Using Sensing Technology for Pavement Performance Monitoring in Edmonton, Alberta

ABSTRACT
Pavements in cold regions are continuously under the influence of extreme climates, in addition to variable and ever-increasing traffic loads. Consequently, various types of structural failures can occur depending on specific circumstances and construction features. Thus, a well-planned pavement maintenance strategy must take place throughout the years to reach the designed service life and even sustainably extend the pavement structure's lifetime. An accepted and widely practiced process for continuous monitoring of the pavement conditions is collecting environmental and performance data using sensors installed in different pavement structural layers. In fact, the embedded instrumentation in the pavements can be an effective tool for capturing data such as temperature, moisture, and the induced stresses and strains within the pavement structure, allowing professionals in the field to determine the appropriate maintenance approach based on the collected information. This paper is divided into two main parts. The first part aims to provide a literature review on the sensors used for the instrumentation of pavements. Based on the review of different case studies, this study shows various applications of pavement sensors and their significance for analyzing pavement conditions. The second part of this study focuses on the instrumentation of a test section which was constructed in July 2022 in Edmonton, Alberta. This part mainly discusses the construction and instrumentation of the smart road test section and the application of artificial intelligence to predict the pavement performance based on the captured data.


Keywords: Pavement evaluation; Pavement response; Sensor type; Smart road; Instrumentation.

Author

Linares, Silas Henrique Barbosa De Carvalho
Huang, Yunyan
Moghaddam, Taher Baghaee
Shafiee, Mohammad
Hashemian, Leila
Bayat, Alireza

Session title

Innovations in Pavement Management, Engineering and Technologies

Category

Asset Management

Year

2023

Format

Paper

File

 


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