Pricing of highway infrastructure for transportation asset management

Purpose The purpose of this paper is to present a methodology for estimating the “price,” or the not-to-loss value, of individual highway assets, which reflects not only the assets’ capital value but also economic productivity, by adopting a productivity-based asset valuation framework. The price tags can be used in prioritizing highway assets in support of transportation asset management processes. Design/methodology/approach The methodology adopts the utility theory to consider multiple performance measures reflecting the economic productivity generated by the assets, as well as their capital value. Key performance measures are first selected, and their values are retrieved from highway asset management databases. Next, the utility functions representing decision makers’ preferences convert the performance measures into utility values, which adjust the replacement cost (RC) of each highway asset to estimate price tags. To demonstrate its applicability, case studies were conducted for the highway networks of Texas and Washington State in the USA. Findings The methodology yielded price tags that better reflect the importance of highways’ roles in the economy in comparison to methods where only RCs are used. Furthermore, it was proven to be flexible enough to accommodate local conditions such as varying data availability. Originality/value The research provides a practical and reasonable way to prioritize critical highway assets in purport of maintenance and rehabilitation resource allocations, based on their economic productivity as well as physical condition and historical cost information, enhancing the overall efficiency and effectiveness of highway asset management.

Highway Asset Deterioration Rates

This paper is about highway asset deterioration rates. Typically, these are difficult to determine. However, using a data collection method adopted in North Carolina (and the resulting data obtained over a 5-year timespan), an approach was developed to determine accurate deterioration rates for several highway assets. This was not previously done, and thus, deterioration was not included as a factor in estimating future maintenance needs for these assets despite the ready availability of the necessary data. This paper focuses on unpaved shoulders and outlines how their deterioration rates were obtained and how such rates can also be obtained for other assets. The resulting deterioration rates are presented and compared over various road systems and geographical regions. With this new knowledge, deterioration rates can now be included in life cycle asset analysis, resulting in more accurate condition predictions and maintenance budgeting. The paper focuses on highway assets and does not address bridge or pavement maintenance.

Integrating Guardrail System Preservation Policies into Asset Management Practices

Asset management provides a strategic framework for infrastructure systems and focuses on getting the most out of their performance with the available resources. To determine future budget needs, highway agencies must have the necessary data and analytical tools with which to predict the performance of highway assets over time. Currently, transportation asset management systems are at different maturity levels. Pavement and bridges are considered the big ticket of all highway assets, but the preservation of signs, signals, lighting, guardrails, and pavement markings is also crucial to protect road users. Despite its importance, one of the safety assets with fewer asset management analytical tools is guardrail systems. Transportation agencies typically replace or repair guardrails that have endured major damage from car crashes. To implement a proactive preservation program, in agreement with transportation asset management practices, various parameters must be known. These parameters include inventory information, current guardrail condition, and performance models to forecast changes in the guardrail system condition over time. This paper describes a performance-based model with an analytical method to formulate a proactive preservation program for guardrail systems. The model was developed from inventory data and predicts changes in the guardrail system condition over time. A case study estimates the annual agency costs and backlogged costs over a 10-year analysis period. This model can be integrated into an asset management system to facilitate the formulation of preservation programs for guardrail systems at the strategic level.