Research Areas by Functional Context
Development of decision-support tools based on constrained multiple-objective optimization of infrastructure resources and investment tradeoffs.
In this research area, Dr. Labi and his research team have contributed to a variety of areas such as unprecedented methodologies for trade-off analysis in transportation asset management (his PhD student earned a national best thesis award for this work).
This includes techniques for incorporating uncertainty associated with the decision input factors and for generating Pareto frontiers, and modified methodologies for multi-objective optimization for project selection in network-level management of bridges, pavements, safety, and other highway assets.
He has made improvements to existing solution methods and algorithms for multi-criteria bridge management at the network level, assessed the computational efficiency of the existing and new algorithms, established a decision support system for optimal scheduling of highway maintenance, and developed a methodology for carrying out safety improvement programming for rural two-lane highways using constrained optimization at a system-of-systems level.
With regard to multiple objective optimization of asset management decisions based on risk and uncertainty, Dr. Labi and his team, in a series of research projects for the Indiana department of transportation and the National Academy of Sciences, developed and implemented methodologies for identifying and evaluating optimal investments decisions for the rehabilitation and renewal of physical infrastructure.
This includes the multiple-objective optimization for bridge management systems (where they developed optimization methodology and software module for PONTIS (now known as AASHTOWare Bridge Management software), the national bridge management package. This software package continues to be widely used as the primary bridge management software by transportation agencies across the U.S., and internationally.
In the analysis of performance trade-offs, Dr. Labi’s research includes the development of a new comprehensive methodology to facilitate the analysis of trade-offs in TAM by first establishing a general multiobjective optimization framework for TAM followed by development of a new, hybrid method for generating Pareto frontiers from which the performance trade-offs can be analyzed. The tradeoff curves help decision makers to not only quantify how different resource allocations affect system performance but also investigate the implicit barter relationships between different performance measures.
He has demonstrated that the new method quickens significantly the process of Pareto frontier generation for conducting trade-off analysis. Using data from real-life case studies, Dr. Labi and his team have automated the generation of the new hybrid method and showed that not only does it converge faster but also it yields better-distributed Pareto frontiers compared to existing methods. The generated Pareto frontiers are used in the industry to describe the trade-offs between cost and performance measures and between different pairs of performance measures. A successful quantification of these trade-offs is important for the practice because agency decision makers have long been stymied by a lack of knowledge of the extent to which different decisions lead to different performance trade-offs.
Derivation of theoretical constructs for assessments of infrastructure renewal effectiveness.
In this research area, Dr. Labi has made contributions in the following areas: development of theoretical constructs and statistics/econometrics-based methodologies to assess the effectiveness, in terms of the increased longevity or enhanced condition, of emerging classes of treatments applied to highway assets (pavements and bridges).
The treatments include rehabilitation, micro-surfacing, and thin HMA overlays, and the methodologies include analytical techniques that are multi-dimensional, aggregate, or disaggregate in nature.
In the short-term effectiveness of infrastructure interventions, Dr. Labi made available a set of mathematical constructs that analysts can use to quantify the long-term and short-term effectiveness of any treatment applied to an asset. For short-term effectiveness, he established three measures of effectiveness: deterioration reduction level, performance jump, and deterioration rate reduction each of which can be used in conjunction with any performance indicator.
More importantly, his research has exposed mis-estimation biases in past attempts in quantifying treatment effectiveness by drawing attention to (and resolving) the issue of relative timing between the date of the preservation application and the date of performance monitoring.rk-related performance measures for asset management); development of methodologies for using real options techniques in establishing snow options on the regional stock exchange and also for asset management intervention timing.
Development of methodological frameworks for region-wide investment decision-making and impact evaluation.
Dr. Labi has made methodological contributions related to the specific sub-areas: incorporation of safety in network-level transportation planning; linking interstate pavement preservation investment to performance; efficiency measurement of highway bridge replacement and rehabilitation and of the operational performance of public transportation agencies.
Other similar sub-areas where he has contributed include statistics-based methodology for assessing pavement performance levels across states in the USA; assessing preservation needs for a bridge network; assessment of the factors that influence highway safety, health care services, and motorization at various countries worldwide.
