Improve Aggressive Driver Recognition Using Collision Surrogate Measurement and Imbalanced Class Boosting

Real-time recognition of risky driving behavior and aggressive drivers is a promising research domain, thanks to powerful machine learning algorithms and the big data provided by in-vehicle and roadside sensors. However, since the occurrence of aggressive drivers in real traffic is infrequent, most...

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Detalles Bibliográficos
Autores principales: Wang, Ke, Xue, Qingwen, Xing, Yingying, Li, Chongyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7177658/
https://www.ncbi.nlm.nih.gov/pubmed/32244469
http://dx.doi.org/10.3390/ijerph17072375

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7177658/
https://www.ncbi.nlm.nih.gov/pubmed/32244469
http://dx.doi.org/10.3390/ijerph17072375

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