Consideration of Information Loss in the Transportation Asset Management Process

Abstract

Transportation asset management (TAM) relies on data to inform decisions on the maintenance or improvement of a given asset. Two of the essential data elements in the TAM process include the inventory, and the condition of an asset over time. Often, the condition is described using several factors, such as the amounts and types of cracking, and those factors are then combined to form a condition index. The index is frequently the basis for developing performance prediction models. However, when the condition of an asset is defined using a measure comprised of several metrics, the risk exists that considerable information could be lost or distorted from index-related calculations. Although the importance of the loss of information depends on the decision framework in which the asset is being managed, it does distort the relationship between the asset deterioration and the factors that drive that deterioration. This paper describes information loss using data and indexes from the U.S. National Park Service pavement network. The effect of the loss of information on the ability to develop performance prediction models is demonstrated. The aim was to present an approach for calculating information loss along with strategies for minimizing that loss. The results showed how loss of information can affect the ability to develop performance prediction models. The primary conclusion of this study is that information loss and -distortion should be evaluated for all condition indexes in an effort to minimize that loss and distortion.