快速路交通事件自动检测算法的研究与实现
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摘要
随着城市快速交通迅猛发展,城市快速路路网结构日益复杂,交通事件也日益增多。由于快速路通行量大又有较高的稳定行驶车速,比普通的城市道路相对封闭,比城市间的高速公路流量大,一旦发生交通事件,如果不能得到及时的处理,就非常容易造成交通拥堵,因此准确、快速的判断交通事件的发生对整个快路网的畅通运行有着十分重要的现实意义。交通事件自动检测是高速公路/快速路智能交通管理系统的重要组成部分,提高事件自动检测算法性能可以显著改善事件管理系统的运行效果。本论文所依托的是北京市自然科学基金资助项目《北京快速路交通流模型与交通诱导关键技术研究》(8052016)的一个研究内容,同时也是北京四通智能交通系统集成有限公司项目《北京市快速路智能交通管理平台》的一个子模块。
文中阐述了国内外交通事件自动检测方法的研究现状,目前的事件自动检测算法各有侧重点,没有一种的性能完全优于其他算法。本文在分析了交通事件对交通流产生的影响的基础上,针对现有算法各种的优缺点,综合考虑发生交通事件时交通流数据在两维空间上、时间上的异常变化,提出了一种易于实际应用的三维集成事件自动检测算法。该算法设计思想是当交通事件发生时在横向维上考虑相邻车道间流量和速度的变化,在纵向维上考虑上下游断面占有率的变化,在时间维上考虑占有率在占有率-流量模型上的等级变化,然后集成结果报警。本文还详细介绍了其他子模块集成判断模块和参数更新模块的设计思想和工作步骤。
为验证算法,本文采用北京快速路实测交通流数据和事件信息对本文算法进行有效性分析和实用性分析,结果表明本文算法基本满足实际应用需要。最后在明确系统目标的基础上,利用Visual C++和oracle数据库实现了实际应用的算法软件。本文中涉及到的研究思路、研究方法是针对有固定检测器路段交通事件自动检测方法的一个探索,可以为交通事件自动检测算法提供一定的参考。
With the rapid development of urban rapid transport, urban road network structure becomes more complex and traffic incidents also become much more. Because there is a lot of high-speed traffic on urban freeway, which is more closed than ordinary urban road and more crowded than inter-city freeway, urban freeway will congest heavily if the incidents can't be cleaned in time. So an accurate, rapid detection of the happening of traffic incidents has a very important practical significance to the unobstructed network. Traffic automatic incident detection (AID) is an important part of freeway emergency management system, and high-performance automatic incident detection algorithm can significantly improve the system's effect. The thesis stems from a research content of Beijing Natural Science Foundation-funded projects named as "Research on Traffic Flow Model and Key Technologies of Traffic Guidance for Beijing Urban Freeways" (8052016) and also is a sub-project of "intelligent traffic management system in Beijing" which is a project from Beijing STONE Intelligent Transportation System Integration CO., LTD.
After an extensive literature review of existing AID techniques, the paper introduces the key points of existing algorithms and finds there is not an absolute perfect algorithm. On the basis of the analysis of traffic incidents' impact and according to the temporal and the two-dimensional spatial abnormal variability of traffic flow as a result of traffic incidents, the paper proposes an easily applicative AID algorithm based on 3D integration. The design idea is that when a traffic incident happens, the algorithm integrates the change of volume and speed of adjacent lanes in the horizontal dimension, the change of occupancy of upstream and downstream section in the vertical dimension and the change of occupancy levels of the flow-occupancy model in the temporal dimension to alarm incidents. The paper also describes design ideas and working procedures of integrated judgment module and parameters update module in the details.
Then in order to verify the algorithm, the paper analyses the validity and practicability of the algorithm with the detector data from Beijing freeway, and the result shows the integrated algorithm can meet basic needs of practical application. And on the basis of the clear system objective, the paper uses the Visual C++ and Oracle technology to program an applicative software. The research ideas and the algorithm proposed in this paper is a method exploration of traffic automatic incident detection algorithm of fixed detectors and may provide certain theoretical reference.
