Driving Behavior Classification Based on Oversampled Signals of Smartphone Embedded Sensors Using an Optimized Stacked-LSTM Neural Networks

Driving Behavior Classification Based on Oversampled Signals of Smartphone Embedded Sensors Using an Optimized Stacked-LSTM Neural Networks

Driving behavior classification is an essential real-world requirement in different contexts. In traffic safety, avoiding traffic accidents by taking corrective actions against aggressive behaviors is necessary to protect drivers. Similarly, in the automotive insurance industry, distinguishing betwe...

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Bibliographic Details
Main Authors: Moayed A. Khodairy, Gibrael Abosamra
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Driving behavior classification
deep learning
stacked-LSTM
smartphone embedded sensors
driving safety
signal upsampling
Online Access:https://ieeexplore.ieee.org/document/9312195/

Internet

https://ieeexplore.ieee.org/document/9312195/

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