A Framework for Network Level Pavement Maintenance Planning for Low Volume Roads

Abstract

Low volume roads (LVRs) play a pivotal role in the economic development of rural areas especially by providing connectivity for the communities to access markets, education and social needs in an efficient manner. They serve as the link between the local road network to the arterial and collector road network designed at providing accessibility to residential, agricultural or industrial areas. Lack of funding, subjective and ad hoc decision making has resulted in an inefficent utilization of resources in the local road agencies. Lack of a sound analytical process is a major impediment to maintain these roads in cost effective manner under the resource constraints prevalent. Existing pavement management systems (PMS) require extensive data collection and complex analysis processes, which makes them impractical to be deployed in local agencies. The core attributes of the proposed system are, reduced the data requirements, simplified the analytical tools and allowing users to customize considering the resource constraints. In this study, a relationship between International Roughness Index (IRI) and relevant distresses for LVR is established and based on that cost estimation model is developed for distress repair. Furthermore, the strategy which provide maximum condition for preventive maintenance is found by using decision tree approach in the network level optimization. A case study illustrated that the use of proposed PMS provides better overall network condition with compare to conventional decision making for same budget level.