文中阐述了国内外交通事件自动检测方法的研究现状,目前的事件自动检测算法各有侧重点,没有一种的性能完全优于其他算法。本文在分析了交通事件对交通流产生的影响的基础上,针对现有算法各种的优缺点,综合考虑发生交通事件时交通流数据在两维空间上、时间上的异常变化,提出了一种易于实际应用的三维集成事件自动检测算法。该算法设计思想是当交通事件发生时在横向维上考虑相邻车道间流量和速度的变化,在纵向维上考虑上下游断面占有率的变化,在时间维上考虑占有率在占有率-流量模型上的等级变化,然后集成结果报警。本文还详细介绍了其他子模块集成判断模块和参数更新模块的设计思想和工作步骤。
为验证算法,本文采用北京快速路实测交通流数据和事件信息对本文算法进行有效性分析和实用性分析,结果表明本文算法基本满足实际应用需要。最后在明确系统目标的基础上,利用Visual C++和oracle数据库实现了实际应用的算法软件。本文中涉及到的研究思路、研究方法是针对有固定检测器路段交通事件自动检测方法的一个探索,可以为交通事件自动检测算法提供一定的参考。
With the rapid development of urban rapid transport, urban road network structure becomes more complex and traffic incidents also become much more. Because there is a lot of high-speed traffic on urban freeway, which is more closed than ordinary urban road and more crowded than inter-city freeway, urban freeway will congest heavily if the incidents can't be cleaned in time. So an accurate, rapid detection of the happening of traffic incidents has a very important practical significance to the unobstructed network. Traffic automatic incident detection (AID) is an important part of freeway emergency management system, and high-performance automatic incident detection algorithm can significantly improve the system's effect. The thesis stems from a research content of Beijing Natural Science Foundation-funded projects named as "Research on Traffic Flow Model and Key Technologies of Traffic Guidance for Beijing Urban Freeways" (8052016) and also is a sub-project of "intelligent traffic management system in Beijing" which is a project from Beijing STONE Intelligent Transportation System Integration CO., LTD.
After an extensive literature review of existing AID techniques, the paper introduces the key points of existing algorithms and finds there is not an absolute perfect algorithm. On the basis of the analysis of traffic incidents' impact and according to the temporal and the two-dimensional spatial abnormal variability of traffic flow as a result of traffic incidents, the paper proposes an easily applicative AID algorithm based on 3D integration. The design idea is that when a traffic incident happens, the algorithm integrates the change of volume and speed of adjacent lanes in the horizontal dimension, the change of occupancy of upstream and downstream section in the vertical dimension and the change of occupancy levels of the flow-occupancy model in the temporal dimension to alarm incidents. The paper also describes design ideas and working procedures of integrated judgment module and parameters update module in the details.
Then in order to verify the algorithm, the paper analyses the validity and practicability of the algorithm with the detector data from Beijing freeway, and the result shows the integrated algorithm can meet basic needs of practical application. And on the basis of the clear system objective, the paper uses the Visual C++ and Oracle technology to program an applicative software. The research ideas and the algorithm proposed in this paper is a method exploration of traffic automatic incident detection algorithm of fixed detectors and may provide certain theoretical reference.
引文
[1]李秀文,荣建等.快速路路段交通特性研究.道路交通与安全.2005.1.38-43
[2]郑建湖,陈洪.快速路交通事件自动检测系统及算法.计算机测量与控制.2006.14(9).1143-1145
[3]韩国华.高速公路交通事件管理系统关键技术研究[学位论文].吉林.吉林大学.2005.2-4
[4]张敬磊,王晓原.交通事件检测算法研究进展.武汉理工大学学报.2005.29(2).215-218
[5]代磊磊.高速公路事件自动检测算法综述.ITS通讯.2004.6(3).1-5
[6]C.L.Dudek,C.J.Messer,and N.B.Nuckles.Incident Detection on Urban Freeways.TRB.Transportation Research Record.Washington D C:TRB,1974:12-24
[7]Karl F.Petty,Michael Ostland et al.A New Methodology for Evaluating Incident Detection Algorithms.Transportation Research Part C:Emerging Technologies.2002,10(3).189-204.
