Economical methods for measuring road surface roughness

• Autorzy: Grabowski D. , Szczodrak M. , Czyżewski A.

Identyfikatory

DOI

10.24425/123905

• Języki publikacji: EN

Abstrakty

EN

Two low-cost methods of estimating the road surface condition are presented in the paper, the first one based on the use of accelerometers and the other on the analysis of images acquired from cameras installed in a vehicle. In the first method, miniature positioning and accelerometer sensors are used for evaluation of the road surface roughness. The device designed for installation in vehicles is composed of a GPS receiver and a multi-axis accelerometer. The measurement data were collected from recorded ride sessions taken place on diversified road surface roughness conditions and at varied vehicle speeds on each of examined road sections. The data were gathered for various vehicle body types and afterwards successful attempts were made in constructing the road surface classification employing the created algorithm. In turn, in the video method, a set of algorithms processing images from a depth camera and RGB cameras were created. A representative sample of the material to be analysed was obtained and a neural network model for classification of road defects was trained. The research has shown high effectiveness of applying the digital image processing to rejection of images of undamaged surface, exceeding 80%. Average effectiveness of identification of road defects amounted to 70%. The paper presents the methods of collecting and processing the data related to surface damage as well as the results of analyses and conclusions.

Słowa kluczowe

EN

image processing; neural networks; pothole detection; Kinect; Raspberry Pi

• Wydawca: Komitet Metrologii i Aparatury Naukowej PAN
• Czasopismo: Metrology and Measurement Systems
• Rocznik: 2018
• Tom: Vol. 25, nr 3
• Strony: 533--549
• Opis fizyczny: Bibliogr. 28 poz., fot., rys., tab., wykr., wzory

Twórcy

autor

Grabowski D.

• Gdańsk University of Technology, Faculty of Electronics, Telecommunications and Informatics, G. Narutowicza 11/12, 80-233 Gdańsk, Poland

autor

Szczodrak M.

• Gdańsk University of Technology, Faculty of Electronics, Telecommunications and Informatics, G. Narutowicza 11/12, 80-233 Gdańsk, Poland

autor

Czyżewski A.

• Gdańsk University of Technology, Faculty of Electronics, Telecommunications and Informatics, G. Narutowicza 11/12, 80-233 Gdańsk, Poland

Bibliografia

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Uwagi

EN

1. The research was subsidized by the Polish National Centre for Research and Development and the General Directorate of Public Roads and Motorways within the grant No. OT4-4B/AGH-PG-WSTKT. The authors would like to acknowledge Ms. Karolina Marciniuk for her contribution to collecting accelerometer measurement results.

PL

2. Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).