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Title:

Detecting and Classifying Roadway Pavement Cracks, Rutting, Raveling, Patching, and Potholes Utilizing Smartphones

Accession Number:

01662663

Record Type:

Component

Abstract:

Civil engineers face numerous challenges in monitoring roadway deterioration and in assuring roadway pavement maintenance to the preferred level of serviceability. The paper presents a data-driven framework and related field studies on the use of supervised machine learning and smartphone sensor technologies for the detection, classification and georeferencing of common roadway pavement surface anomalies. The study proposes a low-cost and automated method to obtain up-to-date information about roadway pavement surface anomalies, with the use of smartphones mounted on vehicles. Robust regression analysis and bagged trees classification models are used to compliment smartphone-based data collection. The technology for the suggested system is readily available and accurate, and can be utilized in crowd-sourced applications for pavement management systems (PMS) and geographical information system (GIS) implementations. Further, the proposed methodology has been field-tested (detection and classification of five types of pavement surface anomalies, exhibiting accuracy levels higher than 90%) and at this time it is expanded to include larger datasets and a bigger number of common roadway pavement surface defect types. The proposed system is of practical importance since it provides continuous information about roadway pavement surface condition which can be valuable for pavement management systems and public safety.

Supplemental Notes:

This paper was sponsored by TRB committee AFD20 Standing Committee on Pavement Condition Evaluation.

Report/Paper Numbers:

18-02674

Language:

English

Authors:

Kyriakou, Charalambos
Christodoulou, Symeon E
Dimitriou, Loukas

Pagination:

14p

Publication Date:

2018

Conference:

Transportation Research Board 97th Annual Meeting

Location: Washington DC, United States
Date: 2018-1-7 to 2018-1-11
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References; Tables

Subject Areas:

Highways; Maintenance and Preservation; Pavements

Source Data:

Transportation Research Board Annual Meeting 2018 Paper #18-02674

Files:

TRIS, TRB, ATRI

Created Date:

Jan 8 2018 10:38AM