[8]Persaud,B.N.,and Hall,F.L.Catastrophe Theory and Patterns in 30-second Freeway Traffic Data-Implication for incident detection.Transportation Research Part A.1990:23(2).103-113.
[9]P G Michalopoulos.Vehicle Detection Video Through Image Processing:The Autoscore System.IEEE Trans.on Vehicular Technology.1991.40(1).21-29.
[10]徐学才.高速公路事件管理系统设计及算法实现[学位论文].四川.西南交通大学.2004.3-4
[11]张彬彬.高速公路交通事件检测算法及检测器布设方案研究[学位论文].吉林.吉林大学.2005.4-5
[12]张洋.高速公路交通事件检测与管理系统研究[学位论文].北京.北京航天航空大学.2002.8-9
[13]王彦卿.交通异常门限值的探讨.公路交通科技.1900.7(18).51-56
[14]李文江,荆便顺.基于小波分析的事件检测算法.西安公路交通大学学报.1997.17(28).134-138
[15]周伟,罗石贵.基于模糊综合识别的事件检测算法.西安公路交通大学学报.2001.21(2).70-73
[16]郭恒明,张鹏飞.基于环形线圈的城市道路段交通异常自动检测方法研究.上海公路.2001.(4).31-34
[17]吕琪,王慧.基于动态神经网络模型的交通事件检测算法.公路交通科技.2003.20(6).105-108
[18]高海龙,张北海.高速公路紧急事件管理系统的开发.ITS通讯.2001.1(42).43-47
[19]彭春露,彭国雄.城市道路交通异常事件管理系统设计.交通运输系统工程与信息.2002.2(3).18-21
[20]张秀媛,达庆东.公路自动事件检测技术.系统工程理论与实践.2001.21(6).118-124
[21]孟建军.基于动态交通模型和多信息融合的高速公路交通事件检测算法[学位论文].江苏.河海大学.2007.6-20
[22]陆化普.城市交通管理评价体系.第1版.北京.人民交通出版社.2003.35-36
[23]潘若禹.基于数据融合的高速公路交通异常事件检测的研究[学位论文].西安.长安大学.2006.5-27
[24]王小华.基于模糊算法的高速公路事件检测及主线控制系统的研究与实现[学位论文].江苏.河海大学.2003.8-42
[25]庞根明.城市道路交通事件自动检测方法研究[学位论文].吉林.吉林大学.2007.37-38
[26]赵祥模.高速公路监控系统理论及应用.第1版.北京.电子工业出版社.2003.31-36
[27]徐名海.交通事件自动检测与决策系统的研究[学位论文].湖南.长沙交通学院.2002.7-10
[28]Peter T.Martin,Joseph Perrin,Blake Hansen.Incident Detection Algorithm Evaluation.University of Utah.Utah Department of Transportation.2001.7-35
[29]谭光莉,姜紫峰.高速公路事故自动检测算法的研讨.西安公路交通大学学报.1999.19(3).57-77
[30]唐金芝.数据融合技术在高速公路交通事件检测中的应用[学位论文].吉林.吉林大学.2007.5-7
[31]Y.J Stephanedes,A.P Chassiakos.Application of Filtering Techniques for Incident Detection.Journal of Transportation Engineering.1993.119(1).13-26
[32]刘伟铭,王倩.基于小波包变换的交通事件检测.交通与计算机.2004.22(6).9-12
[33]杨耀华,李昕等.高速公路事件检测系统及算法.公路交通科技.2003.20(3).133-136
[34]Willsky,A Chow,et al.Dynamic Model-based Techniques for the Detection of Incident on Freeways.IEEE Trans.Automatic Control.1980.25(3).347-360
[35]吕琪.基于动态神经网络模型的交通事件检测算法[学位论文].浙江.浙江大学.2007.17-25
