Abstract

The method of evaluating pavement roughness with vibration acceleration data collected by smart phones is influenced by many factors, of which the length of pavement evaluation unit is an important one. In order to explore the influence of evaluation unit length on pavement roughness evaluation result with vibration data, this paper carried out a driving experiment, used the self-developed smart-phone APP acquisition running-vehicle vibration of data, used the multi-function checkout automobile detection of pavement smoothness, and established the relationship models of pavement roughness — vibration index and speed index when the evaluation unit length are 100 m, 500 m and 1000 m respectively. The results showed that when the unit length is 1000 m, the accuracy of the evaluation model is the highest, and the determination coefficient reaches 0.876. The verification experiment also proved that the evaluation model has good accuracy and stability. And also it was showed that the accuracy of the pavement roughness evaluation model increases with the increase of the length of the evaluation unit, which may be related to the matching error between the vibration data and the pavement roughness. How to improve the accuracy of the evaluation results about the short unit is the key content to be studied in the future.

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