Detection of Unreported Treatments in Pavement Management System of Iowa DOT Using Machine Learning Classification Algorithm
Publication: Journal of Transportation Engineering, Part B: Pavements
Volume 148, Issue 4
Abstract
Treatment records are among the most frequently underreported data items in pavement management systems (PMSs), which negatively affects various PMS analysis tools, such as pavement performance and deterioration models. Disregarding unreported treatments may lead to inaccurate pavement age and condition estimates, resulting in erroneous and nonoptimal maintenance and rehabilitation decisions. Nevertheless, the unreported and frequently missing pavement treatment data has received limited attention. Hence, this paper contributes to the body of knowledge by introducing a methodology for detecting unreported treatment actions and their occurrence probabilities over pavement age using a machine learning classification algorithm. Logistic regression models were developed using historical pavement condition data and validated on two levels: (1) split validation; and (2) manual validation using video logs of the pavement condition before and after treatment application. The results show that the developed models can detect unreported pavement treatments with accuracy, precision, and F1 scores ranging from 89% to 96%, 82% to 91%, and 70% to 85%, respectively. The presented methodology and developed models will help highway agencies identify unreported and missing pavement treatments, contributing to more cost-effective maintenance and rehabilitation decisions.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request. The list of available models, codes, and data is listed below:
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The code of the machine learning classification algorithm is available upon request.
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The PMIS data is available online on the Iowa DOT open data website.
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Information & Authors
Information
Published In
Journal of Transportation Engineering, Part B: Pavements
Volume 148 • Issue 4 • December 2022
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Jun 13, 2021
Accepted: May 24, 2022
Published online: Sep 28, 2022
Published in print: Dec 1, 2022
Discussion open until: Feb 28, 2023
ASCE Technical Topics:
- Algorithms
- Architectural engineering
- Artificial intelligence and machine learning
- Building management
- Computer programming
- Computing in civil engineering
- Data analysis
- Engineering fundamentals
- Gravels
- Infrastructure
- Maintenance and operation
- Mathematics
- Methodology (by type)
- Pavement condition
- Pavements
- Research methods (by type)
- Systems engineering
- Systems management
- Transportation engineering
- Validation
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