Do vehicles sense pavement surface anomalies?

Charalambos Kyriakou, Symeon E. Christodoulou, Loukas Dimitriou
University of Cyprus, Cyprus

DOI: 10.35490/EC3.2019.159
Abstract: Nowadays, pavement monitoring agencies typically assess pavement quality approximately only once per year. The main reason for this low frequency of inspections is the fact that current methods are expensive and laborious. The paper presents a data-driven framework and related field studies on the use of pattern recognition techniques and smartphone sensor technologies for the detection, classification and georeferencing of roadway pavement surface anomalies. The proposed system provides continuous and reliable information about the five most common roadway pavement surface anomalies which are valuable for pavement management systems and public safety.
Keywords: Road Anomaly Detection, Smartphones Technology, Robust Regression, Bagged Trees
Pages: 56 - 64
Paper:
http://ec-3.org/conf2019/contribution_159_final/

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