Throughout the course of time and due to budget constrains agencies have changed their emphasis from construction of new roads to maintenance and rehabilitation of existing pavement structures. To achieve so, proper evaluation of the pavement's condition has been the principal source of information for effective road network management of state, city, and local transportation agencies. The necessity of obtaining the most benefit from limited funding led to the desire of Carson City and Douglas County's Public Works offices to implement a Pavement Management System for their networks. To achieve so, the Paver Software was selected as the common data management tool. Thorough data analysis of the pavement condition and work history data is necessary to obtain accurate performance prediction models. Lack of data was compensated with sewer line construction data and engineering judgment along with a three tier cleaning process. The current budget of both agencies was shown to be significantly lower than the necessary budget to maintain or improve the overall pavement network condition to an acceptable level. The reports generated serve the agencies to prioritize their spending through cost effective treatments, defend themselves against public criticism, and for requesting additional funding. Based on the findings from this study, it was recommended for local agencies to develop pavement management systems to apply the most cost effective treatments and obtain the most out of their limited budgets. A plan was provided on how to maintain and update the developed pavement management system.

In 2014, Wyoming Technology Transfer Center/Local Technical Assistance Program (WYT2/LTAP) initiated a pavement management system (PMS) program for county roads in the State of Wyoming. Building a PMS for county roads provides assistant and defensible tools for legislatures to allocate appropriate funds to maintain county roads. In Wyoming, there are total 2,444 miles of county paved roads managed and maintained under the supervision of local governments and municipalities. More than 50% of county paved roads have an average daily traffic (ADT) less than 400 vehicles per day. These roads are considered as low-volume roads. There is no legal requirement to implement a typical pavement management system on county and local roads. However, the funding constraints for maintaining county roads increase the importance of implementing a pavement management system on the lower systems. The most important issue in managing county paved roads as low-volume roads is to define practices and polices applied within the available resources. This study investigates appropriate tools to better manage low-volume paved roads. The tools provide effective guidelines and statistical techniques to reduce the costs of collecting pavement condition data. Online surveys were disseminated for all experts and pavement managers who are involved in preserving low-volume paved roads in Colorado and nationwide. This study developed four surveys. The summaries of only two surveys were included in this thesis since the two other surveys are in progress. A feedback from TRB standing committee members and specialist engineers in Colorado Department of Transportation (CDOT) was analyzed. The most appropriate practices and recommended tools were developed for managing low-volume paved roads using effective strategies. These strategies help local governments in Wyoming manage their county paved roads in a cost-effective manners. The automated techniques used to collect pavement condition data are relatively expensive for local agencies. In addition, there are questions about the needs to collect pavement condition data annually since county roads have relatively low traffic volumes. In order to optimize the cost of data collection, this study evaluates the possibility of reducing the amount of pavement condition data collected in each survey. Reducing the amount of collected data provides missing values. This study applies multiple imputation analyses as an assistant tool to predict the uncollected data at the network level. Another objective of this study is to determine the most cost-effective pavement condition data collection frequencies. The study uses a historical PMS data of the State secondary highways in Wyoming as a case study. A comparison between different frequencies was developed. It was concluded that uncollected pavement condition indices can be predicted using initial/historical values. The imputation models, developed in this study, provided a good estimation of the uncollected pavement condition indices. Therefore, pavement condition data of low-volume paved roads is not recommended to be collected for the whole network annually. Instead, a less expensive sequence can be adopted where the data which is not collected can be predicted using multiple imputation models developed in this study.