Abstract: This paper introduces an autonomous and cost-effective method for assessing cycleway pavement roughness, using an action camera equipped with high-resolution sensors including an Inertial Measurement Unit (IMU) and a Global Positioning System (GPS). The methodology utilizes simplified quarter car model for bicycles, without manual intervention, to calculate International Roughness Index (IRI) for cycleway surface quality evaluation. It utilizes our novel approach to determine stable section from which average acceleration orientation vector is computed. For analysis we propose a corrected-roughness index (CRI), which is a quantized version of IRI. Experiments conducted on asphalt cycleways in Ireland revealed strong correlations between vehicle vibration and surface roughness. Results further demonstrate the consistency of the proposed model across different bikes through comparative analysis. Observations indicate bias in vibration data, influenced by different tire sizes and the me
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