Assessing Driving Risk Level: Harnessing Deep Learning Hybrid Model With Intercity Bus Naturalistic Driving Data

Assessing Driving Risk Level: Harnessing Deep Learning Hybrid Model With Intercity Bus Naturalistic Driving Data

Driving risk assessment is crucial for enhancing traffic safety, especially given the severe consequences of highway accidents. This study advances the field by developing a deep learning hybrid model for time series analysis to categorize driving risks into low, moderate, and high levels. By collec...

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Bibliographic Details
Main Authors: Wei-Hsun Lee, Che-Yu Chang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Driving risk assessment
high-risk driving level predictor
naturalistic driving data
deep learning hybrid model
static journey background information
Online Access:https://ieeexplore.ieee.org/document/10870206/
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https://ieeexplore.ieee.org/document/10870206/

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