ABSTRACT

Existing pavement management systems (PMSs) aggregate short survey sections into long homogeneous sections (typically 1–5 km), aiming to reduce the amount of data and formulate a tractable optimisation problem. However, assuming that sections in a similar condition will undergo a similar deterioration of this condition is incorrect, resulting in imprecise predictions and violations of thresholds. Thus, any maintenance and rehabilitation (M&R) optimisation approach based on long road sections and a single condition indicator (aggregated or not) cannot provide applicable results at the project level. This paper provides a holistic model framework and consistent methodology for a new PMS, abolishing the need for composite condition indices, data aggregation and homogeneous sections in the M&R optimisation process. The proposed bottom-up optimisation is based on short survey sections (25–50m) and solves for optimal treatment type, timing, work-zone length and layout, minimising agency, road user and environmental life cycle costs. Instead of using just one condition indicator, the method models the effects of each treatment on multiple distress types and their combinations. Moreover, the short survey sections are grouped into larger work zones based on purely economic criteria (i.e. economies-of-scale costs). Treatment cost, temporary traffic control cost, and work-zone user cost models are derived as a function of the project size and calibrated for actual prices in Austria. Genetic algorithms are employed as a part of the solution algorithm, being capable of handling an unlimited number of road sections. Furthermore, the approach can be extended to account for budget restrictions, risk and cross-asset allocation of funds for any aging repairable infrastructure system.

摘要

现有的路面管理系统（PMS）将短的勘测段汇总为长的均匀段（通常为1-5 km），旨在减少数据量并提出易于处理的优化问题。但是，假设处于相似条件的部分将经历此条件的相似恶化，这是不正确的，从而导致预测不准确和违反阈值。因此，任何基于长路段和单个状态指标（无论是否汇总）的维护和修复（M＆R）优化方法都无法在项目级别提供适用的结果。本文为新的PMS提供了一个整体模型框架和一致的方法，从而消除了M＆R优化过程中对复合条件索引，数据聚合和同质部分的需求。拟议的自下而上的优化基于短调查段（25–50m），并解决了最佳的处理类型，时间安排，工作区长度和布局，从而最大限度地减少了代理，道路使用者和环境生命周期成本。该方法不仅使用一种状况指标，还对每种处理对多种遇险类型及其组合的影响进行建模。此外，根据纯粹的经济标准（即规模经济成本），将简短调查部分划分为较大的工作区域。根据项目规模得出治疗成本，临时交通控制成本和工作区用户成本模型，并根据奥地利的实际价格进行校准。遗传算法被用作解决方案算法的一部分，能够处理无限数量的路段。此外，