A portable measurement system for pavement surface macrotexture – a case study in China

ABSTRACT

This study proposes a portable measurement system (PS) for pavement surface macrotexture, which improves the current detection technology and provides the necessary support for maintenance and evaluation works on urban roads, newly built roads, parking, footpath, tunnels, bicycle lanes, and short distance roads. The system can obtain the elevation values through a high precision laser sensor and a data acquisition card. Next, the outliers of natural elevation values are screened and interpolated by a statistical test method, and then the corrected data are filtered by an improved Kalman filter algorithm. Finally, the mean profile depth (MPD) is calculated based on the standard ASTM E1845-15. The replication experiments, the correlation experiments with sand patch test (SPT), and the comparative experiment with vehicle laser profiler (VLP) are carried out on 20 test sections. The results show that the variation coefficients of PS are less than 5%, the correlation indexes with SPT are more than 0.928, the mean square errors and the mean absolute percentage errors of PS are less than 0.0032 and 4.98%, respectively. Meanwhile, the conversion models of MPD with mean texture depth (MTD) are established to realise that the direct estimation of MTD data utilising MPD data for different pavement types.

KEYWORDS:

• Macrotexture depth
• portable system
• Kalman filter
• mean profile depth
• verification experiment
• comparative experiment

Acknowledgement

This work was supported by the [National Natural Science Foundation of China]: [Grant Number: NSFC71871165]. The authors are responsible for all views and opinions expressed in this paper. Besides, we would like to thank the Shanghai Pres Company for providing vehicle laser profiler for academic and research activities, and the researchers in the road engineering department of Tongji university for their help to pavement material verification.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by Natural Science Foundation of China [grant number NSFC71871165].