Real-Time Asphalt Pavement Layer Thickness Prediction Using Ground-Penetrating Radar Based on a Modified Extended Common Mid-Point (XCMP) Approach

  • Siqi Wang
  • , Zhen Leng
  • , Xin Sui
  • , Weiguang Zhang
  • , Tao Ma
  • , Zehui Zhu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

The conventional surface reflection method has been widely used to measure the asphalt pavement layer dielectric constant using ground-penetrating radar (GPR). This method may be inaccurate for in-service pavement thickness estimation with dielectric constant variation through the depth, which could be addressed using the extended common mid-point method (XCMP) with air-coupled GPR antennas. However, the factors affecting the XCMP method on thickness prediction accuracy haven’t been studied. Manual acquisition of key factors is required, which hinders its real-time applications. This study investigates the affecting factors and develops a modified XCMP method to allow automatic thickness prediction of in-service asphalt pavement with non-uniform dielectric properties through depth. A sensitivity analysis was performed, necessitating the accurate estimation of time of flights (TOFs) from antenna pairs. A modified XCMP method based on edge detection was proposed to allow real-time TOFs estimation, then dielectric constant and thickness predictions. Field tests using a multi-channel GPR system were performed for validation. Both the surface reflection and XCMP setups were conducted. Results show that the modified XCMP method is recommended with a mean prediction error of 1.86%, which is more accurate than the surface reflection method (5.73%).

Original languageEnglish
Pages (from-to)1-13
Number of pages13
JournalIEEE Transactions on Intelligent Transportation Systems
DOIs
Publication statusAccepted/In press - 2024

Keywords

  • Antennas
  • Asphalt
  • Asphalt pavement
  • Dielectric constant
  • Estimation
  • extended common mid-point method
  • ground-penetrating radar
  • layer thickness
  • Mathematical models
  • Real-time systems
  • Reflection

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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