交通运输系统工程与信息

交通运输系统工程与信息 ›› 2006, Vol. 6 ›› Issue (5): 42-49 .

• 智能交通系统与信息技术 • 上一篇    下一篇

一种改善的路面粗糙度评价抽样方法

王秀斌1 ，YU Lei2 ，ZHUO Wei-jie3，LI Xiu-gang4   

  1. 1．Department of Business and Economics，University of Wisconsin-Superior，WI 54880-4500，USA 2．Texas Southern University and Changjiang Scholar of Northern Jiaotong University；3．Houston-Galveston Area Council，TX，USA；4．Department of Civil Engineering，Tonri University，China

    1．美国威斯康星大学苏泊尔分校工商经济系，威斯康星，美国54880-4500；
    2．Texas Southern University and Changjiang Scholar of Beijing Jiaotong University；3．Houston-Galveston Area Council，TX，USA；
    4．同济大学城市建设学院，中国

  • 收稿日期:2006-09-10 修回日期:1900-01-01 出版日期:2006-10-20 发布日期:2006-10-20

Improved Sampling Method for Pavement Roughness Evaluation

WANG Xiu-bin1，YU Lei2 ，ZHUO Wei-jie3 ，LI Xiu-gang4   

  1. 1．Department of Business and Economics，University of Wisconsin-Superior，WI 54880-4500，USA 2．Texas Southern University and Changjiang Scholar of Northern Jiaotong University；3．Houston-Galveston Area Council，TX，USA；4．Department of Civil Engineering，Tonri University，China

  • Received:2006-09-10 Revised:1900-01-01 Online:2006-10-20 Published:2006-10-20

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摘要： 鉴于对国家公路系统进行全面评价的方法耗费太大，一般采用抽样方法来评价路面粗糙度，这涉及到很多实际因素．尽管分层随机抽样的方法已经在干线和一般的集散系统得到利用，它仍有很大的发展空间．本文在提出多个针对路面条件的随机变量的基础上，通过改变路面粗糙度分布的基本假定来改进抽样方法，为路面粗糙度的估计建立了一个整体的框架．论文简要介绍了简单随机抽样、分层随机抽样方式，通过分析说明后者能够对路面网络的粗糙度样本提供更全面的估计，而且其偏差更小．论文进一步讨论了以精确估计为基础的良好分层带来的影响．结果表明，在交通网络上可找到一种独特的优化分层方法．根据分析结果，本文定义了该改进分层方法．

关键词: 国际路面粗糙度指数, 路面管理, 分层随机抽样, 公路工程

Abstract: The sampling method for pavement roughness evaluation has significant practical implications because the exhaustive review method in use for Nation Highway System (NHS)is too costly．Though stratified random sampling method is adopted for the arterial and collector functional systems there is a good potential to improve it．In this paper，we build a general framework for pavement roughness evaluation by improving the sampling method with fundamental assumptions about the distribution of pavement roughness，based on which we define the random variable for the overall pavement condition．After briefly introducing a simple random sampling and a stratified random sampling method，we analytically show that the latter can provide an estimate of the comprehensive roughness profile over the network with a smaller deviation．We further discuss the impact of a good stratification on an accurate estimation．Analytically we show that there exists a unique optimal stratification method applied to the transportation network．Based on the analytical result，we propose an improved stratification method．

Key words: international roughness index, pavement management, stratified random sampling, highway engineering