Integration of optimization methodology to evaluate pavement maintenance strategies for deteriorated low-volume roads

Abstract

Low-volume roads (LVRs) are restricted with limited maintenance funding due to the recent national economic downturn. Only few selected LVRs with deteriorated pavements are typically rehabilitated in which poor LVRs are expected to continue deteriorating to extreme levels of distress. Colorado Department of Transportation (CDOT) is evaluating pavement treatments on LVRs to find the most cost-effective maintenance strategies. As part of these efforts, a comprehensive optimization analysis is adopted in this paper to investigate alternative maintenance strategies and define the capital improvement plans for deteriorated LVRs with marginal pavement conditions. A proposed strategy was found to enhance the effectiveness of current policies followed by CDOT. However, the results emphasize the need for additional resources at network level for dealing with deteriorated LVRs. The optimization procedure described in this paper can be followed by other agencies nationwide to identify strategies and establish funding needs that secure higher funding from decision makers.

Factors Affecting Maintenance Probability and Resurfacing Thickness Based on the Pavement Management System

“…In other words, M&R activities are always implemented when the performance indicators (such as RD, IRI, and PSI) meet the predefined threshold or trigger value, which indicates that a pavement is in a bad condition [8,9]. As a typical example of the "worst-first" approaches, hierarchical decision tree was frequently established because of their simple structure and easy to implement feature [10][11][12][13][14][15]. Generally, hierarchical decision tree is defined by a series of "if this occurs then this occurs" conditions that lead to a specific decision.…”