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雷达事件检测技术在公路交通管理中的应用 被引量:1

Application of Radar Event Detection Technology in Highway Traffic Control
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摘要 高速公路和城市快速路是承担我国公路运输和城市道路运输的主要道路,具有车速快、流量大等许多特点,一旦发生突发交通事件,极易引发交通事故,严重影响道路的通行能力和运营效率。在日常的交通运行和交通管理中,如果仅仅依靠人工报告,电视监视等非自动检测方法发现交通事件,不但浪费大量的资源,而且不全面及时,给交通安全带来了隐患。因此,交通事件自动检测技术越发成为智能交通的研究热点,旨在第一时间快速发现交通事件的地点,利于及时处理交通事件。介绍了雷达事件检测技术在公路交通管理中的应用。 Highway and city expressway are the main ways of road transportation and urban road transportation,with characteristics like high- speeding and large- flowing. Once traffic emergency happened,it is likely to trigger traffic accident and influence traffic capacity and circulation efficiency. In daily traffic circulation and control,merely depending on non- automatic detection method such as labor reporting and video surveillance to find traffic incident,is not only a waste of large amounts of resources,but also a hidden danger for incomplete or late. Therefore,traffic incident automatic measurement technology increasingly become a research hotspot in intelligent transportation system,aiming at finding the site of traffic incident at the first time and solve it in time.This paper introduces the application of radar event detection technology in highway traffic control.
作者 张彤
出处 《北方交通》 2015年第4期111-115,共5页 Northern Communications
关键词 高速公路 智能交通 事件检测 雷达检测 公路管理 Highway Intelligent transportation system Event detection Radar detection Highway control
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  • 1杨绪兵,陈松灿.增强的主分量分类器[J].复旦学报(自然科学版),2004,43(5):769-772. 被引量:2
  • 2姜桂艳,温慧敏,杨兆升.高速公路交通事件自动检测系统与算法设计[J].交通运输工程学报,2001,1(1):77-81. 被引量:67
  • 3韩自存,杨绪兵.模糊主分量分类器[J].安徽工程科技学院学报(自然科学版),2007,22(1):45-50. 被引量:1
  • 4Hu W J, Song Q.Principle component classifier[EB/OL]. (2004-02-12 ) .http ://svm.first.gmd.de./.
  • 5Tong Hanghang,Li Chongrong,He Jingrui,et al.Anomaly internet network traffic detection by kernel principle component classifier[C]//Lecture Notes in Computer Science, 2005,3498: 476-481.
  • 6Yuan F, Cheu R L.Incident detection using support vector machines[J].Transportation Research Part C, 2003,11 : 309-328.
  • 7Chen Shuyan, Wang Wei, Qu Gaofeng.Traffic incident detection based on rough sets approach[C]//2007 International Conference on Machine Learning and Cybernetics,2007,7.
  • 8Payne H J,Helfenbein E D,Knobel H C.Development and testing of incident detection algorithms:volume 2-research methodology and detailed results[Z].Deport No.FHWA-RD-76-20 Federal Highway Administration,1976.
  • 9Perasnd B,Hall F L.Catastrophe theory and pattern in 30-second free-way traffic data implication for incident detection[J].Transportation Research 23A,1989,(2).
  • 10Chassiakos A P,Stephanedes Y J.Smoothing algorithms for incident detection[J].Transportation Research Record 1394,1993.

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