Virginia Department Of Transportation Research Articles

Distributed Traffic Signal Optimization at V2X Intersections

This paper presents our research on a traffic signal control system (TSCS) at V2X intersections. The overall objective of the study is to create an implementable TSCS. The specific objective of this paper is to investigate a distributed system towards implementation. The objective function of minimizing queue delay is formulated as the integral of queue lengths. The discrete queueing estimation is mixed with macro and micro traffic flow models. The novel proposed architecture alleviates the communication network bandwidth constraint by processing BSMs and computing queue lengths at the local intersection. In addition, a two-stage distributed system is designed to optimize offsets, splits, and cycle length simultaneously and in real time. The paper advances TSCS theories by contributing a novel analytic formulation of delay functions and their first degree of derivatives for a two-stage optimization model. The open-source traffic simulation engine Enhanced Transportation Flow Open-Source Microscopic Model (ETFOMM version 1.2) was selected as a simulation environment to develop, debug, and evaluate the models and the system. The control delay of the major direction, minor direction, and the total network were collected to assess the system performance. Compared with the optimized TSCS timing plan by the Virginia Department of Transportation, the system generated a 21% control delay reduction in the major direction and a 7% control delay reduction in the minor direction at just a 10% penetration rate of connected vehicles. Finally, the proposed distributed and centralized systems present similar performances in the case study.

Rutting Performance Evaluation of BMD Surface Mixtures with Conventional and High RAP Contents under Full-Scale Accelerated Testing.

The balanced mix design (BMD) constitutes a significant step forward in the pursuit of better-performing asphalt mixtures. This approach/framework offers increased innovative opportunities for the proper design and production of engineered asphalt mixtures without the need to strictly adhere to traditional volumetric requirements. The primary objective of this paper is to conduct a comprehensive investigation of the permanent deformation (rutting) behavior of surface mixtures (SMs) with conventional and high reclaimed asphalt pavement (HRAP) contents through full-scale accelerated testing under incremental loading conditions while accounting for the environmental aging effect. HRAP SMs were designed in this study, marking the initial application of Virginia Department of Transportation (VDOT) BMD special provisions, with attempts to incorporate 45% and even 60% RAP. Results showed that all BMD HRAP mixtures exhibited higher rut depths compared to the control mixture, which can be attributed to the inclusion of high binder contents aimed at enhancing cracking resistance. The asphalt pavement analyzer (APA) rut test and the stress sweep rutting tests were performed on mixtures sampled during production. Correlation analysis revealed significant and strong positive correlations between accelerated pavement testing (APT) and the multilevel laboratory rutting performance tests considered in this study. Finally, while acknowledging the limitations and all the assumptions considered in this study, the correlation analysis recommended refining the VDOT BMD APA rut depth threshold by lowering the current limit of 8 mm to 7 mm to ensure good performing mixtures from a rutting point of view.

Evaluating the Rutting Potential of Asphalt Mixtures with Simple and Practical Tests

The objective of this study was to explore the use of monotonic loading tests (“monotonic tests”) as screening tools to assess the rutting potential of dense-graded asphalt surface mixtures in Virginia. To that end, three monotonic tests—the indirect tensile at high temperature (IDT-HT) test, the rapid rutting (RR) test, and the Marshall stability and flow (MS) test—identified from the literature, were evaluated using 16 plant-produced asphalt mixtures with “A” and “D” designations. The scope of the work also included performing the multiple stress creep and recovery test on the extracted and recovered binders. The results were applied to assess the monotonic tests and the asphalt pavement analyzer (APA) test relative to each other using several performance metrics. The results were also employed to develop performance threshold criteria for the tests being considered. The results showed that the IDT-HT and RR tests can be used to screen the rutting potential of asphalt mixtures meeting the Virginia Department of Transportation (VDOT) mixture volumetric and gradation requirements for A and D mixtures. The initial performance criteria for the IDT-HT and RR tests were established for these mixtures. Based on the results, the IDT-HT test was found to be the most suitable alternative test to the APA test.

