Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Achieving quality assurance in accepting automated pavement condition data: threshold development and error pattern analysis
Automated pavement condition survey systems are widely used for network-wide pavement distress detection, yet concerns about data quality remain. To address this, it is crucial to develop effective data quality assurance (QA) procedures. This study proposes two indexes for QA procedures: the accuracy index based on the differences between automated measurements and manual audit measurements, and the precision index based on the differences between automated measurements of two consecutive years. Using automated distress data (2017–2021) and manual audit data from Texas, the Difference of Two-Sigma (D2S) method was applied to determine the thresholds of various distress types for the accuracy and precision indexes. Then, a validation of the proposed thresholds was conducted by visually checking the 2022 image data of a selected pavement network. Through this process, the reliability of the thresholds was evaluated, and the error patterns present in the automated data were analysed. The study results demonstrated that the developed thresholds were able to effectively identify data quality issues. The primary source of errors in the automated condition survey system was false-positive detections of pavement distresses, frequently caused by features in the pavement surface background, primarily due to the textures of the pavements.
Achieving quality assurance in accepting automated pavement condition data: threshold development and error pattern analysis
Automated pavement condition survey systems are widely used for network-wide pavement distress detection, yet concerns about data quality remain. To address this, it is crucial to develop effective data quality assurance (QA) procedures. This study proposes two indexes for QA procedures: the accuracy index based on the differences between automated measurements and manual audit measurements, and the precision index based on the differences between automated measurements of two consecutive years. Using automated distress data (2017–2021) and manual audit data from Texas, the Difference of Two-Sigma (D2S) method was applied to determine the thresholds of various distress types for the accuracy and precision indexes. Then, a validation of the proposed thresholds was conducted by visually checking the 2022 image data of a selected pavement network. Through this process, the reliability of the thresholds was evaluated, and the error patterns present in the automated data were analysed. The study results demonstrated that the developed thresholds were able to effectively identify data quality issues. The primary source of errors in the automated condition survey system was false-positive detections of pavement distresses, frequently caused by features in the pavement surface background, primarily due to the textures of the pavements.
Achieving quality assurance in accepting automated pavement condition data: threshold development and error pattern analysis
Tao, Jueqiang (Autor:in) / Luo, Xiaohua (Autor:in) / Wang, Feng (Autor:in) / Faieq, Ajmain (Autor:in) / Gong, Haitao (Autor:in) / Qiu, Xin (Autor:in)
31.12.2024
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
| Taylor & Francis Verlag | 2023
Development of Automated Algorithms for Pavement Condition Survey
| British Library Online Contents | 1996
Development of Automated Algorithms for Pavement Condition Survey
| British Library Conference Proceedings | 1996