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Estimating pavement roughness using a low-cost depth camera
In a continuation of the Wyoming Technology Transfer Center (WYT2/LTAP) efforts to minimise the costs associated with the pavement condition assessment process, this study examined the capability of a low-cost depth camera (D435i) in measuring the International Roughness Index (IRI) as an indicator of pavement roughness. This study was performed on 48 pavement segments with various lengths and geometric features extracted from the Wyoming local roads database. A computer program was written specifically to control the camera, process the acquired data, and to return the final IRI values. The data was collected at posted speed limits. Noise reduction and hole filling techniques were applied to rectify the acquired depth data. It was found that a D435i depth camera can estimate the IRI of paved roads with a reasonable certainty compared to a standard profiler. The D435i depth camera can explain 83% of the variations in the actual IRI values measured using a standard road profiler. Statistical analysis showed no significant difference between both measurement methods at a 95% confidence level. The proposed approach has the potential to be a baseline for an inexpensive data collection system suitable for local agencies with limited budgets.
Estimating pavement roughness using a low-cost depth camera
In a continuation of the Wyoming Technology Transfer Center (WYT2/LTAP) efforts to minimise the costs associated with the pavement condition assessment process, this study examined the capability of a low-cost depth camera (D435i) in measuring the International Roughness Index (IRI) as an indicator of pavement roughness. This study was performed on 48 pavement segments with various lengths and geometric features extracted from the Wyoming local roads database. A computer program was written specifically to control the camera, process the acquired data, and to return the final IRI values. The data was collected at posted speed limits. Noise reduction and hole filling techniques were applied to rectify the acquired depth data. It was found that a D435i depth camera can estimate the IRI of paved roads with a reasonable certainty compared to a standard profiler. The D435i depth camera can explain 83% of the variations in the actual IRI values measured using a standard road profiler. Statistical analysis showed no significant difference between both measurement methods at a 95% confidence level. The proposed approach has the potential to be a baseline for an inexpensive data collection system suitable for local agencies with limited budgets.
Estimating pavement roughness using a low-cost depth camera
Aleadelat, Waleed (Autor:in) / Aledealat, Khaled (Autor:in) / Ksaibati, Khaled (Autor:in)
International Journal of Pavement Engineering ; 23 ; 4923-4930
06.12.2022
8 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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