The forest roads are the main integration mode between forests and companies. Therefore, there is a need for defining not only the required maintenance activities, but also the exact time for such intervention. Starting from this premise this paper presents the results of the assessment of two methods of classification of the quality of unpaved roads in order to verify which one reflects the field reality and thus can serve as the basis for a unpaved road management system. In this paper main defects in forest roads were measured following a method named Unsurfaced Road Condition Index (URCI) which served as a database for testing the efficiency of using artificial neural networks (ANN) in the management of forest roads taking into account costs minimization and traffic stoppage. It was concluded that the use of artificial neural networks showed superior performance that the URCI method.
Unpaved road; Forest transportation; Artificial neural networks
