Multimodal Feature-Assisted Continuous Driver Behavior Analysis and Solving for Edge-Enabled Internet of Connected Vehicles Using Deep Learning

The emerging technology of internet of connected vehicles (IoCV) introduced many new solutions for accident prevention and traffic safety by monitoring the behavior of drivers. In addition, monitoring drivers’ behavior to reduce accidents has attracted considerable attention from industry and academ...

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Detalles Bibliográficos
Autores principales:	Omar Aboulola, Mashael Khayyat, Basma Al-Harbi, Mohammed Saleh Ali Muthanna, Ammar Muthanna, Heba Fasihuddin, Majid H. Alsulami
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	internet of connected vehicles (IoCV) edge node driver behavior analysis hidden Markov model (HMM) tri-agent-based soft actor critic (TA-SAC) recommendations Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/5378b03b131c4edfb2640a1a5733a15a
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Multimodal Feature-Assisted Continuous Driver Behavior Analysis and Solving for Edge-Enabled Internet of Connected Vehicles Using Deep Learning

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