Crash severity analysis of vulnerable road users using machine learning.
Road crash fatality is a universal problem of the transportation system. A massive death toll caused annually due to road crash incidents, and among them, vulnerable road users (VRU) are endangered with high crash severity. This paper focuses on employing machine learning-based classification approa...
Guardado en:
Autores principales: | Md Mostafizur Rahman Komol, Md Mahmudul Hasan, Mohammed Elhenawy, Shamsunnahar Yasmin, Mahmoud Masoud, Andry Rakotonirainy |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Public Library of Science (PLoS)
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/90ed1fcca3d44135a108770cb903001d |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
The effectiveness of the AEB system in the context of the safety of vulnerable road users
por: Ucińska Monika, et al.
Publicado: (2021) -
Education for Road Safety: What is the State of Affairs in Three Groups of Vulnerable Road Users in Spain?
por: Francisco Alonso, et al.
Publicado: (2021) -
Crash Injury Severity Prediction Using an Ordinal Classification Machine Learning Approach
por: Shengxue Zhu, et al.
Publicado: (2021) -
Comparison of physical and psychological health outcomes for motorcyclists and other road users after land transport crashes: an inception cohort study
por: Lisa N. Sharwood, et al.
Publicado: (2021) -
Crash and disengagement data of autonomous vehicles on public roads in California
por: Amolika Sinha, et al.
Publicado: (2021)