[36]B Abdulhai and S.G Ritchie.Enhancing the University and Transferability of Freeway Incident Detection Using a Bayesian-based Neural Network.Transportation Research Part C.1996.7(5).261-280
[37]C.H Hsiao,C.T Lin and M.Cassidy.Application of Fuzzy Logic and Neural Networks to Automatically Detect Freeway Traffic Incident.Journal of Transportation Engineering.1994.125(5).753-772
[38]蔡志理.高速公路交通事件检测及交通疏导技术研究[学位论文].吉林.吉林大学.2007.13-14
[39]D.Srinivasan,R.L Cheu,et al.Development of an Intelligent Technique for Traffic Network Incident Detection.Engineering Application of Artificial Intelligence.2000.13(3).311-322
[40]陈德旺,关积珍等.基于占有率的交通流参数模型研究.交通运输系统工程与信息.2006.6(5).83-86
[41]张智星,孙春在等作.张平安等译.神经—模糊和软计算.第1版.西安.西安交通大学出版社.2006.89-117
[42]张志涌等.精通MATLAB6.5版.第1版.北京.北京航空航天大学出版社.2003.127-128
[43]张琨.快速路旅行时间预测算法研究[学位论文].北京北京交通大学.2007.26-53
[44]李世欣.基于集成模糊分类器的交通状态判别算法[学位论文].北京北京交通大学.2007.36-37
[45]Microsoft Corporation.对比SQL Server和Oracle..http://www.microsoft.com/china/sql/prodinfo/compare/oracle/default.mspx.2007-12-17
[46]启明工作室.Visual C++ +SQL Server数据库应用系统开发与实例.第1版.北京.人民邮电出版社.2004.109-143
[47]网冠科技.Visual C++6.0时尚编程百例.第1版.北京.机械工业出版社.2001.109-143
[2]郑建湖,陈洪.快速路交通事件自动检测系统及算法.计算机测量与控制.2006.14(9).1143-1145
[3]韩国华.高速公路交通事件管理系统关键技术研究[学位论文].吉林.吉林大学.2005.2-4
[4]张敬磊,王晓原.交通事件检测算法研究进展.武汉理工大学学报.2005.29(2).215-218
[5]代磊磊.高速公路事件自动检测算法综述.ITS通讯.2004.6(3).1-5
[6]C.L.Dudek,C.J.Messer,and N.B.Nuckles.Incident Detection on Urban Freeways.TRB.Transportation Research Record.Washington D C:TRB,1974:12-24
[7]Karl F.Petty,Michael Ostland et al.A New Methodology for Evaluating Incident Detection Algorithms.Transportation Research Part C:Emerging Technologies.2002,10(3).189-204.
[8]Persaud,B.N.,and Hall,F.L.Catastrophe Theory and Patterns in 30-second Freeway Traffic Data-Implication for incident detection.Transportation Research Part A.1990:23(2).103-113.
[9]P G Michalopoulos.Vehicle Detection Video Through Image Processing:The Autoscore System.IEEE Trans.on Vehicular Technology.1991.40(1).21-29.
