Evaluating and Improving Asphalt Pavement in the City of Pittsburgh

Each year, the City of Pittsburgh resurfaces 50-90 miles of urban road, and the roads deteriorate over the years, adding an additional cost to both the City and residents. The ultimate goal of this research is to review the state-of-the-art asphalt pavement development, compare the mix, manufacturing and paving process of asphalt pavement being used in Pittsburgh with neighboring states, and make recommendations on the improvement of the durability of asphalt pavement for the City. This first phase of this research is to conduct thorough literature review of what factors attribute to the asphalt pavement to what degree, and compare the asphalt pavement process among several states in the northeast.

At the completion of this 8-week project, CMU will provide a report that will help the City better understand the state-of-the-art asphalt pavement development, compare the mix, manufacturing and paving process of asphalt pavement being used in Pittsburgh with neighboring states, and make recommendations on the improvement of the durability of asphalt pavement for the City.

Project Update (April 2020): 

The team observed three things:

• The one-size-fits-all design of HMA in Pittsburgh is likely to overspend materials and labors on secondary roads with mild or little traffic volumes.
• Experimental design and field observations would help better determine the most cost effective HMA (mixture types, asphalt binders, aggregates and RAP compositions) for Pittsburgh roads, when taking into account design service life, traffic volumes, traffic speeds, vehicle compositions (buses and heavy-duty trucks), thickness of the pavement, and equivalent single axle load (ESALs) on roads.
• Thin Hot Mix Asphalt Overlay (THMACO) could be used to preserve the pavement condition. Also, Pittsburgh can use Open Graded Drainage Layer (OGDL) to provide the pavement drainage system.

It is also recommended to adopt a data-drive approach to understand the underlying mechanism of pavement degradation with massive data collected over the last decade. Those data include, but are not limited to, the paving time and process of pavement, time, location and outcomes of pavement inspection and retrofit, weather conditions, traffic conditions, drainage design, bus operation, roadway design, roadways surface conditions, and any other factors that potentially affect pavement deterioration and in-service time.

The data-driven research, if successful, enables accurate models of pavement deterioration over specific location and time, as well as for short-term and long-term prediction of pavement quality, allowing decision making of pavement design, paving, retrofit projects and capital planning. It may be more cost-effective than traditional physical experiments of pavement materials.