基于GPS浮动车的城市交通路段行程时间实时估算方法研究
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摘要
路段行程时间是反映交通流运行的一个重要指标。实时或准实时行程时间数据是构建动态交通信息服务系统、信号协调控制系统以及城市交通诱导系统等ITS子系统的重要基础,也是国内外ITS研究的热点。恰当地给出实时的路段行程时间,可以为交通管理部门提供准确的道路交通数据,以便管理、调度;可以为出行者提供有意义的参考,使他们选择适合的出行路线,避免时间和金钱的浪费,同时提高路网利用率。因此,路段行程时间的实时估算对道路运行系统有重要意义。
本文首先综述了交通信息采集技术,对比各种采集技术优缺点,选用GPS浮动车作为实时交通信息获取的来源;其次,对现有路段行程时间的估算方法做了分析,重点分析了浮动车法估算行程时间的各种不同算法;最终,对基于GPS浮动车的城市交通路段行程时间实时估算方法做了深入研究。完成的具体内容如下:
1.首先,综述实时交通信息的获取方式和路段行程时间的估算方法。介绍了常见的交通数据采集技术,着重介绍了GPS浮动车技术,包括GPS系统、GPS在交通采集中的应用,GPS浮动车技术的基本概念、系统工作原理及优点。介绍了现有的各种路段行程时间估算方法,重点对浮动车法估算路段行程时间进行介绍,如样本中位数估算方法、指数平滑估算方法、基于速度和时间的估算方法、结合断面检测数据估算方法。
2.其次,主要研究基于GPS浮动车的城市交通路段行程时间实时估算方法。分析了影响利用GPS浮动车数据进行行程时间实时估算的主要因素;给出估算方法中确定计算间隔的基本思路和实现方法;分析GPS浮动车实时数据的预处理过程,包括故障数据的识别和修复;改进了GPS定位数据的转换算法,并将该算法应用于GPS浮动车数据和电子地图的匹配方法中;结合文中对城市路段的定义,给出路段行程时间的实时估算方法。
3.最后,以文中提出的计算间隔确定方法、改进的GPS定位数据的转换算法、路段行程时间的实时估算方法为核心技术,结合VB技术开发了一套演示系统,并通过广州市某路段的GPS浮动车数据对该方法进行仿真。实践证明,本文提出的路段行程时间实时估算方法,能够以较高的运算效率提供合理的路段实时行程时间,具有一定的实用意义。
Link travel-time is reflected in the traffic flow at an important indicator. Real-time or quasi real-time travel time data is an important basis to build ITS subsystems, such as dynamic traffic information service system, signal coordination control system and urban traffic guidance systems. ITS is the research hotspot at home and abroad. Properly giving real-time link travel-time has two meanings. For one thing, it can provide accurate traffic data for traffic management department for management, scheduling. For another, it can provide meaningful information for travelers to enable them to choose the appropriate travel routes, and to avoid wasting time and money while improving road network utilization. Therefore, real-time link travel-time estimation on the road is important to run the system.
In this paper, traffic information collection technologies are reviewed, the advantages and disadvantages of various collection techniques are compared, GPS floating car technology is chosen as a source of real-time traffic information; Second, the existing link travel time estimation methods were analyzed, focusing on analysis of the floating car method Estimated travel time for a variety of different algorithms; Ultimately, GPS-based floating car real-time urban traffic link travel time estimation method to do an in-depth research. Complete details are as follows:
1. Firstly, ways to obtain real-time traffic information and link travel time estimation methods are reviewed. Common traffic data acquisition technologies are introduced, focusing on the GPS floating car technology, including GPS systems, GPS applications in traffic acquisition, GPS floating car technology, the basic concept, working principle and advantages of the system. Describes the various sections of the existing travel time estimation methods, with emphasis on the floating car used in the estimation of link travel time are introduced, such as the sample median estimation method, exponential smoothing estimation methods, based on speed and time estimation methods, combined with test data section estimation method.
2. Secondly, real-time travel time estimation method of urban traffic link based on GPS floating car is mainly researched. Analysis of the impact of using GPS probe vehicle data for real-time estimates of travel time factors; given interval estimation method identified in the calculation of the basic ideas and methods; analysis of real-time GPS probe vehicle data preprocessing, including data to identify and repair faults ; improve the GPS positioning data conversion algorithm and the algorithm used in GPS floating car data and electronic map matching method; combined paper on the definition of urban roads, given the real-time link travel time estimation method.
3. Finally, this paper presents the calculation to determine the method of interval, improved GPS positioning data conversion algorithm, real-time link travel time estimation methods as the core technologies, combined with VB technology, a set of demonstration system is developed. Through a section of Guangzhou GPS floating car data, the method is simulated. Practice shows that the proposed real-time link travel time estimation method can provide a reasonable high computing efficiency section of real-time travel time, with certain practical significance.