[10]徐学才.高速公路事件管理系统设计及算法实现[学位论文].四川.西南交通大学.2004.3-4
[11]张彬彬.高速公路交通事件检测算法及检测器布设方案研究[学位论文].吉林.吉林大学.2005.4-5
[12]张洋.高速公路交通事件检测与管理系统研究[学位论文].北京.北京航天航空大学.2002.8-9
[13]王彦卿.交通异常门限值的探讨.公路交通科技.1900.7(18).51-56
[14]李文江,荆便顺.基于小波分析的事件检测算法.西安公路交通大学学报.1997.17(28).134-138
[15]周伟,罗石贵.基于模糊综合识别的事件检测算法.西安公路交通大学学报.2001.21(2).70-73
[16]郭恒明,张鹏飞.基于环形线圈的城市道路段交通异常自动检测方法研究.上海公路.2001.(4).31-34
[17]吕琪,王慧.基于动态神经网络模型的交通事件检测算法.公路交通科技.2003.20(6).105-108
[18]高海龙,张北海.高速公路紧急事件管理系统的开发.ITS通讯.2001.1(42).43-47
[19]彭春露,彭国雄.城市道路交通异常事件管理系统设计.交通运输系统工程与信息.2002.2(3).18-21
[20]张秀媛,达庆东.公路自动事件检测技术.系统工程理论与实践.2001.21(6).118-124
[21]孟建军.基于动态交通模型和多信息融合的高速公路交通事件检测算法[学位论文].江苏.河海大学.2007.6-20
[22]陆化普.城市交通管理评价体系.第1版.北京.人民交通出版社.2003.35-36
[23]潘若禹.基于数据融合的高速公路交通异常事件检测的研究[学位论文].西安.长安大学.2006.5-27
[24]王小华.基于模糊算法的高速公路事件检测及主线控制系统的研究与实现[学位论文].江苏.河海大学.2003.8-42
[25]庞根明.城市道路交通事件自动检测方法研究[学位论文].吉林.吉林大学.2007.37-38
[26]赵祥模.高速公路监控系统理论及应用.第1版.北京.电子工业出版社.2003.31-36
[27]徐名海.交通事件自动检测与决策系统的研究[学位论文].湖南.长沙交通学院.2002.7-10
[28]Peter T.Martin,Joseph Perrin,Blake Hansen.Incident Detection Algorithm Evaluation.University of Utah.Utah Department of Transportation.2001.7-35
[29]谭光莉,姜紫峰.高速公路事故自动检测算法的研讨.西安公路交通大学学报.1999.19(3).57-77
[30]唐金芝.数据融合技术在高速公路交通事件检测中的应用[学位论文].吉林.吉林大学.2007.5-7
[31]Y.J Stephanedes,A.P Chassiakos.Application of Filtering Techniques for Incident Detection.Journal of Transportation Engineering.1993.119(1).13-26
[32]刘伟铭,王倩.基于小波包变换的交通事件检测.交通与计算机.2004.22(6).9-12
[33]杨耀华,李昕等.高速公路事件检测系统及算法.公路交通科技.2003.20(3).133-136
[34]Willsky,A Chow,et al.Dynamic Model-based Techniques for the Detection of Incident on Freeways.IEEE Trans.Automatic Control.1980.25(3).347-360
[35]吕琪.基于动态神经网络模型的交通事件检测算法[学位论文].浙江.浙江大学.2007.17-25
[36]B Abdulhai and S.G Ritchie.Enhancing the University and Transferability of Freeway Incident Detection Using a Bayesian-based Neural Network.Transportation Research Part C.1996.7(5).261-280
[37]C.H Hsiao,C.T Lin and M.Cassidy.Application of Fuzzy Logic and Neural Networks to Automatically Detect Freeway Traffic Incident.Journal of Transportation Engineering.1994.125(5).753-772
[38]蔡志理.高速公路交通事件检测及交通疏导技术研究[学位论文].吉林.吉林大学.2007.13-14
[39]D.Srinivasan,R.L Cheu,et al.Development of an Intelligent Technique for Traffic Network Incident Detection.Engineering Application of Artificial Intelligence.2000.13(3).311-322
[40]陈德旺,关积珍等.基于占有率的交通流参数模型研究.交通运输系统工程与信息.2006.6(5).83-86
[41]张智星,孙春在等作.张平安等译.神经—模糊和软计算.第1版.西安.西安交通大学出版社.2006.89-117
[42]张志涌等.精通MATLAB6.5版.第1版.北京.北京航空航天大学出版社.2003.127-128
[43]张琨.快速路旅行时间预测算法研究[学位论文].北京北京交通大学.2007.26-53
[44]李世欣.基于集成模糊分类器的交通状态判别算法[学位论文].北京北京交通大学.2007.36-37
[45]Microsoft Corporation.对比SQL Server和Oracle..http://www.microsoft.com/china/sql/prodinfo/compare/oracle/default.mspx.2007-12-17
[46]启明工作室.Visual C++ +SQL Server数据库应用系统开发与实例.第1版.北京.人民邮电出版社.2004.109-143
[47]网冠科技.Visual C++6.0时尚编程百例.第1版.北京.机械工业出版社.2001.109-143