Integrating multi-scale inspection, maintenance, rehabilitation, and reconstruction decisions into system-level pavement management systems

Abstract

We are presenting a pavement management framework that involves multi-scale decisions, including system-level budget allocations, group-level inspections, and facility-level maintenance, rehabilitation, and reconstruction (MR&R) strategies. We consider two objectives: (i) to minimize the total discounted cost for the main stakeholders, represented by the agency and users; and (ii) to minimize the discounted user costs under a limited agency budget. Inspection technology innovations have enabled us to investigate the conditions of a group of multiple roadway facilities almost simultaneously, using instrumented vehicles that can travel at the same speed as traffic. Previous related studies have primarily focused on, at most, a bi-level structure with all the managerial activities, such as inspection and MR&R at the facility level and the allocation of a pooled budget at the system level. However, this cannot reflect the current group-level inspection practice, positioned between the facility and system levels. The proposed methodology adopts a bottom-up approach to account for heterogeneous facility- and group-specific properties, and it optimally facilitates determination of the multi-scale decisions to minimize the discounted societal costs. We address the complex multi-scale problem efficiently by adopting the Markov Decision Process, function approximation, and Lagrangian relaxation. As a numerical study, we analyze a real-world roadway network, including three expressway groups and one local road group, near Daejeon City in Korea. The system-level optimal solutions for the multi-scale decisions are determined, and the impacts of the grouping method are investigated.