Oklahoma Department Of Transportation Research Articles

Analyzing the Impact of Depreciation-Estimating Methods on State Transportation Agencies’ Equipment Replacement Decisions Using Dynamic Programming

Replacing equipment at the most economical time not only helps to save state transportation agencies (STAs) costs for operating the fleet but also keeps the fleet’s level of service at an optimal level. Prior research studies focused on developing alternative economic-oriented equipment replacement models rather than the equivalent annual cost (EAC) model to achieve better economic decisions. In addition, various optimization techniques were applied to equipment replacement problems with different objectives, constraints, and contexts. However, few studies examined the impact of depreciation estimation on the equipment replacement decision within STAs by minimizing total equipment cost over a finite study period using the dynamic programming optimization method. This study performed a case study of two class codes of equipment [1.5 m3 (2-yd) diesel engine front-end loaders and 0.453 t (half-ton) fleetside pickup trucks] to analyze the impact of different depreciation calculations on equipment replacement decisions. Using real-world data provided by the Oklahoma Department of Transportation, the study showed that the double-declining balance depreciation method substantially reduces the number of pieces of equipment recommended for replacement compared with the result of the straight-line depreciation method. This study contributes to the understanding of the impact of depreciation methods on equipment replacement decisions as well as the importance of properly estimating equipment depreciation to minimize the equipment costs over a designated study period among STA communities. The demonstrated manual calculation procedures of dynamic programming for cost optimization potentially may facilitate STA’s adoption of dynamic programming for equipment economic decisions.

Effect of chemical warm-mix additives on asphalt binder rheological and chemical properties in the context of aging

Warm-Mix Asphalt (WMA) has achieved gradually increasing popularity among researchers and agencies because of the environmental and economic benefits associated with lower production temperatures. An ongoing research study sponsored by the Oklahoma Department of Transportation (ODOT) is focusing on evaluating how different chemical WMA additives and the associated lower production temperatures impact asphalt binder and mixture properties and exploring potential relationships between asphalt rheology and chemistry in the context of chemical WMA and various aging conditions. This manuscript presents partial findings from this study that involved testing of two binder types (modified and unmodified binder) and four different WMA additives (chemical additives). Different aging conditions were simulated by changing the Rolling Thin Film Oven (RTFO) temperature, and by subjecting the binder to different cycles of Pressure Aging Vessel (PAV) aging. Frequency and Temperature Sweep tests by a Dynamic Shear Rheometer (DSR) and Bending Beam Rheometer (BBR) tests were performed for rheological characterization, while Fourier Transform Infrared Spectrometer (FTIR) test was conducted for chemical characterization. Analysis of the test results indicated that while all the WMA additives can improve the rheological and chemical properties of control binders at original and RTFO conditions, two additives cause inferior properties after 20 h, 40 h, and 60 h of PAV aging, indicating possible higher aging susceptibility and long-term performance concerns. Good correlations (R2 greater than 0.8) observed between binder rheological parameters and chemical indices indicate the existence of fundamental relationships between asphalt binder’s engineering properties and chemical make-up, which also supports the possibility of using FTIR as a quick screen or fingerprint tool for binder selection and comparison. Two new rheological parameters have been proposed for evaluation of the polymer-modified binder in this study. This was important to address the presence of multi-transition behavior in modified binders. These two parameters show consistent trends with increasing aging conditions.

