Development of Cross-Asset Comparative LOS Condition Index

Comparing Level of Service (LOS) across infrastructure asset classes is difficult because of a lack of a common asset condition indicator. Some expert practitioners have suggested various types of asset value index as a common measure for comparing asset health but such an index, on its own, might mask the underlying level of service. In addition, quantifying risk and reliability is becoming ever more important when managing infrastructure assets.

 

Asset Condition Indices are often composites of several measured or estimated asset attributes. Pavement Condition Indices, for example, are often derived by deducting values representing many different pavement distresses from a perfect score. However, when a composite index is used, the underlying nature of the severity of distress or its extent is not evident directly from the index. One must refer to the underlying individual distress data to determine why the index got its ultimate value.

 

The magnitude of the deduct values are often somewhat subjective based on expert judgement relating to the relative severity of a given distress. In pavement, for instance, alligator cracking is seen to be more costly to repair than transverse cracking and is therefore given a larger deduct value resulting in a lower condition index. Although this may be reasonable for pavements, any mathematics behind the quantitative relationships between deduct values is not well documented in the literature. Quantifiable damage indices for pavements such as those used in the Highway Development and Management (HDM) framework have been in widespread use outside of North America and with the introduction of Mechanistic-Empirical Pavement Design Guide (MEPDG), are now gradually being adopted in North America providing a more consistently defined structure for quantifying pavement distress.

 

This paper briefly discusses the evolution of the classes of pavement indices from the traditional composite class indices through to damage indices and into those developed or now being developed to manage some other infrastructure classes including Infrastructure Value Indices.

 

The paper then puts forward a framework for incorporating risk and reliability with asset value indices in such a manner that both of these performance indicators could be compared across asset classes. Finally the paper describes a recently developed, damage based, LOS Index that can readily be applied to virtually any infrastructure asset class and that conveys not only the condition of the asset but allows Asset Managers to gauge the severity and density of distress through a single index number. The index can be readily implemented at any level of agency experience and requires no sophisticated data collection technology. The paper demonstrates the application of the technique through a municipal transportation infrastructure example.