbeitung 
ingested:
08.03.2020 
format:
text