Statistical Safety Performance Models considering Pavement and Roadway Characteristics

Transportation agencies build statistical models and predict the average crash frequency to identify hazardous road sections and make informed decisions to reduce crashes. In this paper, safety performance models (SPFs) were built and evaluated considering various pavement and roadway characteristics, including pavement friction, which is seldom available for analysis. Four count data models—Poisson model, negative binomial (NB) model, hurdle-NB model (HNB), and zero-inflated NB (ZINB) model—were built based on roadway characteristics and crash data provided by the Oklahoma Department of Transportation (ODOT). Pavement friction, roadway geometry, surface condition characteristics, and traffic exposure were considered the contributing factors to traffic crashes. Established models were compared in terms of the goodness-of-fit, zero inflation, and statistical significance of factors. The HNB model exhibited promising fitting performance with a manageable number of influencing variables. Coefficients in the HNB model suggest that adequate pavement friction and the presence of shoulders can significantly reduce the crash frequency and thus improve roadway safety performance. Potential issues of the statistical models, such as unobserved heterogeneity and multicollinearity, were also discussed. The relation between roadway infrastructure characteristics (including pavement friction) and roadway safety revealed in this study could assist in choosing the proper statistical model for better decision-making and selecting appropriate preventive treatments for improved roadway safety.

Field Monitoring of the Long Term Pavement Performance (LTPP) Warm-Mix Asphalt (WMA) Site in Oklahoma

As Warm-Mix Asphalt (WMA) moves into mainstream use, the lower WMA production temperature and injection of water in some WMA technologies have raised concerns on how it may affect short- and long-term field performance over the design life. Under the Long Term Pavement Performance (LTPP) Specific Pavement Study 10 (SPS-10) experiment initiative, the Oklahoma Department of Transportation (ODOT) constructed six testing sections with five different WMA methodologies and one HMA control section. This paper presents the application of several art-of-the-state high speed instruments to collect comprehensive array of pavement performance data for long term performance monitoring of this site. The newly developed 3D laser imaging technology is used to collect 1mm 3D surface data for the evaluation of pavement surface distress and transverse profiling for rutting. Longitudinal profiling for roughness and macro-texture for safety are acquired via a high speed inertial profiler, while pavement friction is continuously collected using a Grip Tester. Four data collection events have been performed since the construction of the site. Data collected on the WMA sections and the control HMA section are compared and evaluated for surface performance deterioration. It is demonstrated that the WMA sites using various technologies exhibit better or comparable performance relative to the conventional HMA, in terms of pavement cracking, rutting, and roughness. Aggregate properties and mixture design significantly impact the pavement macro-texture and skid resistance properties.

Classification and speed estimation of vehicles via tire detection using single‐element piezoelectric sensor

SummaryThis paper presents novel vehicle classification technology by utilizing a single‐element piezoelectric sensor placed diagonally on a traffic lane to accurately identify vehicles. Novelty of this technique originates from using diagonally placed piezoelectric strip sensor and machine learning technology to provide a highly accurate and cost‐effective alternative to current vehicle classification systems. Diagonal placements of the piezoelectric strip sensor ensure detection of passing vehicle tires by facilitating vehicle classification process. Presented technology is capable of accurately classifying vehicles into a relatively large number of classifications, including motorcycle, which has proven to be a challenging category in present‐day commercial vehicle classifiers. Vehicle classification is a vital intelligent transportation systems application. Accurate data reporting aids suitable roadway design for safety and capacity and can also support other purposes, such as reporting highway congestion to the general public or providing area denseness data to interested businesses.To make a classification decision, a vehicle's signal is acquired from diagonal piezoelectric strip sensor, processed, and then applied to a machine learning algorithm. A speed estimation technique using the same single‐element piezoelectric sensor was also developed, tested, and compared with an embedded vehicle classifier currently used by the Oklahoma Department of Transportation. Testing on several highway sites indicated up to 97% classification accuracy. This paper presents a complete description of the developed system, including sensor installation, data acquisition and processing, and classification algorithm. Overall, the system offers a high‐performance cost‐effective solution for vehicle classification that minimizes roadwork typically required for loop and sensor installations of current systems. Copyright © 2016 John Wiley & Sons, Ltd.

