UC Berkeley

Greenhouse gas emissions reduction has garnered special importance in recent times in the transportation sector, including pavement design and management. In this study, we incorporate this environmental objective in pavement management. We present an optimization problem to minimize GHG emissions under multiple budget constraints by determining joint management strategies for a range of heterogeneous interventions, including maintenance, rehabilitation and reconstruction. We propose a computationally efficient bottom-up solution algorithm, which is built on Lagrangian Relaxation and Dynamic Programming. Finally, we apply our findings to a real-world highway network in California, where the results show a potential GHG emissions reduction of 20% through an increased combined budget of 35% on the Pareto frontier.