本文首先综述了交通信息采集技术,对比各种采集技术优缺点,选用GPS浮动车作为实时交通信息获取的来源;其次,对现有路段行程时间的估算方法做了分析,重点分析了浮动车法估算行程时间的各种不同算法;最终,对基于GPS浮动车的城市交通路段行程时间实时估算方法做了深入研究。完成的具体内容如下:
1.首先,综述实时交通信息的获取方式和路段行程时间的估算方法。介绍了常见的交通数据采集技术,着重介绍了GPS浮动车技术,包括GPS系统、GPS在交通采集中的应用,GPS浮动车技术的基本概念、系统工作原理及优点。介绍了现有的各种路段行程时间估算方法,重点对浮动车法估算路段行程时间进行介绍,如样本中位数估算方法、指数平滑估算方法、基于速度和时间的估算方法、结合断面检测数据估算方法。
2.其次,主要研究基于GPS浮动车的城市交通路段行程时间实时估算方法。分析了影响利用GPS浮动车数据进行行程时间实时估算的主要因素;给出估算方法中确定计算间隔的基本思路和实现方法;分析GPS浮动车实时数据的预处理过程,包括故障数据的识别和修复;改进了GPS定位数据的转换算法,并将该算法应用于GPS浮动车数据和电子地图的匹配方法中;结合文中对城市路段的定义,给出路段行程时间的实时估算方法。
3.最后,以文中提出的计算间隔确定方法、改进的GPS定位数据的转换算法、路段行程时间的实时估算方法为核心技术,结合VB技术开发了一套演示系统,并通过广州市某路段的GPS浮动车数据对该方法进行仿真。实践证明,本文提出的路段行程时间实时估算方法,能够以较高的运算效率提供合理的路段实时行程时间,具有一定的实用意义。
Link travel-time is reflected in the traffic flow at an important indicator. Real-time or quasi real-time travel time data is an important basis to build ITS subsystems, such as dynamic traffic information service system, signal coordination control system and urban traffic guidance systems. ITS is the research hotspot at home and abroad. Properly giving real-time link travel-time has two meanings. For one thing, it can provide accurate traffic data for traffic management department for management, scheduling. For another, it can provide meaningful information for travelers to enable them to choose the appropriate travel routes, and to avoid wasting time and money while improving road network utilization. Therefore, real-time link travel-time estimation on the road is important to run the system.
In this paper, traffic information collection technologies are reviewed, the advantages and disadvantages of various collection techniques are compared, GPS floating car technology is chosen as a source of real-time traffic information; Second, the existing link travel time estimation methods were analyzed, focusing on analysis of the floating car method Estimated travel time for a variety of different algorithms; Ultimately, GPS-based floating car real-time urban traffic link travel time estimation method to do an in-depth research. Complete details are as follows:
1. Firstly, ways to obtain real-time traffic information and link travel time estimation methods are reviewed. Common traffic data acquisition technologies are introduced, focusing on the GPS floating car technology, including GPS systems, GPS applications in traffic acquisition, GPS floating car technology, the basic concept, working principle and advantages of the system. Describes the various sections of the existing travel time estimation methods, with emphasis on the floating car used in the estimation of link travel time are introduced, such as the sample median estimation method, exponential smoothing estimation methods, based on speed and time estimation methods, combined with test data section estimation method.
2. Secondly, real-time travel time estimation method of urban traffic link based on GPS floating car is mainly researched. Analysis of the impact of using GPS probe vehicle data for real-time estimates of travel time factors; given interval estimation method identified in the calculation of the basic ideas and methods; analysis of real-time GPS probe vehicle data preprocessing, including data to identify and repair faults ; improve the GPS positioning data conversion algorithm and the algorithm used in GPS floating car data and electronic map matching method; combined paper on the definition of urban roads, given the real-time link travel time estimation method.
3. Finally, this paper presents the calculation to determine the method of interval, improved GPS positioning data conversion algorithm, real-time link travel time estimation methods as the core technologies, combined with VB technology, a set of demonstration system is developed. Through a section of Guangzhou GPS floating car data, the method is simulated. Practice shows that the proposed real-time link travel time estimation method can provide a reasonable high computing efficiency section of real-time travel time, with certain practical significance.