Network level pavement evaluation with 1 mm 3D survey system

The latest iteration of PaveVision3D Ultra can obtain true 1 mm resolution 3D data at full-lane coverage in all 3 directions at highway speed up to 60 mph. This paper introduces the PaveVision3D Ultra technology for rapid network level pavement survey on approximately 1280 center miles of Oklahoma interstate highways. With sophisticated automated distress analyzer (ADA) software interface, the collected 1 mm 3D data provide Oklahoma Department of Transportation (ODOT) with comprehensive solutions for automated evaluation of pavement surface including longitudinal profile for roughness, transverse profile for rutting, predicted hydroplaning speed for safety analysis, and cracking and various surface defects for distresses. The pruned exact linear time (PELT) method, an optimal partitioning algorithm, is implemented to identify change points and dynamically determine homogeneous segments so as to assist ODOT effectively using the available 1 mm 3D pavement surface condition data for decision-making. The application of 1 mm 3D laser imaging technology for network survey is unprecedented. This innovative technology allows highway agencies to access its options in using the 1 mm 3D system for its design and management purposes, particularly to meet the data needs for pavement management system (PMS), pavement ME design and highway performance monitoring system (HPMS).

Poisson Regression Analysis of Highway Fatality Accident Data in Oklahoma

Analysis of fatality automobile accident data can be challenging in rural areas where a relatively small number of such accidents occurs on specific sections of highways. Combining crash data from the Fatality Analysis Reporting System (FARS) and highway networks and design specifications from the Oklahoma Department of Transportation (ODOT), this article employs Poisson regression analysis to determine what roadway characteristics (e.g. grade, geometry, and design) are most associated with fatal accidents on predominantly rural segments of highways in Oklahoma. The results provide information about what combinations of highway design traits have contributed most to past crashes and therefore can identify potentially dangerous road segments system-wide. This information will help transportation engineers evaluate current construction practice and seek ways to address design issues that are shown to contribute significantly to serious crashes.

Influence of In-Isolation Properties of Geogrids on Their Pullout Performance in a Dense Graded Aggregate

A series of in-isolation and pullout tests was carried out on selected extruded (EGG) and non-extruded (NEGG) geogrid products that are available for base reinforcement and subgrade stabilization applications. The objective of the study was to examine the influence of selected geogrids index properties on their in-aggregate performance in roadway applications. The pullout tests were carried out in Oklahoma Department of Transportation (ODOT) Type-A aggregate, which is a dense-graded aggregate most commonly used in ODOT projects. Pullout tests provide useful information on the in-aggregate performance of geogrids outside the stress bulb directly beneath the tire pressure. The in-isolation properties studied included the geogrids low-strain (i.e. 2 and 5 % strain) rib strength, and ultimate rib strength and junction strength in both machine and cross-machine directions. Results of the study indicated that for both EGG and NEGG categories of geogrids examined, greater rib and junction strength properties overall resulted in greater pullout resistance. Geogrids junction strength and low-strain rib strength showed a reasonably strong correlation with their pullout performance regardless of the geogrid category examined. The rib strength at 2 % strain showed a stronger correlation than the 5 %-strain strength with the geogrid pullout performance. However, ultimate rib strength of geogrid showed convincing correlations with their pullout performance only when they were examined in separate categories with respect to their manufacturing technique (i.e. when the EGG and NEGG geogrids were examined as separate categories). The findings of this study are expected to be beneficial in relating the in-isolation properties of geogrids to their in-aggregate performance.

Feasibility of Implementing a Computer-Assisted Pavement Rehabilitation Decision Support System

Rehabilitation of urban highways is a critical issue confronting Department of Transportation agencies since most states have an inventory of highways that have exceeded their design lives. Delivery of cost-effective projects which minimize delays and traffic impacts of highway rehabilitation is needed. The Construction Analysis for Pavement Rehabilitation Strategies (CA4PRS) is a software program for predicting construction productivity during various closure timeframes for highway rehabilitation. This tool has been used in California and Washington among other states and has proved capable of providing significant scheduling and productivity inputs into early design planning. This study presents the results of evaluating the implementation and use of the CA4PRS by the Georgia Department of Transportation (GDOT) and the Oklahoma Department of Transportation (ODOT) in planning their highway projects. A knowledge inventory survey conducted at GDOT and ODOT is used to assess if the tool could be used in the context of Georgia and Oklahoma. Furthermore, the applicability of CA4PRS is tested in two case studies in an effort to evaluate its potential implementation.

