Decision making for road infrastructures in a network based on a policy gradient method Available to Purchase

Developing proper maintenance and rehabilitation investment plans is vital for prolonging the service life of road infrastructures while preserving the required service level under capital constraints. This paper proposes a reinforcement learning approach for determining an optimal policy of selecting maintenance, repair and rehabilitation alternatives for a network of road infrastructure facilities. The proposed approach is based on a policy gradient method and overcomes the computational complexity of optimisation problems due to a large number of possible combinations of network conditions and maintenance, repair and rehabilitation alternatives. The developed optimal management policy takes into consideration interdependencies among infrastructure facilities in a road network. Numerical studies on concrete bridge decks in road networks are performed to demonstrate the advantage, feasibility and capability of the proposed approach.