4.6 Article

Differences Evaluation of Pavement Roughness Distribution Based on Light Detection and Ranging Data

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APPLIED SCIENCES-BASEL
卷 13, 期 14, 页码 -

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MDPI
DOI: 10.3390/app13148080

关键词

highway transportation; pavement roughness measurement; LiDAR data analysis; hypothetical test

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This study utilized high-precision LiDAR technology to obtain three-dimensional point cloud data for a 25 km road section in Shanghai. Variance analysis and the Kruskal-Wallis test were conducted to evaluate the differences in the distribution and variability of pavement roughness. The findings revealed significant differences in the international roughness index (IRI) among the survey lines within the road section. Additionally, it was recommended to consider the lateral distribution of pavement roughness and regulate the detection length in road performance evaluations to enhance reliability and facilitate more accurate maintenance decision making.
Pavement roughness serves as a crucial indicator for evaluating road performance. However, traditional measurement methods, such as laser detection vehicles, are limited to providing roughness values for a single profile, failing to capture the overall pavement condition comprehensively. To address this limitation, this study utilized high-precision light detection and ranging technology (LiDAR) to acquire three-dimensional point cloud data for a 25 km road section in Shanghai. Road elevations were extracted from different lateral survey lines. Subsequently, variance analysis and the Kruskal-Wallis non-parametric test were conducted to evaluate the differences in the lateral distribution and longitudinal variability of the pavement roughness. The findings revealed significant differences in the international roughness index (IRI) among the survey lines within the road section. Moreover, the observed variations in the lateral distribution of pavement roughness were influenced by the characteristics of the road section itself. Roads exhibiting discrete roughness patterns displayed a higher likelihood of significant detection disparities. Additionally, it was discovered that the discrepancy between the detection length and the actual road length introduced volatility in repeated detection results, necessitating a limitation of this discrepancy to 30 m. Consequently, it has been recommended to consider the lateral distribution of pavement roughness and to regulate the detection length in road performance evaluations to enhance reliability and facilitate more accurate maintenance decision making. The study highlights the importance of incorporating comprehensive assessment approaches for pavement roughness in road management practices.

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