Realistic Life-Cycle Cost Analysis with Typical Sequential Patterns of Pavement Treatment through Association Analysis

Advancements in data collection, digital data storage, and database management technologies have dramatically increased the capabilities of state highway agencies to generate and to store highway project data. The Oklahoma Department of Transportation (DOT), along with other state DOTs, stores a large amount of highway project data throughout the life cycle of highway projects. Although much of the budget is allocated to collecting and maintaining pavement data sets, the amount of benefit from extracting information and knowledge from the data is limited. This study applies association analysis in data mining to the historical treatment data set available in the Oklahoma DOT to identify the typical sequential patterns of treatment activities. Then, a realistic life-cycle cost analysis (LCCA) model based on typical sequential patterns of pavement treatment activities is developed and compared with the traditional LCCA performed by RealCost through an example. The case study indicates that the results of the realistic LCCA can be significantly different from those of the traditional approach. Because life-cycle cost models developed in this study are based on the actual treatment strategies performed by the Oklahoma DOT, it is expected that the life-cycle cost is closer to actual costs than the traditional approach. Using the realistic LCCA model developed in this study, state DOTs will be able to develop more realistic pavement maintenance and rehabilitation strategies and budgets.

Stiffness and drainage characteristics of unbound aggregate bases

This study focused on evaluating the effect of various gradations on the resilient modulus (<i>M_r</i>) and permeability of two-limestone aggregate bases, known as Dolese and Anchor. Three gradations, namely, upper limit of Oklahoma Department of Transportation (ODOT) Type A (UL-A), lower limit of ODOT Type B (LL-B) and lower limit of ODOT Type C (LL-C) were used to prepare specimens. Specimens were compacted at moisture contents drier than the optimum moisture using the same energy specified by the AASHTO T 180 test method. Results showed that the <i>M_r</i> values of specimens with UL-A gradation were higher than the <i>M_r</i> values for LL-C specimens, followed by LL-B. In addition, Dolese specimens exhibited higher <i>M_r</i> values compared to the corresponding values of Anchor. It was also found that the <i>M_r</i> values decreased with the uniformity of coefficient and the coefficient of gradation. On the other hand, the resilient modulus increased with the percent passing US Standard No. 200. In addition, higher coefficient of permeability (<i>k</i>) values were obtained for LL-B specimens, followed by LL-C and then UL-A. The <i>M_r</i> results determined in this study were within the range reported in the literature and the actual <i>k</i> values were lower than the <i>k</i> values predicted from existing regression models in the literature.

The impact of public information on bidding in highway procurement auctions

A number of papers in the theoretical auction literature show that the release of information regarding the seller's valuation of an item can cause bidders to bid more aggressively. This widely accepted result in auction theory remains largely untested in the empirical literature. Recent theoretical work has also shown that this effect can be more pronounced in auctions with larger common cost uncertainty. We examine the impact of a policy change by the Oklahoma Department of Transportation that led to the release of the state's internal estimate of the costs to complete highway construction projects. We perform a differences-in-differences analysis comparing bidding in Texas, a state that had a uniform policy of revealing the same information all throughout the period of analysis, to bidding in Oklahoma. Our results show that, in comparison to Texas auctions, the average bid in Oklahoma fell after the change in engineers’ cost estimate (ECE) policy. This decline in bids was even larger for projects where the common uncertainty in costs is greater. Moreover, the within-auction standard deviation of bids fell after the change in ECE policy with the most significant decline observed again in projects with greater common cost uncertainty.

