Road agencies provide maintenance work to serve a satisfactory level of road services to the public. However, as time goes on, pavement structure deteriorates for many reasons. Since repeated maintenance work upon deteriorated pavement structures can accelerate the deterioration speed, the pavements require periodic reconstruction work to recover original integrity. However, in the real world, it is difficult to carry out such a high level of maintenance work due to insufficient budgets, and no evidence for a guarantee of better economic efficiency. To support decision making in asset management, this study tries to define changing pavement performance by repeated maintenance work with empirical data. As an analytical tool, mixed hazard model with hierarchical Bayesian estimation method was applied. With the results, a best maintenance scheme on reconstruction timing was suggested by life cycle cost analysis. For the empirical study, a maintenance history data on Korean national highways, accumulated from 1965, was applied. The analysis procedures and results of this paper could be a good reference to build much realistic long-term maintenance strategy and reasonable budget allocation. In addition, the mixed hazard model with the hierarchical Bayesian estimation method is expected to be a useful tool in solving problems with heterogeneous population sampling, and in finding best practice and gaps among competitive alternatives.

The government of the Republic of Korea has set the minimum service level of bridges as Grade B and has defined the risk management level as higher than 95 percent. To achieve this goal, it is necessary to understand the deterioration process and risk of deficiencies for bridges, and these characteristics should be reflected in the management strategy and budget investment plan. To this end, this study developed deterioration models according to the bridge ages to define heterogeneous deterioration characteristics of aging bridges. To build the deterioration models, this study collected and processed bridge diagnosis data for 10 years, and a Bayesian Markov mixed hazard model was introduced. Analysis results showed that the life expectancy of the aging bridges over 30 years was remarkably short, 1/3 of the average life expectancy of the network, and the probability of failure was seven times higher than that of new bridges within 10 years after completion. In addition, the optimal maintenance demand that satisfies a risk management level of 95 percent illustrated that 44.7 percent of the bridges at Grade C should be continuously maintained annually. The results showed that it is urgent to prepare a preemptive response strategy and budget-securing plan for aging bridges, which will rapidly increase to 39% in the next 10 years and 76% in 20 years.

As the Framework Act on Sustainable Infrastructure Management has recently been enacted in Korea, it has become mandatory to establish a medium-and long-term plan for managing social infrastructure and evaluating the feasibility of maintenance projects. However, road agencies are experiencing problems due to a lack of deterioration models which are essential to conducting a life cycle cost analysis. Thus, this study developed deterioration models for bridge pavements as the first step to secure the power of execution of the Infrastructure Management Act. The deterioration model subdivided pavement materials into asphalt, conventional concrete, and latex-modified concrete. This study analyzed the data on diagnosis for the last 12 years in Korea by applying the Bayesian Markov Hazard Model. The average life expectancy by pavement type was analyzed as follows: 12.8 years for asphalt pavement; 23.4 years for concrete pavement; and 9.8 years for latex-modified concrete pavement. For the probabilistic life cycle cost analysis and risk management, probability distributions of life expectancy, effective range by confidence level, and Markov transition probability were presented. This study lays a foundation for deterministic and probabilistic life cycle cost analysis of bridge pavement. Future studies need to develop deterioration models standardized for all components of bridges and all types of social infrastructure.

Anti-frost layers in road pavement structures are widely applied to cold areas internationally. They mitigate cracks, potholes and roughness caused by the freeze–thaw phenomenon. Although the anti-frost layer design has been introduced to Korean road networks since the 1990s, its utility has not yet been empirically proven. This study attempts to evaluate the utility of the anti-frost layer with statistical methods using empirical data. As an analytical tool, the Bayesian Markov mixed hazard model for deterioration modelling and comparative analysis was introduced. In empirical studies, 8-year nation-wide network long-term pavement performance data (2316 sections) collected by the Korean Pavement Management System was applied. The analysis results signify that the anti-frost layer is good for prevention of cracks in network levels but is not enough for some cold areas with a freezing index of over 100. To secure the utility of anti-frost layers in the entire road network, it is necessary to revise the current Korean design standard.