Stochastic performance modeling considering maintenance effects for highway pavement management

Sun, L (2001) Stochastic performance modeling considering maintenance effects for highway pavement management. PhD thesis, University of Texas at Austin, USA.

Abstract

This dissertation presents concepts of transportation infrastructure performance modeling. The concepts are applied to pavement performance modeling and prediction involving various maintenance interventions. Methodologies, including regression analysis using explanatory variables and/or time as regressors, time series analysis and intervention analysis, are explored. Effects of six maintenance strategies on roughness are investigated based on actual field data obtained from a state Department of Transportation. It is found that, in general, maintenance improves ride quality and therefore should be used annually in practice to maintain the serviceability of highway transportation infrastructure. Models for predicting future roughness in terms of International Roughness Index (IRI) after a specific maintenance strategy are developed, which can be incorporated into existing pavement management systems to provide decision support for optimal benefit-cost maintenance strategy selection. A methodology is proposed to predict present serviceability index (PSI). Stationary and piecewise stationary renewal processes are used to model mixed traffic loading. Uncertainty in PSI modeling and prediction is formulated using rigorous statistical methods. The theory can be applied to other transportation infrastructure where regular condition data is taken for which the trend can be analyzed as a performance index, and where maintenance interventions are made in an effort to improve predicted performance.

Item Type: Thesis (Doctoral)
Thesis advisor: Hudson, W R and Kennedy, T W
Uncontrolled Keywords: decision support; uncertainty; highway; pavement; traffic; renewal; intervention analysis; regression analysis; time series
Index terms: time-series analysis, dissertation, loading, modelling, intervention analysis, regression analysis, transportation infrastructure, statistical method, strategy, time series, management system, decision support, renewal, methodology
Subjects: statistical analysis, infrastructure and transport systems, decision analysis, research evaluation and metrics, research methods, management, renovation and retrofit, analytical methods, data science, construction operations, data analysis and analytics, research dissemination and communication
Topics: Business Strategy, Research Practice, Site Management, Organizational Design, Risk Management, Engineering Principles
Descriptive scope: 4 PCTA

N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here