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...
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| creator | Han, Shuo Xu, Jinliang Yan, Menghua Gao, Sunjian Li, Xufeng Huang, Xunjiang Liu, Zhaoxin |
| 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. |
| doi_str_mv | 10.1371/journal.pone.0252767 |
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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.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0252767</identifier><identifier>PMID: 34214083</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>China ; Crashes ; Drainage ; Drainage facilities ; Earth Sciences ; Engineering and Technology ; Environmental aspects ; Experiments ; Field tests ; Floods ; Friction ; Highway safety ; Humans ; Influence ; Management ; Measurement ; Medicine and Health Sciences ; Models, Theoretical ; Physical Sciences ; Prediction models ; Rain ; Rain and rainfall ; Rainfall ; Rainfall intensity ; Regression analysis ; Research and Analysis Methods ; Research methodology ; Roads ; Roads & highways ; Simulation ; Structure ; Traffic accidents & safety ; Traffic safety ; Transportation planning ; Water ; Water depth ; Water film</subject><ispartof>PloS one, 2021-07, Vol.16 (7), p.e0252767</ispartof><rights>COPYRIGHT 2021 Public Library of Science</rights><rights>2021 Han et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2021 Han et al 2021 Han et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-dbfb2644d32b054a77be8df4040434954fb0e1f381ad316b04f1552ef39c50343</citedby><cites>FETCH-LOGICAL-c692t-dbfb2644d32b054a77be8df4040434954fb0e1f381ad316b04f1552ef39c50343</cites><orcidid>0000-0002-3817-2487</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8253438/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8253438/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34214083$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Mosa, Ahmed Mancy</contributor><creatorcontrib>Han, Shuo</creatorcontrib><creatorcontrib>Xu, Jinliang</creatorcontrib><creatorcontrib>Yan, Menghua</creatorcontrib><creatorcontrib>Gao, Sunjian</creatorcontrib><creatorcontrib>Li, Xufeng</creatorcontrib><creatorcontrib>Huang, Xunjiang</creatorcontrib><creatorcontrib>Liu, Zhaoxin</creatorcontrib><title>Predicting the water film depth: A model based on the geometric features of road and capacity of drainage facilities</title><title>PloS one</title><addtitle>PLoS One</addtitle><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.</description><subject>China</subject><subject>Crashes</subject><subject>Drainage</subject><subject>Drainage facilities</subject><subject>Earth Sciences</subject><subject>Engineering and Technology</subject><subject>Environmental aspects</subject><subject>Experiments</subject><subject>Field tests</subject><subject>Floods</subject><subject>Friction</subject><subject>Highway safety</subject><subject>Humans</subject><subject>Influence</subject><subject>Management</subject><subject>Measurement</subject><subject>Medicine and Health Sciences</subject><subject>Models, Theoretical</subject><subject>Physical Sciences</subject><subject>Prediction models</subject><subject>Rain</subject><subject>Rain and rainfall</subject><subject>Rainfall</subject><subject>Rainfall 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Mancy</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predicting the water film depth: A model based on the geometric features of road and capacity of drainage facilities</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2021-07-02</date><risdate>2021</risdate><volume>16</volume><issue>7</issue><spage>e0252767</spage><pages>e0252767-</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>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.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>34214083</pmid><doi>10.1371/journal.pone.0252767</doi><tpages>e0252767</tpages><orcidid>https://orcid.org/0000-0002-3817-2487</orcidid><oa>free_for_read</oa></addata></record> |
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| source | MEDLINE; DOAJ Directory of Open Access Journals; Public Library of Science (PLoS) Journals Open Access; EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | China Crashes Drainage Drainage facilities Earth Sciences Engineering and Technology Environmental aspects Experiments Field tests Floods Friction Highway safety Humans Influence Management Measurement Medicine and Health Sciences Models, Theoretical Physical Sciences Prediction models Rain Rain and rainfall Rainfall Rainfall intensity Regression analysis Research and Analysis Methods Research methodology Roads Roads & highways Simulation Structure Traffic accidents & safety Traffic safety Transportation planning Water Water depth Water film |
| title | Predicting the water film depth: A model based on the geometric features of road and capacity of drainage facilities |
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