Development of a Tool to Assess the Quality of Collected Pavement Management Data

Over the past 4 years, the Oklahoma Department of Transportation (ODOT) has implemented a pavement management system (PMS) to provide the agency with accurate, current, and relevant pavement condition information for use in prioritizing candidate pavement projects based on economic and engineering analyses. Now that the implementation process has been completed, ODOT routinely uses its PMS to enhance network- and project-level decision making. Currently, ODOT contracts with a vendor to collect network-level sensor, geometric, and distress data using automated data collection techniques. The data are then processed with a combination of automated and semiautomated techniques. The agency recognized that the value of the recommendations made by its PMS is greatly dependent on the quality of the collected information included in the PMS. Therefore, ODOT has emphasized the importance of checking the quality of data before they are used for important management decisions. As one way of assessing the data quality, ODOT developed checks of the data collected and submitted by the vendor. ODOT realized the value of creating an automated procedure for checking the final delivered pavement condition database to provide a rapid, repeatable, and accurate assessment of the data quality. To address this need, ODOT developed a visual basic application tool based on Microsoft Access to provide a user-friendly interface to the systematic procedure of conducting the many required data quality checks. In addition to the control and verification site testing procedures and distress ratings checks, this tool will be used by the agency as part of a comprehensive approach to assessing pavement condition data accuracy and completeness. Details regarding the creation and function of the quality assurance tool are provided in this paper.

Development of a Tool to Assess the Quality of Collected Pavement Management Data

Over the past 4 years, the Oklahoma Department of Transportation (ODOT) has implemented a pavement management system (PMS) to provide the agency with accurate, current, and relevant pavement condition information for use in prioritizing candidate pavement projects based on economic and engineering analyses. Now that the implementation process has been completed, ODOT routinely uses its PMS to enhance network- and project-level decision making. Currently, ODOT contracts with a vendor to collect network-level sensor, geometric, and distress data using automated data collection techniques. The data are then processed with a combination of automated and semiautomated techniques. The agency recognized that the value of the recommendations made by its PMS is greatly dependent on the quality of the collected information included in the PMS. Therefore, ODOT has emphasized the importance of checking the quality of data before they are used for important management decisions. As one way of assessing the data quality, ODOT developed checks of the data collected and submitted by the vendor. ODOT realized the value of creating an automated procedure for checking the final delivered pavement condition database to provide a rapid, repeatable, and accurate assessment of the data quality. To address this need, ODOT developed a visual basic application tool based on Microsoft Access to provide a user-friendly interface to the systematic procedure of conducting the many required data quality checks. In addition to the control and verification site testing procedures and distress ratings checks, this tool will be used by the agency as part of a comprehensive approach to assessing pavement condition data accuracy and completeness. Details regarding the creation and function of the quality assurance tool are provided in this paper.

The Impact of Public Information on Bidding in Highway Procurement Auctions

A number of papers in the theoretical auction literature show that the release of information regarding the seller's valuation of an item can cause bidders to bid more aggressively. This widely accepted result in auction theory remains largely untested in the empirical literature. Recent theoretical work has also shown that this effect can be more pronounced in auctions with larger common cost uncertainty. We examine the impact of a policy change by the Oklahoma Department of Transportation that led to the release of the state's internal estimate of the costs to complete highway construction projects. We perform a differences-in-differences analysis comparing bidding in Texas, a state that had a uniform policy of revealing the same information all throughout the period of analysis, to bidding in Oklahoma. Our results show that, in comparison to Texas auctions, the average bid in Oklahoma fell after the change in engineers' cost estimate (ECE) policy. This decline in bids was even larger for projects where the common uncertainty in costs is greater. Moreover, the within-auction standard deviation of bids fell after the change in ECE policy with the most significant decline observed again in projects with greater common cost uncertainty.

Stochastic synergies in sequential auctions

We consider sequential construction contracts in which bidders may benefit from one auction to the next due to synergistic tasks across the projects auctioned. Theoretical considerations indicate that winners in the earlier auctions are more likely to participate in later auctions. Moreover, conditional on participation, past winners place lower bids, on average, and are so more likely to win in later auctions. We present evidence in support of these predictions using sequential construction auctions conducted by the Oklahoma Department of Transportation.

