Using naturalistic driving data to identify driving style based on longitudinal driving operation conditions

Using naturalistic driving data to identify driving style based on longitudinal driving operation conditions

Purpose – An individual’s driving style significantly affects overall traffic safety. However, driving style is difficult to identify due to temporal and spatial differences and scene heterogeneity of driving behavior data. As such, the study of real-time driving-style identification methods is of g...

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Bibliographic Details
Main Authors: Nengchao Lyu, Yugang Wang, Chaozhong Wu, Lingfeng Peng, Alieu Freddie Thomas
Format: Article
Language:English
Published: Tsinghua University Press 2022-02-01
Series:Journal of Intelligent and Connected Vehicles
Subjects:
machine learning
advanced driver assistant systems
driver behaviors and assistance
sensor data processing
Online Access:https://www.emerald.com/insight/content/doi/10.1108/JICV-07-2021-0008/full/pdf?title=using-naturalistic-driving-data-to-identify-driving-style-based-on-longitudinal-driving-operation-conditions

Internet

https://www.emerald.com/insight/content/doi/10.1108/JICV-07-2021-0008/full/pdf?title=using-naturalistic-driving-data-to-identify-driving-style-based-on-longitudinal-driving-operation-conditions

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