ABSTRACT
Pavement management systems are commonly used for assisting road pavement maintenance and rehabilitation decisions. In recent years, the optimization goal is shifting from minimizing purely economic consequences of pavement condition to broader sustainability related impacts. In this work, several socio-economic and environmental impacts, such as user delay, accidents, vehicle operating cost, fuel consumption, and emissions, are analyzed and assessed with regard to road pavement condition. An optimization model for pavement maintenance planning and resource allocation is developed on the basis of a generalized cost function. Due to the size and complexity of the optimization problem, a genetic algorithm is employed for solving it. Several scenarios have been tested considering a variety of pavement sections, traffic and initial pavement condition characteristics, and budget availability. Testing results have been found rational and indicating that the gain in generalized cost is far greater than the cost of pavement maintenance and rehabilitation.
