In order to solve the urgent problem of how to manage and sustain highway tunnels with advanced information technology with the background of the rapid development in the modem traffic, and achieve the cost- effectiveness optimal principle objectives under the premise of guaranteeing a smooth flow of traffic; a highway tunnel maintenance and management system framework and the key modules were proposed. First, the determined highway tunnel condition assessment index system was established according to the result of expert consulting forms. Secondly, the tunnel diseases, the corresponding maintenance measurements, and many-to-many relationship between diseases and maintenance measurements were introduced. Then, three kinds of 0-1 integer programming models were built according to different tunnel operators＇ needs in the optimization decision module. Finally, the further development and implementation of the system was prospected. The research results can provide references to tunnel researchers and managers.
Taking variability and uncertainty involved in performance prediction into account, in order to make the prediction reliable and meaningful, a distribution-based method is developed to predict future PSI. This method, which is based on the AASHTO pavement performance model, treats predictor variables as random variables with certain probability distributions and obtains the distribution of future PSI through the method of Monte-Carlo simulation. A computer program PERFORM using Monte Carlo simulation is developed to implement the numerical computation. Simulation results based on pavement and traffic parameters show that traffic, surface layer material property, and initial pavement performance are the most significant factors affecting pavement performance. Once the distribution of future PSI is determined, statistics such as the mean and the variance of future PSI are readily available.
