Using PMS Data to Identify Premature Cracking in Pavement

A roadway system is often the single largest financial investment for a public agency. Pavement is one of the most important assets in the infrastructure asset system. It is crucial to maintain pavement in good performing condition to ensure optimal and sustainable performance however, accelerated pavement deterioration has been of great concern to many stakeholders and transportation agencies due to the amount of money spent every year to rehabilitate newly constructed roads and mitigate the accelerated degradation in pavement condition. While premature cracking can be attributed primarily to different factors such as material properties, changes in climate conditions and traffic loadings, Pavement Management System (PMS) historical condition data represents a valuable source of information that can be used to investigate premature cracking in pavement and identify causes of early failure. This paper will present a methodology to use PMS collected condition data to identify premature cracking in pavements. Historical data collected over twenty years for the city of Ottawa will be used to observe city's roads performance over time. Historical construction data for major rehabilitation activities will be extracted from PMS database and linked to the historical condition data. Measured distresses will be scaled, indexed and an automated procedure will be established to identify scenarios for premature cracking incidents over the twenty years analysis period. Statistical analysis will be conducted to compare different distress indices and identify trends and predominant crack types that are highly impacting the pavement performance.