Development of holding strategies for deteriorated low-volume roads and evaluation of performance of Iowa test sections

Yu, Jianhua

doi:10.31274/etd-180810-4497

Cited by 2 publications

(2 citation statements)

References 10 publications

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“…In Nevada, CIR surfaced with a double chip seal was found to be a cost-effective rehabilitation alternative compared with a 2-inch overlay ( 8 ). Iowa DOT also recommends applying CIR with double chip seal or thin overlay to hold the condition of pavement at an acceptable service life ranging from 3 to 6 years ( 9 ). Despite extensive studies, knowledge gaps still remain in understanding when a particular pavement treatment should be applied.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Expert-Based Decision-Making of Pavement Maintenance using Artificial Neural Networks with Pattern-Recognition Algorithms

Hafez

Ksaibati

Atadero

2019

Transportation Research Record: Journal of the Transportation R

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Light pavement rehabilitations and low-cost treatments are extensively employed among transportation agencies on roads with relatively low traffic volumes to optimize available resources. One concern with this approach entails the difficulties of determining the optimal timing for treatment application. Making the best use of limited resources requires improvements in maintenance decision-making for selecting treatments considering all affecting factors and previous experience. This paper presents a machine learning approach in the decision-making process for determining the most appropriate pavement maintenance and rehabilitation alternatives for low-volume paved roads at the network level. Based on regional experts’ recommendations and engineering judgments in Colorado, a wide range of 884 cases of pavement-treatment patterns were generated. Then an artificial neural network (ANN) was trained with pattern-recognition algorithms. Two ANN prediction models were developed on the basis of pavement condition data, represented by six condition indices, and road lengths. The objective of training the models is to evaluate the variability of maintenance practices among five engineering regions within the Colorado Department of Transportation (CDOT). The outcome of this study describes the implementation gaps of pavement-preservation activities among CDOT regions resulting from limited maintenance funding. The regional maintenance selection can be processed by the developed ANN decision-making tool to recommend alternatives from regional recommendations as well as similar applications statewide to fit pavement management needs and expected performance.

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Section: Introductionmentioning

confidence: 99%

Optimizing Expert-Based Decision-Making of Pavement Maintenance using Artificial Neural Networks with Pattern-Recognition Algorithms

Hafez

Ksaibati

Atadero

2019

Transportation Research Record: Journal of the Transportation R

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“…Other state DOTs investigated the possibility to provide short-term solutions to maintain badly deteriorated pavements. In 2013, Iowa DOT recommends strategies to hold the condition of poor pavements of LVRs at an acceptable level until relevant rehabilitation funding is available (Yu et al 2015). Different combinations of hot-mix asphalt (HMA) overlay, cold in-place recycling (CIR), full-depth replacement (FDR), and chip seals were evaluated in Iowa.…”

Section: Introductionmentioning

confidence: 99%

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

2019

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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.

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Development of holding strategies for deteriorated low-volume roads and evaluation of performance of Iowa test sections

Cited by 2 publications

References 10 publications

Optimizing Expert-Based Decision-Making of Pavement Maintenance using Artificial Neural Networks with Pattern-Recognition Algorithms

Optimizing Expert-Based Decision-Making of Pavement Maintenance using Artificial Neural Networks with Pattern-Recognition Algorithms

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

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