Sensitivity Analysis of Highway Economic Requirements System Pavement Performance Models

Bryce, James; Elkins, G E; Thompson, Travis

doi:10.1061/jpeodx.0000150

Cited by 4 publications

(2 citation statements)

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“…Many agencies currently employ treatment decision matrices for pavement networks based on distress extent and severity (see [ 32 ]), which means that composite indexes are not necessary for treatment selection at the network level in the year that data are collected. Furthermore, much research has been conducted to develop performance models for distresses based on mechanistic-empirical principles (see [ 33 ]). Therefore, an approach to maintaining information is to predict distress growth as opposed to predicting the growth of a proxy value for that distress.…”

Section: Discussionmentioning

confidence: 99%

Consideration of Information Loss in the Transportation Asset Management Process

Bryce

2023

Transportation Research Record: Journal of the Transportation R

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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.

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Section: Discussionmentioning

confidence: 99%

Consideration of Information Loss in the Transportation Asset Management Process

Bryce

2023

Transportation Research Record: Journal of the Transportation R

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“…Although pavement performance models have been extensively reported in the literature for pavements that experience general public travel (e.g., Katicha et al ( 4 ), Bryce et al ( 5 ), etc. ), many challenges exist specific to the NPS pavement network.…”

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confidence: 99%

Evaluation of Pavement Performance Models Using Historical Condition Data for the U.S. National Parks Pavement Network

Bryce

Nichols

Elias

et al. 2023

Transportation Research Record: Journal of the Transportation R

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Pavement management, a subdivision of transportation asset management, seeks to use finite and limited resources to maintain or improve the condition of a pavement network for a defined time horizon. Pavement performance prediction is integral to pavement management, and among other uses, it contributes to budget projections and allows scenario analyses to be conducted. This paper documents the evaluation of the original pavement performance models developed for the U.S. National Park Service (NPS) pavement network using historical condition data. The Federal Lands Highway Program began to use a pavement management system for NPS pavements in 2005, and the results in this paper represent an evaluation of those models with an emphasis on developing recommendations for improvement. The main finding of the work presented in this paper is that the current NPS models result in significant overprediction of deterioration in practically all cases, although the effect is more pronounced for those measures associated with structural failure. This means that the NPS pavement network is in better condition than the models predict. The performance prediction models for those segments that received preservation treatments are also investigated in this paper, and it is found that the model bias is less for these than for the models predicting condition without a preservation treatment. However, this is attributed to the segments that received preservation treatments being in good condition. Overall, the findings point to a need to recalibrate or redevelop the models to improve their prediction capabilities.

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Reliability-Based Scheduling of Pavement Rehabilitation Considering Imperfect Repair

Das

Siddagangaiah

2022

J. Transp. Eng., Part B: Pavements

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Sensitivity Analysis of Highway Economic Requirements System Pavement Performance Models

Cited by 4 publications

References 4 publications

Consideration of Information Loss in the Transportation Asset Management Process

Consideration of Information Loss in the Transportation Asset Management Process

Evaluation of Pavement Performance Models Using Historical Condition Data for the U.S. National Parks Pavement Network

Reliability-Based Scheduling of Pavement Rehabilitation Considering Imperfect Repair

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