引文
[1] Stephen J. Bahler. Field Test of non-intrusive traffic Detection technologies. Proceedings of the 5th World Congress on Intelligent Transportation Systems.Seoul,Korea,1998
[2]王曦光,胡春龙,刘丽娟.浅议交通量数据采集的几种方法[J].北方交通,2009,10(10):76-78
[3]朱中,杨兆升,初连禹.交通流诱导系统信息采集技术[J].吉林工业大学自然科学学报.1999,(1):86-91
[4]王力,王川久.智能交通系统中实时交通信息采集处理的新方法[J].系统工程.2005,(2):86-89
[5]刘基余.GPS卫星导航定位原理与方法[M].北京:科学出版社,2003
[6]常青,杨东凯,寇艳红等.车辆导航定位方法及应用[M].北京:机械工业出版社,2005
[7]杜歆,李宏东,顾伟康.一种提高差分GPS基准站定位精度的新方法[J].浙江大学学报(理学版),2002,29(6):637-642
[8] NRC, National Research Council,2002,Collecting,processing and integrating PS data into GIS[C].NCHRP Synthesis 301.National Academy Press; Washington D.C.
[9]李江.交通工程学[M].北京:人民交通出版社,2002.
[10]邹亮,徐建闽,朱玲湘等.基于行程时间估计的快速路检测器布设密度优化方法研究[J].公路交通科技,2007.24(6):114-117
[11] Huisken, G. and E.C.Van Berkum. A Comparative Analysis of Short-Range Travel Time Prediction Methods. Proc. of 82nd Annual TRB meeting. 2003
[12]张和生,张毅,温慧敏等.利用GPS数据估计路段的平均行程时间[J].吉林大学学报(工学版),2007,37(3):533-537
[13]段学勇.基于小样本浮动车数据的信号灯路段行程时间估计方法研究[D].北京交通大学,2008
[14] Matin A.Ferman, Derinis E.Blumenfeld and Xiaowen Dai, A Simple Analytical Model of a Probe-Based Traffic Information System, IEEE, 2003
[15] TRB, National Research Council. Highway capacity manual [M], Washington, D.C: TRB, National Research Council.2000
[16]中国公路学会《交通工程手册》编委会.交通工程手册[M].北京:人民交通出版社,1998,464-469
[17]王炜,过秀成.交通工程学[M].东南大学出版社,2000
[18]任福田,刘小明,荣建.交通工程学.人民交通出版社,2003
[19]章威,徐建闽,张孜.基于出租车GPS定位技术的ITS共用信息平台实时路况信息采集及处理方法[J].公路交通科技,2007,24(5):125-129
[20]方志伟.基于浮动车数据的城市路段行程时间预测研究[D].北京交通大学,2008
[21]杨立娟.基于浮动车的城市道路行程时间采集与预测方法研究[D].吉林大学,2007
[22]常安德.基于GPS浮动车的路段行程时间采集方法研究[D].吉林大学,2009
[23]张伟.基于GPS-GIS的路段行程时间预测研究[D].辽宁工程技术大学,2006
[24]高学英.城市道路路段行程时间估计与融合方法[D].吉林大学,2009
[25]姜桂艳,常安德,张玮.基于GPS浮动车的路段行程时间估计方法比较[J].吉林大学学报(工学版),2009,39(9):182-185
[26]蒋捷,陈军.导航地图数据库[M].北京:科学出版社,2005,1-7
[27]何兆成,赵建明,王振波,韦清波.城市信号控制网络中的路段行程时间估计法[J].交通运输工程学报,2008,8(4):95-98
[28]张和生,张毅,胡东成.路段平均行程时间估计方法[J].交通运输工程学报,2008,8(1),89-96
[29]张保存,杨晓光,严新平.基于浮动车的交通信息采集系统研究[J].交通与计算机,2006,24(5),31-34
[30]杜景龙,姜俐平.地理信息系统的数据精度分析[J].东北测绘,2001,24(1):27-28
[31]朱华统,杨元喜,吕志平.GPS坐标系统的变换[M].北京:测绘出版社,1994
[32]李裕聪,覃绍伟.用VB编程实现GPS测量中的坐标系统转换[J].中国水运,2008,8(1):133-134
[33]鲍远律,刘振安.卫星定位、交通监控与数字地图[M].北京:国防工业出版社,2006
[34]姜晨光,阎桂峰.椭球子午线弧长计算的新方法[J].测绘工程,1998,7(4):38-42
[35]史其信.GPS技术在智能交通系统中的应用[J].中国安防产品信息,2004,3(3):20-25
[36]杨兆升.关于智能运输系统的关键理论——综合路段行程时间预测的研究[J].交通运输工程学报.2001,(1):65-67
[37]沙定国.误差分析与测量不确定度评定[M].北京:中国计量出版社,2003
[38]胡明伟.基于GPS的实时交通信息采集方法的研究[J].公路交通科技,2007,24(5):121-124
[39]李佳伟.基于GPS的浮动车系统中数据传输方式相关问题的研究[D].北京交通大学,2008
[40]董均宇.基于GPS浮动车的城市路段平均速度估计技术研究[D].重庆大学,2006
[2]王曦光,胡春龙,刘丽娟.浅议交通量数据采集的几种方法[J].北方交通,2009,10(10):76-78
[3]朱中,杨兆升,初连禹.交通流诱导系统信息采集技术[J].吉林工业大学自然科学学报.1999,(1):86-91
[4]王力,王川久.智能交通系统中实时交通信息采集处理的新方法[J].系统工程.2005,(2):86-89
[5]刘基余.GPS卫星导航定位原理与方法[M].北京:科学出版社,2003
[6]常青,杨东凯,寇艳红等.车辆导航定位方法及应用[M].北京:机械工业出版社,2005
[7]杜歆,李宏东,顾伟康.一种提高差分GPS基准站定位精度的新方法[J].浙江大学学报(理学版),2002,29(6):637-642
[8] NRC, National Research Council,2002,Collecting,processing and integrating PS data into GIS[C].NCHRP Synthesis 301.National Academy Press; Washington D.C.
