|Table of Contents|

[1] Miao Yinghao, Chen Guanghui, Wang Wentao, Gong Xiuqing, et al. Application of gray-tone difference matrix-based featuresof pavement macrotexture in skid resistance evaluation [J]. Journal of Southeast University (English Edition), 2015, 31 (3): 389-395. [doi:10.3969/j.issn.1003-7985.2015.03.016]
Copy

Application of gray-tone difference matrix-based featuresof pavement macrotexture in skid resistance evaluation()
Share:

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

Volumn:
31
Issue:
2015 3
Page:
389-395
Research Field:
Traffic and Transportation Engineering
Publishing date:
2015-09-20

Info

Title:
Application of gray-tone difference matrix-based featuresof pavement macrotexture in skid resistance evaluation
Author(s):
Miao Yinghao Chen Guanghui Wang Wentao Gong Xiuqing
Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China
Keywords:
asphalt pavement 3-dimensional macrotexture gray-tone difference matrix(GTDM) skid resistance
PACS:
U416.2
DOI:
10.3969/j.issn.1003-7985.2015.03.016
Abstract:
This paper presents a method to characterize asphalt pavement macrotexture using the gray-tone difference matrix(GTDM)and discusses the potentials of the GTDM indicators for skid resistance evaluation. There are 37 field sites included in the data collection, which cover 6 types of asphalt pavement surfaces. The mean profile depth derived from 3-D macrotexture measurements(MPD3)has a significant relationship with the mean texture depth(MTD), which can be described by a logarithm model with R2 of 0.962. There is no significant linear relationship between the friction coefficient at a speed of 60 km/h(DFT60)and macrotexture indicators. A nonlinear model with British pendulum number(BPN)incorporated can relate DFT60 to MTD or indicator fcon. A comparison with MTD shows that GTDM-based fcon has a potential to be a macrotexture indicator for skid resistance evaluation, which describes the general height difference and the average local height difference of pavement macrotexture. A relatively high fcon is helpful for improving asphalt pavement skid resistance.

References:

[1] OECD. Towards zero: ambitious road safety targets and the safe system approach [M]. Paris: Organization for Economic Co-operation and Development, 2008: 121.
[2] Henry J J. Evaluation of pavement friction of characteristics [R]. Washington, DC: Transportation Research Board, 2000.
[3] AASHTO. Guide for pavement friction [M]. Washington, DC: American Association of State Highway and Transportation Officials, 2008.
[4] Cackler E T, Ferragut T, Harrington D S. Evaluation of U.S. and European concrete pavement noise reduction methods [R]. Ames, IA, USA: National Concrete Pavement Technology Center, Iowa State University, 2006.
[5] Abbas A, Kutay M E, Azari H, et al. Three-dimensional surface texture characterization of portland cement concrete pavements [J]. Computer-Aided Civil and Infrastructure Engineering, 2007, 22(3): 197-209.
[6] Ech M, Yotte S, Morel S, et al. Laboratory evaluation of pavement macrotexture durability [J]. Revue Européenne de Génie Civil, 2007, 11(5): 643-662.
[7] Gendy A E, Shalaby A. Mean profile depth of pavement surface macrotexture using photometric stereo techniques [J]. Journal of Transportation Engineering, 2007, 133(7): 433-440.
[8] Gendy A E, Shalaby A, Saleh M, et al. Stereo-vision applications to reconstruct the 3D texture of pavement surface [J]. International Journal of Pavement Engineering, 2011, 12(3): 263-273.
[9] Vilaca J L, Fonseca J C, Pinho A M, et al. A new machine for acquire pavement texture [C]//IEEE 7th International Conference on Computational Cybernetics. Palma de Mallorca, Spain, 2009: 97-102.
[10] Wen J. Study on evaluating texture depth of asphalt pavement with digital technology [D]. Xi’an: School of Information Engineering, Chang’an University, 2009.
[11] Bitelli G, Simone A, Girardi F, et al. Laser scanning on road pavements: a new approach for characterizing surface texture [J]. Sensors, 2012, 12: 9110-9128.
[12] Sengoz B, Topal A, Tanyel S. Comparison of pavement surface texture determination by sand patch test and 3D laser scanning [J]. Periodica Polytechnica: Civil Engineering, 2012, 56(1): 73-78.
[13] Wang K C P, Li L. Pavement surface texture modeling using 1 mm 3d laser images [C]//Transportation Systems Workshop. Austin, TX, USA, 2012.
[14] Laurent J, Hébert J F, Lefebvre D, et al. Using 3d laser profiling sensors for the automated measurement of road surface conditions [C]//7th RILEM International Conference on Cracking in Pavements. Delft, Netherlands, 2012.
[15] Amadasun M, King R. Textural features corresponding to textural properties [J]. IEEE Transactions on Systems, Man and Cybernetics, 1989, 19(5): 1264-1274.
[16] Vince D G, Dixon K J, Cothren R M, et al. Comparison of texture analysis methods for the characterization of coronary plaques in intravascular ultrasound images [J]. Computerized Medical Imaging and Graphics, 2000, 24(4): 221-229.
[17] Christodoulou C I, Michaelides S C, Pattichis C S. Multifeature texture analysis for the classification of clouds in satellite imagery [J]. IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(11): 2662-2668.
[18] Nurzyńska K, Kubo M, Muramoto K. Texture operator for snow particle classification into snowflake and graupel [J]. Atmospheric Research, 2012, 118: 121-132.
[19] Materka A, Strzelecki M. Texture analysis methods—a review [R]. Brussels: Institute of Electronics, Technical University of Lodz, 1998.
[20] Miao Y H, Song P P, Gong X Q. Fractal and multifractal characteristics of 3D asphalt pavement macrotexture [J]. Journal of Materials in Civil Engineering, 2014, 26(8): 04014033.
[21] ASTM. E1845-09 Standard practice for calculating pavement macrotexture mean profile depth [S]. West Conshohocken: ASTM International, 2009.
[22] Wambold J C, Antle C E, Henry J J, et al. International PIARC experiment to compare and harmonize texture and skid resistance measurements [R]. Paris: Permanent International Association of Road Congresses, 1995.

Memo

Memo:
Biography: Miao Yinghao(1975—), male, doctor, associate professor, miaoyinghao@bjut.edu.cn.
Foundation item: The National Natural Science Foundation of China(No.50908004, 51178013).
Citation: Miao Yinghao, Chen Guanghui, Wang Wentao, et al. Application of gray-tone difference matrix-based features of pavement macrotexture in skid resistance evaluation[J].Journal of Southeast University(English Edition), 2015, 31(3):389-395.[doi:10.3969/j.issn.1003-7985.2015.03.016]
Last Update: 2015-09-20