|Table of Contents|

[1] Zhou Lan, Ni Fujian, Zhao Yanjing,. Prediction method of highway pavement ruttingbased on the grey theory [J]. Journal of Southeast University (English Edition), 2015, 31 (3): 396-400. [doi:10.3969/j.issn.1003-7985.2015.03.017]
Copy

Prediction method of highway pavement ruttingbased on the grey theory()
基于灰色理论的高速公路路面车辙预测方法
Share：

Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
31
Issue:
2015 3
Page:
396-400
Research Field:
Traffic and Transportation Engineering
Publishing date:
2015-09-20

Info

Title:
Prediction method of highway pavement ruttingbased on the grey theory
基于灰色理论的高速公路路面车辙预测方法
Author(s):
Zhou Lan1;  Ni Fujian1;  Zhao Yanjing2
1School of Transportation, Southeast University, Nanjing 210096, China
2School of Civil Engineering, Southeast University, Nanjing 210096, China
周岚1;  倪富健1;  赵岩荆2
1东南大学交通学院, 南京 210096; 2东南大学土木工程学院, 南京 210096
Keywords:
prediction method;  grey theory;  cluster analysis;  analysis of variance;  pavement rutting
预测方法;  灰色理论;  聚类分析;  方差分析;  路面车辙
PACS:
U416.217
DOI:
10.3969/j.issn.1003-7985.2015.03.017
Abstract:
In order to make a scientific pavement maintenance decision, a grey-theory-based prediction methodological framework is proposed to predict pavement performance. Based on the field pavement rutting data, analysis of variance(ANOVA)was first used to study the influence of different factors on pavement rutting. Cluster analysis was then employed to investigate the rutting development trend. Based on the clustering results, the grey theory was applied to build pavement rutting models for each cluster, which can effectively reduce the complexity of the predictive model. The results show that axial load and asphalt binder type play important roles in rutting development. The prediction model is capable of capturing the uncertainty in the pavement performance prediction process and can meet the requirements of highway pavement maintenance, and, therefore, has a wide application prospects.
为了制定科学的路面养护决策, 提出了一种基于灰色理论的路面性能预测方法.基于路面车辙检测数据, 采用方差分析方法研究不同因素对车辙的影响;利用聚类分析方法研究路面车辙发展规律;基于聚类结果, 采用灰色理论分类建立了路面车辙灰色预测模型, 有效降低了模型的复杂程度.研究结果表明, 轴载和沥青类型对车辙的发展影响最大.所提预测模型精度较高, 具有一定的实用价值, 能满足高速公路路面养护工程要求, 并能较好地解决路面性能预测中的不确定性.

References:

[1] Somayeh N, Mohammad H S, Alireza B. Development of roughness prediction models using Alberta transportation’s pavement management system[J]. International Journal of Pavement Research and Technology, 2013, 6(6): 714-720.
[2] Arambula E, George R, Xiong W X, et al. Development and validation of pavement performance models for the state of Maryland[J]. Transportation Research Record, 2011, 2225: 25-31.
[3] Wu Z, Chen X W, Yang X M, et al. Finite element model for rutting prediction of flexible pavement with cementitiously stabilized base-subbase[J]. Transportation Research Record, 2011, 2226: 104-110.
[4] Porras-Alvarado J D, Zhang Z M, Salazar L G L. Probabilistic approach to modeling pavement performance using IRI data[C]//Transportation Research Board 93rd Annual Meeting. Washington DC, USA, 2014:145437-1-145437-15.
[5] Prozzi J, Madanat S. Development of pavement performance models by combining experimental and field data[J]. Journal of Infrastructure Systems, 2004, 10(1): 9-22.
[6] Ma J X, Xu F Y, Huang R. A linear and nonlinear auto-regressive model and its application in modeling and forecasting[J]. Journal of Southeast University: Natural Science Edition, 2013, 43(3): 509-514.(in Chinese)
[7] Wang K C P, Li Q, Hall K D, et al. Experimentation with grey theory for pavement smoothness prediction[J]. Transportation Research Record, 2007, 1990: 3-13.
[8] Yi J, Shuo L. Grey system model for estimating the pavement international roughness index [J]. Journal of Performance of Constructed Facilities, 2005, 19(1): 62-68.
[9] Ministry of Communications of the People’s Republic of China. JTG H20—2007 Highway performance assessment standards [S]. Beijing: People Transportation Publishing House, 2008.(in Chinese)
[10] Lu W D. Statistical package for the social sciences(SPSS)tutorial: statistical analysis[M]. Beijing: Publishing House of Electronics Industry, 2012: 64-145.(in Chinese)

Memo

Memo:
Biographies: Zhou Lan(1984—), female, graduate; Ni Fujian(corresponding author), male, doctor, professor, nifujian@gmail.com.
Foundation item: The Major Scientific and Technological Special Project of Jiangsu Provincial Communications Department(No.2011Y/02-G1).
Citation: Zhou Lan, Ni Fujian, Zhao Yanjing. Prediction method of highway pavement rutting based on the grey theory[J].Journal of Southeast University(English Edition), 2015, 31(3):396-400.[doi:10.3969/j.issn.1003-7985.2015.03.017]
Last Update: 2015-09-20