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.

我们提出了一个涉及多尺度决策的路面管理框架，包括系统级预算分配、组级检查和设施级维护、修复和重建 (MR&R) 策略。我们考虑两个目标：（i）最小化主要利益相关者（以机构和用户为代表）的总折扣成本；(ii) 在有限的机构预算下最大限度地减少用户折扣成本。检查技术创新使我们能够使用能够与交通速度相同的仪表车辆几乎同时调查一组多个道路设施的状况。以前的相关研究主要集中在至多具有所有管理活动的双层结构，例如检查和 MR& R 在设施级别和系统级别的汇总预算分配。然而，这不能反映当前定位在设施和系统级别之间的组级检查实践。所提出的方法采用自下而上的方法来考虑异质设施和特定群体的属性，并且它最佳地促进了多尺度决策的确定，以最大限度地减少贴现社会成本。我们通过采用马尔可夫决策过程、函数逼近和拉格朗日松弛有效地解决了复杂的多尺度问题。作为一项数值研究，我们分析了韩国大田市附近的真实道路网络，包括三个高速公路组和一个地方道路组。确定多尺度决策的系统级最优解，