Samer Madanat | New York University (original) (raw)

Books by Samer Madanat

This chapter presents a methodology for maintenance optimization for heterogeneous infrastructure... more This chapter presents a methodology for maintenance optimization for heterogeneous infrastructure systems, i.e., systems composed of multiple facilities with different characteristics such as environments, materials and deterioration processes. We present a two-stage bottom-up approach. In the first step, optimal and near-optimal maintenance policies for each facility are found and used as inputs for the system-level optimization. In the second step, the problem is formulated as a constrained combinatorial optimization problem, where the best combination of facility-level optimal and near-optimal solutions is identified. An Evolutionary Algorithm (EA) is adopted to solve the combinatorial optimization problem. Its performance is evaluated using a hypothetical system of pavement sections. We find that a near-optimal solution (within less than 0.1% difference from the optimal solution) can be obtained in most cases. Numerical experiments show the potential of the proposed algorithm to solve the maintenance optimiza- tion problem for realistic heterogeneous systems.

Papers by Samer Madanat

These papers are organized from four sets of conference sessions: advanced technologies in transp... more These papers are organized from four sets of conference sessions: advanced technologies in transportation; transportation infrastructure management; information technology in transportation; and transportation planning and modeling. Topics include traveler information systems; data collection and estimation; information technology system (ITS) practices and technologies; incident detection and congestion management; advanced systems in hardware, information, and fuel; design, safety, and mobility; high speed transportation; advanced information systems and transportation policies; condition assessment; performance modeling of infrastructure systems; asset management; global information systems (GIS) and global positioning systems (GPS) applications; remote sensing and spatial data application; planning and modeling; emergency preparedness and responses; public transportation systems; application of genetic algorithms; simulation; application of artificial neural networks; and new ap...

New technologies that allow comprehensive, high-speed pavement inspections also require agencies ... more New technologies that allow comprehensive, high-speed pavement inspections also require agencies to make institutional adjustments in order to take full advantage of them. Agencies should change ratings systems to use the new 3-D capabilities, rather than continuing to rely on generically indexed values. Predictions about future decay can be more precise, which means managers will have to un-learn the tendency to over-compensate for uncertainty by repairing pavement before it needs to be fixed. Agencies can use the new information to develop maintenance scheduling models that incorporate new data and improve themselves over time. Managers and inspectors will need to acquire new skills to master these new techniques.

In the first part of this Innovations Deserving Exploratory Analysis (IDEA) project, efforts were... more In the first part of this Innovations Deserving Exploratory Analysis (IDEA) project, efforts were focused on developing and validating the freeway incident likelihood prediction models that form the core of a prototype system for real-time incident likelihood prediction. In the second part of the research, an incident likelihood prediction simulator was developed. This report describes the incorporation of the incident likelihood prediction models into the simulator. A traffic simulator (INTRAS) is used to generate the traffic characteristics (i.e., volume and speed) that are inputs to the freeway incident likelihood prediction models, whereas the environmental conditions are specified by the user. The simulator combines the sequential outputs from an existing incident detection algorithm and those of the incident likelihood prediction models through Bayesian updating.

Applications of Statistics and Probability in Civil Engineering, 2011

…, 2006

... Samer Madanat, Susan Shaheen, Caroline Rodier, Jim Misener, and Mark Miller California PATH G... more ... Samer Madanat, Susan Shaheen, Caroline Rodier, Jim Misener, and Mark Miller California PATH Genevieve Giuliano METRANS ... an initial investigation of the magnitude of the pavement dam-age problem (UCB-ITS-PWP-2005-5); a general review of legal and institutional ...

This is the second of two reports that present fatigue cracking performance models for asphalt co... more This is the second of two reports that present fatigue cracking performance models for asphalt concrete overlays placed on existing asphalt concrete pavement. The models were developed from the pavement management system (PMS) database of the Washington State Department of Transportation (WSDOT). The database included existing pavement structure, overlay thickness and type, truck traffic, and observed percent of the wheelpath cracked from annual condition surveys. Climate data was developed by the UCPRC to augment the WSDOT data. This report presents a model for crack propagation, starting from crack initiation, which was defined as 5 percent of the wheelpath with longitudinal cracking. The combined initiation and propagation models were included in a spreadsheet calculator which was used to perform an analysis of the sensitivity of crack initiation and propagation to the input variables. The models are extremely useful for predicting pavement performance. For use in California they...