Stochastic Synergies in Sequential Auctions

We consider sequential construction contracts in which bidders may benefit from one auction to the next due to synergistic tasks across the projects auctioned. Theoretical considerations indicate that winners in the former auctions are more likely to participate in latter auctions. Moreover, conditional on participation, past winners place lower bids, on average, and are so more likely to win in later auctions. We present evidence in support of these predictions using sequential construction auctions conducted by the Oklahoma Department of Transportation.

An Alternate Method to Determine Asphalt Content of Hot Mix Asphalt Using Volumetric Properties

Abstract Accurate determination of asphalt content (AC) in hot mix asphalt (HMA) is essential to evaluate the performance characteristics of HMA pavements. The standard test methods for determining the AC, currently used by the Oklahoma Department of Transportation (ODOT) and other DOTs and asphalt industries, are time-consuming, environmentally unsuitable, and not applicable to several absorptive and dolomitic aggregates. This study has developed a systematic method for the determination of AC using volumetric properties of aggregate, asphalt, and HMA mix. The developed method employed the theoretical maximum specific gravity (Gmm) of an HMA mix, the bulk and apparent specific gravity of the aggregate (Gsb and Gsa), and the specific gravity of the asphalt binder (Gb). The CoreLok™ device is used to determine the volumetric properties of the aggregate and HMA mix. This developed method is easy to use, environmentally safe, time efficient, and accurate. Three different aggregates were selected for the study based on varying gradation, absorption, and ignition oven correction (IOC) factor. HMA mixes were prepared with each of these aggregates using 5.0 %, 5.5 %, and 6.0 % AC. For each of the mixes, AC was calculated using the proposed method and compared with the actual AC value. The predicted AC values were compared with AC values from the ignition oven method (AASHTO T 308) and the solvent extraction method (AASHTO T 164). Results showed that the proposed method predicted the AC of HMA mix accurately. The method introduces a correction factor (Cv), which needs to be determined during the design stage and specified on the mix design information. The Cv value is used to calculate AC by the proposed method during quality assurance and quality control at the production and service life of HMA.

Variation of Resilient Modulus of Aggregate Base and Its Influence on Pavement Performance

Abstract Resilient modulus (MR), which properly characterizes the load-deformation response of pavement materials under traffic loading, is evaluated. The MR variations due to three different gradations and three different moisture contents were investigated for Richard Spur (RS) aggregate, which is commonly used in Oklahoma as the base material of roadway pavements. The three gradations selected are finer limit, median, and coarser limit, as specified by the Oklahoma Department of Transportation (ODOT) for Type A aggregate. The three moisture contents selected are optimum moisture content (OMC), 2% below and 2% above the OMC. Six duplicate MR tests under identical conditions were conducted for each case by using the AASHTO designation T 294-94. The variabilities of MR values due to the three different gradations and three different moisture contents were found to be within 10 to 50% and 10 to 20%, respectively. Furthermore, the material model coefficients K1 and K2 were calculated, and a multiple linear regression model for predicting the MR values of the aggregate was established in this study. Finally, the effect of MR variation on pavement performance was demonstrated by using one pavement design example.

Archaeological Investigations at 34WG220: A Prehistoric Occupation in the Arkansas River Valley of Eastern Oklahoma

In January and February of 1997, the Oklahoma Department of Transportation (ODOT) conducted archaeological work at site 34WG220 within right-of-way for a project involving realignment of SH-72 just south of Coweta, Wagoner County, Oklahoma. The site investigation consisted of the monitoring of trench excavation as well as controlled machine stripping. A few prehistoric artifacts, none of which are diagnostic, were found during the investigation. However, two cultural features were discovered during the monitoring of the trench excavation. The features were investigated by hand excavation of a 1 x 2 test unit.