Predicting the water film depth: A model based on the geometric features of road and capacity of drainage facilities.

The water film depth is a key variable that affects traffic safety under rainfall conditions. According to the Federal Highway Administration, approximately 5700 people are killed and more than 544 700 people are injured in crashes on wet pavements annually. While several studies have attempted to a...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Shuo Han, Jinliang Xu, Menghua Yan, Sunjian Gao, Xufeng Li, Xunjiang Huang, Zhaoxin Liu
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/61a17616046f45d8a53e5668515137af
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:61a17616046f45d8a53e5668515137af
record_format	dspace
spelling	oai:doaj.org-article:61a17616046f45d8a53e5668515137af2021-12-02T20:05:14ZPredicting the water film depth: A model based on the geometric features of road and capacity of drainage facilities.1932-620310.1371/journal.pone.0252767https://doaj.org/article/61a17616046f45d8a53e5668515137af2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0252767https://doaj.org/toc/1932-6203The water film depth is a key variable that affects traffic safety under rainfall conditions. According to the Federal Highway Administration, approximately 5700 people are killed and more than 544 700 people are injured in crashes on wet pavements annually. While several studies have attempted to address water film depth issues by establishing prediction models, a few focused on the relationship among road geometric features, capacity of drainage facilities and water film depth. To ascertain the influence of the geometric features of road and facility drainage capacities on the water film depth, the road geometry features were first classified into four types, and the facility drainage capacities were considered from three aspects in this study. Furthermore, the concept of short-time rainfall grade was proposed according to the results of the field test. Finally, the theoretical prediction model for the water film depth was conceived, based on the geometric features of road and facility drainage capacities with different rainfall intensities. Compared with the traditional regression prediction models, the theoretical prediction model clearly shows the effects of the geometric features of road and facility drainage capacities. When the road drainage facilities have no drainage capacity, the water film depth increases rapidly with the rainfall intensity. This model can be used to predict the water film depth of road surfaces on rainy days, evaluate the effect of rainfall on the driving environment, and provide guidance for determining safety control measures on rainy days.Shuo HanJinliang XuMenghua YanSunjian GaoXufeng LiXunjiang HuangZhaoxin LiuPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 7, p e0252767 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Shuo Han Jinliang Xu Menghua Yan Sunjian Gao Xufeng Li Xunjiang Huang Zhaoxin Liu Predicting the water film depth: A model based on the geometric features of road and capacity of drainage facilities.
description	The water film depth is a key variable that affects traffic safety under rainfall conditions. According to the Federal Highway Administration, approximately 5700 people are killed and more than 544 700 people are injured in crashes on wet pavements annually. While several studies have attempted to address water film depth issues by establishing prediction models, a few focused on the relationship among road geometric features, capacity of drainage facilities and water film depth. To ascertain the influence of the geometric features of road and facility drainage capacities on the water film depth, the road geometry features were first classified into four types, and the facility drainage capacities were considered from three aspects in this study. Furthermore, the concept of short-time rainfall grade was proposed according to the results of the field test. Finally, the theoretical prediction model for the water film depth was conceived, based on the geometric features of road and facility drainage capacities with different rainfall intensities. Compared with the traditional regression prediction models, the theoretical prediction model clearly shows the effects of the geometric features of road and facility drainage capacities. When the road drainage facilities have no drainage capacity, the water film depth increases rapidly with the rainfall intensity. This model can be used to predict the water film depth of road surfaces on rainy days, evaluate the effect of rainfall on the driving environment, and provide guidance for determining safety control measures on rainy days.
format	article
author	Shuo Han Jinliang Xu Menghua Yan Sunjian Gao Xufeng Li Xunjiang Huang Zhaoxin Liu
author_facet	Shuo Han Jinliang Xu Menghua Yan Sunjian Gao Xufeng Li Xunjiang Huang Zhaoxin Liu
author_sort	Shuo Han
title	Predicting the water film depth: A model based on the geometric features of road and capacity of drainage facilities.
title_short	Predicting the water film depth: A model based on the geometric features of road and capacity of drainage facilities.
title_full	Predicting the water film depth: A model based on the geometric features of road and capacity of drainage facilities.
title_fullStr	Predicting the water film depth: A model based on the geometric features of road and capacity of drainage facilities.
title_full_unstemmed	Predicting the water film depth: A model based on the geometric features of road and capacity of drainage facilities.
title_sort	predicting the water film depth: a model based on the geometric features of road and capacity of drainage facilities.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/61a17616046f45d8a53e5668515137af
work_keys_str_mv	AT shuohan predictingthewaterfilmdepthamodelbasedonthegeometricfeaturesofroadandcapacityofdrainagefacilities AT jinliangxu predictingthewaterfilmdepthamodelbasedonthegeometricfeaturesofroadandcapacityofdrainagefacilities AT menghuayan predictingthewaterfilmdepthamodelbasedonthegeometricfeaturesofroadandcapacityofdrainagefacilities AT sunjiangao predictingthewaterfilmdepthamodelbasedonthegeometricfeaturesofroadandcapacityofdrainagefacilities AT xufengli predictingthewaterfilmdepthamodelbasedonthegeometricfeaturesofroadandcapacityofdrainagefacilities AT xunjianghuang predictingthewaterfilmdepthamodelbasedonthegeometricfeaturesofroadandcapacityofdrainagefacilities AT zhaoxinliu predictingthewaterfilmdepthamodelbasedonthegeometricfeaturesofroadandcapacityofdrainagefacilities
_version_	1718375485565566976

Predicting the water film depth: A model based on the geometric features of road and capacity of drainage facilities.

Ejemplares similares