Journal of Infrastructure Systems

Pavement deterioration models are an important part of any pavement management system. Many of th... more Pavement deterioration models are an important part of any pavement management system. Many of these models suffer from endogeneity bias due to the inclusion of independent variables that are correlated with unobserved factors, which are captured by the model's error terms. Examples of such endogenous variables include pavement overlay thickness and maintenance and rehabilitation activities, both of which are not randomly chosen but are in fact decision variables that are selected by pavement engineers based on field conditions. Inclusion of these variables in a pavement deterioration model can result in biased and inconsistent model parameter estimates, leading to incorrect insights. Previous research has shown that continuous endogenous variables, such as pavement overlay thickness, can be corrected using auxiliary models to replace the endogenous variable with an instrumented variable that has lower correlation with the unobserved error term. Discrete endogenous variables, such as the type of maintenance and rehabilitation activities, have been accounted for by modeling the likelihood of each potential outcome and developing individual deterioration models for each of the potential responses. This paper proposes an alternative approach to accommodate discrete endogenous variables-the selectivity correction method-that allows a single model to incorporate the impacts of all discrete choices. This approach is applied to develop a pavement roughness progression model that incorporates both continuous and discrete endogenous variables using field data from Washington State. The result is a roughness progression model with consistent parameter estimates, which have more realistic values than those obtained in previous studies that used the same data.

This work was performed as part of the California PATH Program of the University of California, i... more This work was performed as part of the California PATH Program of the University of California, in cooperation with the State of California Business, Transportation, and Housing Agency, Department of Transportation, and the United States Department of ...

University of California Transportation Center, Feb 19, 2004

The objective of this paper is to demonstrate the development of pavement performance models by c... more The objective of this paper is to demonstrate the development of pavement performance models by combining experimental and field data. A two step approach was used. In the first step a riding quality model based on serviceability consideration is developed. The data set of the American Association of State Highways Officials ͑AASHO͒ Road Test is used to this effect. Due to the experimental nature of the AASHO Road Test data set, some of the estimated parameters of the model may be biased when the model is to be applied to predict performance in the field. In the second step, the original model parameters are reestimated by applying joint estimation with the incorporation of field data set. This data set was collected through the Minnesota Road Research Project ͑MnRoad͒. The final model is referred to as the joint model, and it can be used to predict the performance of in-service pavement sections. Joint estimation allowed for the full potential of both data sources to be exploited. First, the effect of variables not available in the first data source were identified and quantified. Further, the parameter estimates had lower variance because multiple data sources were pooled, and biases in the parameters of the experimental model were corrected. Finally, different measurements of the same property were incorporated by using a measurement error model. Thus, the methodology proposed in this paper makes optimum use of available data and yields models of improved statistical properties compared with techniques such as ordinary least squares.

Transportation Research Record Journal of the Transportation Research Board, 2000

takes into account the appearance of various forms of distress such as cracking, rutting, ravelin... more takes into account the appearance of various forms of distress such as cracking, rutting, raveling, and faulting.

University of California Transportation Center, 2007

Bridge maintenance and replacement optimization methods use deterioration models to predict the f... more Bridge maintenance and replacement optimization methods use deterioration models to predict the future condition of bridge components. The purpose of this paper is to develop a framework for bridge maintenance optimization using a deterioration model that takes into account aspects of the history of the bridge condition and maintenance, while allowing the use of efficient optimization techniques. Markovian models are widely used to represent bridge component deterioration. In existing Markovian models, the state is the bridge component condition, and the history of the condition is not taken into account, which is seen as a limitation. This paper describes a method to formulate a realistic history-dependent model of bridge deck deterioration as a Markov chain, while retaining aspects of the history of deterioration and maintenance as part of the model. This model is then used to formulate and solve a reliability-based bridge maintenance optimization problem as a Markov decision process. A parametric study is conducted to compare the policies obtained in this research with policies derived using a simpler Markovian model.

Transportation Research Record, 1994

Journal of Transportation Engineering, May 1, 1995

Markovian transition probabilities have been used extensively in the field of infrastructure mana... more Markovian transition probabilities have been used extensively in the field of infrastructure management, to provide forecasts of facility conditions. However, existing approaches used to estimate these transition probabilities from inspection data are mostly ad hoc and suffer from several statistical limitations. In this paper, econometric methods for the estimation of infrastructure deterioration models and associated transition probabilities from inspection data are presented. The first method is based on the Poisson regression model and follows directly from the Markovian behavior of infrastructure deterioration. The negative binomial regression, a generalization of the Poisson model that relaxes the assumption of equality of mean and variance, is also presented. An empirical case study, using a bridge inspection data set from Indiana, demonstrates the capabilities of the two methods.