[9]李江.交通工程学[M].北京:人民交通出版社,2002.
[10]邹亮,徐建闽,朱玲湘等.基于行程时间估计的快速路检测器布设密度优化方法研究[J].公路交通科技,2007.24(6):114-117
[11] Huisken, G. and E.C.Van Berkum. A Comparative Analysis of Short-Range Travel Time Prediction Methods. Proc. of 82nd Annual TRB meeting. 2003
[12]张和生,张毅,温慧敏等.利用GPS数据估计路段的平均行程时间[J].吉林大学学报(工学版),2007,37(3):533-537
[13]段学勇.基于小样本浮动车数据的信号灯路段行程时间估计方法研究[D].北京交通大学,2008
[14] Matin A.Ferman, Derinis E.Blumenfeld and Xiaowen Dai, A Simple Analytical Model of a Probe-Based Traffic Information System, IEEE, 2003
[15] TRB, National Research Council. Highway capacity manual [M], Washington, D.C: TRB, National Research Council.2000
[16]中国公路学会《交通工程手册》编委会.交通工程手册[M].北京:人民交通出版社,1998,464-469
[17]王炜,过秀成.交通工程学[M].东南大学出版社,2000
[18]任福田,刘小明,荣建.交通工程学.人民交通出版社,2003
[19]章威,徐建闽,张孜.基于出租车GPS定位技术的ITS共用信息平台实时路况信息采集及处理方法[J].公路交通科技,2007,24(5):125-129
[20]方志伟.基于浮动车数据的城市路段行程时间预测研究[D].北京交通大学,2008
[21]杨立娟.基于浮动车的城市道路行程时间采集与预测方法研究[D].吉林大学,2007
[22]常安德.基于GPS浮动车的路段行程时间采集方法研究[D].吉林大学,2009
[23]张伟.基于GPS-GIS的路段行程时间预测研究[D].辽宁工程技术大学,2006
[24]高学英.城市道路路段行程时间估计与融合方法[D].吉林大学,2009
[25]姜桂艳,常安德,张玮.基于GPS浮动车的路段行程时间估计方法比较[J].吉林大学学报(工学版),2009,39(9):182-185
[26]蒋捷,陈军.导航地图数据库[M].北京:科学出版社,2005,1-7
[27]何兆成,赵建明,王振波,韦清波.城市信号控制网络中的路段行程时间估计法[J].交通运输工程学报,2008,8(4):95-98
[28]张和生,张毅,胡东成.路段平均行程时间估计方法[J].交通运输工程学报,2008,8(1),89-96
[29]张保存,杨晓光,严新平.基于浮动车的交通信息采集系统研究[J].交通与计算机,2006,24(5),31-34
[30]杜景龙,姜俐平.地理信息系统的数据精度分析[J].东北测绘,2001,24(1):27-28
[31]朱华统,杨元喜,吕志平.GPS坐标系统的变换[M].北京:测绘出版社,1994
[32]李裕聪,覃绍伟.用VB编程实现GPS测量中的坐标系统转换[J].中国水运,2008,8(1):133-134
[33]鲍远律,刘振安.卫星定位、交通监控与数字地图[M].北京:国防工业出版社,2006
[34]姜晨光,阎桂峰.椭球子午线弧长计算的新方法[J].测绘工程,1998,7(4):38-42
[35]史其信.GPS技术在智能交通系统中的应用[J].中国安防产品信息,2004,3(3):20-25
[36]杨兆升.关于智能运输系统的关键理论——综合路段行程时间预测的研究[J].交通运输工程学报.2001,(1):65-67
[37]沙定国.误差分析与测量不确定度评定[M].北京:中国计量出版社,2003
[38]胡明伟.基于GPS的实时交通信息采集方法的研究[J].公路交通科技,2007,24(5):121-124
[39]李佳伟.基于GPS的浮动车系统中数据传输方式相关问题的研究[D].北京交通大学,2008
[40]董均宇.基于GPS浮动车的城市路段平均速度估计技术研究[D].重庆大学,2006