Lightweight Driver Behavior Identification Model with Sparse Learning on In-Vehicle CAN-BUS Sensor Data

This study focuses on driver-behavior identification and its application to finding embedded solutions in a connected car environment. We present a lightweight, end-to-end deep-learning framework for performing driver-behavior identification using in-vehicle controller area network (CAN-BUS) sensor...

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Detalles Bibliográficos
Autores principales: Ullah, Shan, Kim, Deok-Hwan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7570946/
https://www.ncbi.nlm.nih.gov/pubmed/32899751
http://dx.doi.org/10.3390/s20185030

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7570946/
https://www.ncbi.nlm.nih.gov/pubmed/32899751
http://dx.doi.org/10.3390/s20185030

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