Journal of Pavement Engineering, Vol.27
BASIC RESEARCH ON PAVEMENT DAMAGE DIAGNOSIS UTILIZING THE FEATURES OF PERIODICALLY COLLECTED PROBE DATA
2023 Volume 78 Issue 2 Pages I_171-I_181
Details
2023 Volume 78 Issue 2 Pages I_171-I_181
The road administrator routinely inspects pavements, however, the need for repair depends on the inspector's experience and knowledge, and the lack of skilled inspectors has made improving the efficiency of inspection work an urgent issue. As a solution to this problem, previous studies have diagnosed pavement damage during driving by using probe data that record the driving position and acceleration of vehicles. On the other hand, if probe data can be collected at the same time as daily inspections, it will be possible to identify damaged areas through damage diagnosis, analyze data trends over multiple time periods to understand the progress of damage, and predict future damage.
In this study, we attempt to apply LSTM, which is good at classifying and predicting time-series data, to the extraction of damage locations and damage prediction. As a first step, we constructed a pavement damage diagnosis model using LSTM and confirmed its usefulness with a damage extraction rate of about 80%.
