Danny Waiddanny.email@example.com email >
Iowa County Engineers Service Bureau
About the research
Recent federal legislation requires state highway agencies (SHA) and local road agencies to utilize performance-based approaches in their pavement management decision-making processes. The use of a remaining service life (RSL) model would be one such performance-based approach that could facilitate the pavement management decision-making process.
This study developed a Microsoft Excel macro and Visual Basic for Applications (VBA)-based Iowa Pavement Analysis Techniques (IPAT) automation tool that Iowa county engineers can use to estimate the project- and network-level pavement performance and RSL. To address this aim, statistics and artificial neural network (ANN)-based pavement performance and RSL models were developed using pavement structural features, traffic, construction history, and pavement performance records obtained from the Iowa Department of Transportation (DOT) Pavement Management Information System (PMIS) and the Iowa county agencies’ database. The accuracy of models was evaluated using real database representing Iowa county pavement systems.
The IPAT tool provides a series of options for four pavement types representing Iowa county pavement systems—jointed plain concrete pavement (JPCP), asphalt concrete (AC) pavement, AC over JPCP, and portland cement concrete (PCC) overlay—to estimate RSL through different approaches based on various conditions and distress data availability from an individual county. As part of data processing, the concept of developing an Iowa historical performance databank (HPD) was introduced and demonstrated by using raw data collected from county pavements. In addition, the feasibility of integrating preservation and rehabilitation techniques for RSL predictions using ANN models was investigated to evaluate the effects of treatments on RSL of pavements.
The IPAT tool is expected to be used as part of performance-based pavement management strategies and to significantly help decision-makers facilitating maintenance and rehabilitation decisions for better prioritization and allocation of resources.