Performance Evaluation of Traffic Speed Deflectometer Based on Virtual Standard Test Road

It is challenging to find actual standard test roads (ASTRs) to evaluate the measuring performance of the Traffic Speed Deflectometer (TSD), leading to misjudgment of its evaluation results. To address this issue, a method to construct virtual standard test roads (VSTRs) using in-service roads is proposed. Firstly, the principle of TSD based on the Laser-Doppler effect to measure pavement deflection is introduced, and the shortcomings of traditional evaluation methods are reviewed and summarized. Secondly, an adaptive construction method for VSTRs is proposed based on the K-means clustering algorithm. It layers the Falling Weight Deflectometer (FWD) measurements on in-service roads and reconstructs them as virtual roads with stable deflections but different ranges. Thirdly, two new indexes, the coefficient of variation CVk and the influence coefficient of speed ICSk, are proposed to replace the traditional indexes, such as repeatability and correlation coefficient. Finally, the feasibility of evaluating TSD performance based on VSTRs and the new indexes is verified by experiments. Results show that the newly constructed VSTRs solve the problem that the ASTRs are challenging to obtain, reducing the experimental requirements for evaluating TSD, and the new indexes achieve an efficient and scientific evaluation of TSD.

Automated summary

In order to solve the problem of difficult acquisition of actual standard test roads (ASTRs) for evaluating the measuring performance of the Traffic Speed Deflectometer (TSD), a method to construct virtual standard test roads (VSTRs) using in-service roads is proposed in this study. An adaptive construction method for VSTRs is proposed based on the K-means clustering algorithm, and two new indexes CVk and ICSk are introduced to replace traditional indexes such as repeatability and correlation coefficient. The feasibility of evaluating TSD performance based on VSTRs and the new indexes is verified by experiments, showing that the newly constructed VSTRs solve the problem of difficult acquisition of ASTRs and the new indexes achieve an efficient and scientific evaluation of TSD.