For the optimal performance thresholds for interventions, Dr. Labi and his research group developed a simulation-based optimization methodology for establishing optimal intervention application thresholds. The framework dimensions include benefits (infrastructure longevity vs. physical condition), agency vs. user cost considerations, and initial vs. life-cycle contexts. The research quantified the extent to which past practice can and does vary from optimal practice. The developed overarching methodology can be used to establish performance thresholds for various standard interventions not only in the management of transportation assets but also of systems in civil and other engineering disciplines.
With regard to the optimal intervals for infrastructures reconstruction, such methods include the use of mathematical models to track facility performance so that reconstruction can be applied at the right time. To this end, Dr. Labi’s research team developed a variety of novel mathematical constructs to derive stochastic life-cycle based functions that help agencies decide on the best time to reconstruct their facilities (a subject that is rarely addressed explicitly in infrastructure management); these mathematical functions duly considered the costs and benefits associated with each alternative timing strategy.
This is important in the present era of severe budget constraints and increased taxpayer scrutiny, where transportation agencies continue to face challenges in maintaining the condition of their infrastructure at acceptable levels of service with limited resources, a situation further exacerbated by the ever-increasing levels of travel demand and higher user expectation. As such, systematic and cost-effective methods of maintaining, upgrading, and operating physical assets and their usage, and ensuring operational accountability, are now being sought more than ever before.
Development of evaluation methodologies for innovative materials and processes in infrastructure development.
In this research area, Dr. Labi’s specific methodological and conceptual contributions have been in the following sub-areas: self-consolidating concrete; alternative steels for bridge deck reinforcement; and innovative/non-traditional materials for highway construction. His work on evaluating a new type of concrete using artificial intelligence has yielded papers that received 2 research awards: the 2008 K. B. Woods Prize for best TRR journal paper in design & construction awarded by the Transportation Research Board of the National Academies, and the 2007 Bryant Mather Prize for best paper in concrete materials awarded by American Society of Testing & Materials.
In this research, Dr. Labi and his team used standard coding languages to develop an image-processing-based methodology to automate the evaluation of the stability of self-consolidating concrete (SCC, a highly flowable, high-performance nonsegregating concrete); this was done by converting a typical concrete sample image (a cut surface) into a binary image of light colors (aggregates) and dark colors (concrete cement), identifying aggregate sizes, detecting the mortar layer thickness, and using statistical analysis to derive the hardened visual stability index (HVSI).
Prior to this research, the state of the art of HVSI measurement was rather rudimentary: visual assessment was used; however, this was prone to inefficiency and inaccuracies due to human error. Using the innovative methodology developed in this research, an analyst can digitally process a given concrete sample image and effortlessly assess its HVSI stability. This research represents a significant contribution to the practice because there continues to exist the need for inexpensive, quick, and reliable inspection of finished products, particularly new-generation materials such as SCC. Overall, this research is consistent with the ongoing national quest for intelligent and automated systems for quality assurance of materials used in infrastructure development.
In his research that assessed the efficacy of alternative steels for bridge deck reinforcement, Dr. Labi pioneered the development of methodologies to assesses, deterministically and probabilistically, the economic potential of stainless and clad steel as a bridge deck reinforcement materials compared to traditional steel, based on both agency cost and user cost in the long-term. The new methodology was demonstrated for multiple scenarios associated with the factors of economic evaluation within a Monte Carlo framework.
The contribution of this research was the development of a set of nomographs from which an analyst can identify the optimal reinforcement material type under a given set of conditions; optimality was defined in terms of the overall lifecycle costs. For the uncertainty situation, the research quantified the conditions under which the life-cycle cost for the stainless and clad steel options stochastically dominate that of traditional steel.
Development of Operational policies and fee structures for vehicle use on highways.
In this research area, Dr. Labi has made some methodological contributions in the areas of impact analysis of proposed changes in overweight truck operations legislation, and highway cost allocation and finance.
In the study that evaluated the impacts of proposed legislation for overweight trucking operations (requested by the Indiana House of Representatives), Dr. Labi and his research team made some innovative contributions: they developed a Geographic Information Systems (GIS) tool to facilitate overweight (OW) vehicle permitting administration; specified new user fees for overweight trucks on the basis of the consequences of deviations from the 4th-power law of pavement damage; estimated the marginal cost of life-cycle pavement maintenance and rehabilitation using in-service data; and developed an innovative generalized methodology to estimate the added bridge costs due to overweight trucks.
