Context-Aware Attention Encoder-Decoder Network for Connected Heavy-Duty Vehicle Aggressive Driving Identification Under Naturalistic Driving Conditions

Driving behavior analysis and identification are of great significance for improving traffic safety and reducing fuel consumption. Existing methods primarily focused on the driving behavior of light-duty vehicles based on analysis methods using simulation or questionnaire data, while heavy-duty vehi...

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Bibliographic Details

Published in:	IEEE transactions on intelligent transportation systems Vol. 25; no. 8; pp. 9710 - 9722
Main Authors:	Tang, Kun, Yang, Li, Ma, Yongfeng, Guo, Tangyi, He, Fang
Format:	Journal Article
Language:	English
Published:	IEEE 01.08.2024
Subjects:	attention mechanism Computational modeling Connected vehicles context-aware Data models Deep learning Driving behavior heavy-duty vehicle Safety Sensors Vehicle dynamics
ISSN:	1524-9050, 1558-0016
Online Access:	Get full text
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