Pub Date : 2020-07-20DOI: 10.19721/J.CNKI.1001-7372.2020.07.003
He Rui, Wang Tong, Cheng Hua-xin, Xue Cheng, Bai Yong-hou
{"title":"Impact of Qinghai-Tibet Plateau's Climate on Strength and Permeability of Concrete","authors":"He Rui, Wang Tong, Cheng Hua-xin, Xue Cheng, Bai Yong-hou","doi":"10.19721/J.CNKI.1001-7372.2020.07.003","DOIUrl":"https://doi.org/10.19721/J.CNKI.1001-7372.2020.07.003","url":null,"abstract":"","PeriodicalId":35720,"journal":{"name":"中国公路学报","volume":"33 1","pages":"29"},"PeriodicalIF":0.0,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48765050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-20DOI: 10.19721/J.CNKI.1001-7372.2020.06.001
Zhang Xu-xin, Wang Xue-song, Ma Yong, MA Qing-bian
{"title":"International Research Progress on Driving Behavior and Driving Risks","authors":"Zhang Xu-xin, Wang Xue-song, Ma Yong, MA Qing-bian","doi":"10.19721/J.CNKI.1001-7372.2020.06.001","DOIUrl":"https://doi.org/10.19721/J.CNKI.1001-7372.2020.06.001","url":null,"abstract":"","PeriodicalId":35720,"journal":{"name":"中国公路学报","volume":" ","pages":"1"},"PeriodicalIF":0.0,"publicationDate":"2020-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44058492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-20DOI: 10.19721/J.CNKI.1001-7372.2020.06.008
Xue Qing-wen, Jiang Yu-ming, Lu Jian
{"title":"Risky Driving Behavior Recognition Based on Trajectory Data","authors":"Xue Qing-wen, Jiang Yu-ming, Lu Jian","doi":"10.19721/J.CNKI.1001-7372.2020.06.008","DOIUrl":"https://doi.org/10.19721/J.CNKI.1001-7372.2020.06.008","url":null,"abstract":"","PeriodicalId":35720,"journal":{"name":"中国公路学报","volume":"33 1","pages":"84"},"PeriodicalIF":0.0,"publicationDate":"2020-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44524160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-20DOI: 10.19721/J.CNKI.1001-7372.2020.05.014
WU Hua-yue, Zhao Xiangmo
{"title":"Multi-interference Lane Recognition Based on IPM and Edge Image Filtering","authors":"WU Hua-yue, Zhao Xiangmo","doi":"10.19721/J.CNKI.1001-7372.2020.05.014","DOIUrl":"https://doi.org/10.19721/J.CNKI.1001-7372.2020.05.014","url":null,"abstract":"","PeriodicalId":35720,"journal":{"name":"中国公路学报","volume":"33 1","pages":"153"},"PeriodicalIF":0.0,"publicationDate":"2020-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48409348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-04-20DOI: 10.19721/J.CNKI.1001-7372.2020.04.018
Guo Xiao-min, Liu Bi-jun, Long Jiang-yun, XU Hao-da, Lu Zhi
{"title":"Path Planning of Urban Autonomous Driving Using Laser Point Cloud Data","authors":"Guo Xiao-min, Liu Bi-jun, Long Jiang-yun, XU Hao-da, Lu Zhi","doi":"10.19721/J.CNKI.1001-7372.2020.04.018","DOIUrl":"https://doi.org/10.19721/J.CNKI.1001-7372.2020.04.018","url":null,"abstract":"","PeriodicalId":35720,"journal":{"name":"中国公路学报","volume":"33 1","pages":"182"},"PeriodicalIF":0.0,"publicationDate":"2020-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44875737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-03-20DOI: 10.19721/J.CNKI.1001-7372.2020.03.015
Zhao Xiangmo, Lian Xin-yu, Liu Zhanwen, Shen Chao, Dong Ming
{"title":"End-to-end Autonomous Driving-behavior Decision Model Based on MM-STConv","authors":"Zhao Xiangmo, Lian Xin-yu, Liu Zhanwen, Shen Chao, Dong Ming","doi":"10.19721/J.CNKI.1001-7372.2020.03.015","DOIUrl":"https://doi.org/10.19721/J.CNKI.1001-7372.2020.03.015","url":null,"abstract":"","PeriodicalId":35720,"journal":{"name":"中国公路学报","volume":"33 1","pages":"170"},"PeriodicalIF":0.0,"publicationDate":"2020-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45230334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-20DOI: 10.19721/J.CNKI.1001-7372.2020.01.018
Han Yong, XU Jia-shao, Shi Liang-liang, Gao Xiu-jing, Qian Yu-bin, Yang Zhen
{"title":"Uncertainty Analysis of Head Injury via Reconstruction of Electric Two-wheeler Accidents","authors":"Han Yong, XU Jia-shao, Shi Liang-liang, Gao Xiu-jing, Qian Yu-bin, Yang Zhen","doi":"10.19721/J.CNKI.1001-7372.2020.01.018","DOIUrl":"https://doi.org/10.19721/J.CNKI.1001-7372.2020.01.018","url":null,"abstract":"","PeriodicalId":35720,"journal":{"name":"中国公路学报","volume":"33 1","pages":"172"},"PeriodicalIF":0.0,"publicationDate":"2020-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45311705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The key technology of freeway accident detection was studied in order to set up a quick and efficient accident detection system and promote the efficiency of accident rescue. On the basis of characteristic analysis of the existing models, the freeway accident detection model based on support vector machine (SVM) theory was put forward. With database established by self-developed EAD-Simulations system, a simulation experiment was applied to the model. The effects of different kernel functions on detection performance were analyzed and the performance indexes, such as upstream input, upstream and downstream input and different input of features combination were studied. The results show that the excellent performances of the model are demonstrated by contrast with California model. The detection rate raises 179%; error detection rate drops at 0.50% and average detection time cuts down 81%. In addition, the optimal input characteristic combined by occupancy and flow rate in upstream is received.
{"title":"Freeway Accident Detection Model Based on Support Vector Machine","authors":"Baizhu Chen","doi":"10.1061/41184(419)512","DOIUrl":"https://doi.org/10.1061/41184(419)512","url":null,"abstract":"The key technology of freeway accident detection was studied in order to set up a quick and efficient accident detection system and promote the efficiency of accident rescue. On the basis of characteristic analysis of the existing models, the freeway accident detection model based on support vector machine (SVM) theory was put forward. With database established by self-developed EAD-Simulations system, a simulation experiment was applied to the model. The effects of different kernel functions on detection performance were analyzed and the performance indexes, such as upstream input, upstream and downstream input and different input of features combination were studied. The results show that the excellent performances of the model are demonstrated by contrast with California model. The detection rate raises 179%; error detection rate drops at 0.50% and average detection time cuts down 81%. In addition, the optimal input characteristic combined by occupancy and flow rate in upstream is received.","PeriodicalId":35720,"journal":{"name":"中国公路学报","volume":"19 1","pages":"107-112"},"PeriodicalIF":0.0,"publicationDate":"2011-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1061/41184(419)512","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"58575713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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