The research also developed a novel methodology to evaluate OW vehicle operations from an operations standpoint of mobility and safety, by quantifying each of the twin but opposing effects of traffic impairment and trips reduction associated with OW vehicles; the research ultimately established that the direction of the net effect of OW operations depends on the prevailing characteristics of the traffic stream and extent of overweight loading.
The impact of this research was felt in the region as led to a revision in the OW vehicle fee structure. In January 2015, this research was awarded an American Association of State Highway and Transportation Officials (AASHTO) Award for Best High Value Research Project in Region 3 of the United States.
In the research project that carried out highway cost allocation and revenue attribution, Dr. Labi and his team established equity factors for each user group and thus quantified the extent to which inequity exists among the groups. The research also made fee-related recommendations to achieve equity across the user groups, and established that automobiles, sport utility vehicles, vans, and pick-up trucks are overpaying their cost responsibilities by 10%; buses are overpaying their cost responsibilities by 4%; single-unit trucks are close to equity (underpaying by 0.01% of their cost responsibility) and combination trucks are underpaying by 23%.
The research is impactful because it is being used by the Indiana state government as it considers updating the vehicle license fee and registration structure, and also as a basis for implementing a potential statewide mileage-based fee for all vehicles to replace the traditional gas tax.
Project management and cost estimation in infrastructure development
In this research area, Dr. Labi has made methodological and conceptual contributions in a number of areas that include: infrastructure user cost estimation; asset preservation or replacement cost functions; planning-phase cost estimation; change orders in highway construction; and time and cost overruns in construction contracts.
In the area of spatial (global) considerations in the estimated costs savings in highway preservation, Dr. Labi and his collaborators have undertaken a number of research efforts that compared the two contracting approaches in terms of cost savings, and developed a methodology to investigate the underlying spatial dependence and heterogeneity associated with such data. The methodology they developed uses a spatial Durbin model that incorporated a spatially autoregressive dependent variable and a spatially lagged exogenous variable for the contract size.
This research identified as “hot spots”, specific African and Asian countries having negative spatial autocorrelation; and specific European and American countries having positive spatial autocorrelation. The contribution of this research also lies in the investigation of spatial interrelationships, a methodology that is popular in the social sciences but has failed to catch on in transportation systems engineering until this study was carried out. In investigating spatial dependency and spatial heterogeneity in the contract data, the research yielded a product that is particularly beneficial to international donor agencies and financial institutions that routinely make decisions on the selection of appropriate contracting approaches for their projects.
Regarding duration/prolongation of performance-based contracts that are emerging to address issues associated with lengthy workzones, road-user dissatisfaction and increased risk of litigation, Dr. Labi’s research has contributed to the global discourse on PBCs by examining the relationships between PBC duration and prolongation on one hand, and the factors that affect these outcomes on the other hand, while accounting for unobserved heterogeneity.
This is important because delays in the completion of highway projects represent key concerns to agencies, contractors, and the public due to adverse consequences. Dr. Labi and his collaborators determined that the Weibull model with gamma heterogeneity and the zero-inflated random parameters Poisson model best describe the PBC duration model and PBC prolongation model, respectively; this was a critical finding that can help agencies predict the duration of their performance-based contracts. The contribution of the research also includes quantification of the relationships between PBC project size and work scope on one hand, and PBC duration and prolongation on the other hand.
Dr. Labi has also made contributions in the areas of traffic engineering (where he has quantified the impact of vehicle travel characteristics on LOS in a manner that could be used to update the existing highway capacity manual; transit performance and cost analysis (where he has carried out the first and only statistical or econometric analysis of transit rolling stock costs of motorized bus and demand response modes, and also assessed the organizational efficiency of fixed-route transit agencies using data envelopment techniques); network connectivity and accessibility (where he has developed a methodology for quantifying network connectedness and accessibility for purposes of region-wide road maintenance planning, and developed the first formal set of network-related performance measures for asset management); development of methodologies for using real options techniques in establishing snow options on the regional stock exchange and also for asset management intervention timing.