Utilization of 2 D Laser Scan system to evaluate 3D surface texture and potholes detection on pavement

Shih Huang Chen, Ching Tsung Hung, Chang Hua Yu, Cheng I. Li, Chien An Wu

Research output: Contribution to journalArticlepeer-review


Distresss & Friction of pavement is the most popular tropic which is concerned by administrator and engineers, surface texture are also widely regarded as key factor to influence friction. The brief object of this study is to establish the relationship between 3 D texture and friction. In the study, the mixtures include Dense Grade Asphalt Concrete (DGAC), Stone Mastic Asphalt (SMA), and Porous Asphalt (PA). High Definition Scan Texture Machine (HDSTM) with 2D Laser CCD was adopted to measure the 2 D texture of Asphalt concrete specimens, and British Portable Tester (BPN) was also used to evaluate friction of various mixture specimen surfaces. The study was attempted to further create initial 3 D model with data of HDSTM and Computer Simulation Program. Correlation coefficients between the ratio of Surface area in unit area (SA/A) and friction was up to 0.8. SA/A could be regards as the best feasible factor to estimate the mixture surface in the ability of skid resistance, and. Based on above results, 3D texture parameter is remarkable for evaluation of friction . The other object of this study was detecting Potholes with 2D Laser CCD, and High Definition Pavement Texture Machine (HDPTM) was adopted in this study. According to results, the HDPTM could be easy and accuracy to detect small potholes. In brief, 2-D Laser Scan System could be used to evaluate 3D texture and potholes on pavement, and this issue was worthy of further study.

Original languageEnglish
Pages (from-to)7079-7086
Number of pages8
JournalInformation (Japan)
Issue number9 B
StatePublished - Sep 2013


  • 2d laser
  • 3 d texture
  • And potholes detection


Dive into the research topics of 'Utilization of 2 D Laser Scan system to evaluate 3D surface texture and potholes detection on pavement'. Together they form a unique fingerprint.

Cite this