Multi-modal deep fusion for bridge condition assessment

Bridge condition rating is a challenging task as it largely depends on the experience-level of the manual inspection and therefore is prone to human errors. The inspection report often consists of a collection of images and sequences of sentences (text) explaining the condition of the considered bridge. In a routine manual bridge inspection, an inspector collects a set of images and textual descriptions of bridge components and assigns an overall condition rating (ranging between 0 and 9) based on the collected information. Unfortunately, this method of bridge inspection has been shown to yield inconsistent condition ratings that correlate with inspector experience. To improve the consistency among image-text inspection data and further predict the accordant condition ratings, this study first provides a collective image-text dataset, extracted from the collection of bridge inspection reports from the Virginia Department of Transportation. Using this dataset, we have developed novel deep learning-base methods for an automatic bridge condition rating prediction based on data fusion between the textual and visual data from the collected report sets.Our proposed multi modal deep fusion approach constructs visual and textual representations for images and sentences separately using appropriate encoding functions, and then fuses representations of images and text to enhance the multi-modal prediction performance of the assigned condition ratings. Moreover, we study interpretations of the deployed deep models using saliency maps to identify parts of the image-text inputs that are essential in condition rating predictions. The findings of this study point to potential improvements by leveraging consistent image-text inspection data collection as well as leveraging the proposed deep fusion model to improve the bridge condition prediction rating from both visual and textual reports.

Using mechanistic–empirical based analysis to evaluate rutting performance thresholds for balanced mix design tests

The balanced mix design (BMD) framework uses laboratory test methods to establish specifications that would ultimately be used for the design and acceptance of asphalt mixtures. Assembling such specifications is vital to optimizing the performance of asphalt mixtures for the distress of concern without violating any other criteria, consequently establishing the much desired “balance.” This research presents a stepwise method towards the establishment of performance test threshold criteria for rutting evaluation only as part of a greater effort that the Virginia Department of Transportation (VDOT) is pursuing for the implementation of the BMD framework. Data and discussion of five performance tests addressing rutting performance, along with six representative Virginia mixtures, are presented. AASHTOWare Pavement ME analyses at the material level and project level were utilized to fine-tune observations obtained using the surrogate test methods for rutting evaluation. Potential routes and accompanying challenges towards establishing/refining performance criteria that would prove helpful to the ultimate adoption of BMD specifications were outlined. An example of proposed performance criteria based on the presented data is provided. The proposed performance thresholds for rutting evaluation are intended as indicative; for full development and implementation, further refinement of the values is warranted.

Using Indirect Tensile Cracking Test Data for Quality Control and Acceptance

The Virginia Department of Transportation currently requires the use of the indirect tensile cracking test (IDT-CT) in accordance with ASTM D8225 in its balanced mix design specifications to evaluate the cracking resistance of several unmodified dense-graded asphalt surface mixtures. Although some studies have been performed, there is still limited information on testing processes that may have effects on the test results. This paper addresses the identification and assessment of factors that could have a significant effect on the cracking tolerance index (CT index) test results based on the IDT-CT when used for mixture quality control and acceptance by an agency, for example, specimen conditioning method, loading rate, and data collection frequency. Test results suggested that device type might be a significant factor for mixtures with relatively low CT index values. IDT-CT results were not dependent on the type of conditioning method (i.e., dry or wet). Further, they were not dependent on the loading rate applied, regardless of the machine type (servo-hydraulic or screw-drive) or the data collection frequency used over a range of 1 to 100 Hz. Sets of four and three test specimen replicates had single-operator and multi-laboratory precision estimates similar to those determined for five-replicate data sets.

Methodology to Predict Federal Performance Measures From State Performance Measures of Pavement Networks

Pavement management data used in measuring the performance of a pavement network contribute to managing maintenance and rehabilitation needs and determining the required funding levels. A network’s performance can be measured in several ways. The method adopted by the Virginia Department of Transportation has been in use for more than 15 years. With the introduction of Transportation Performance Management by the Federal Highway Administration (FHWA), a set of performance measures required by FHWA are to be reported. A few methods from earlier efforts by others in predicting one or more pavement performance parameters are briefly discussed. The main challenges in the determination of federal performance measures are the lack of prediction models for those measures; the reporting on 1/10th-mi sections that are not directly used in analysis and maintenance planning; and the determination of funding levels based on 1/10th-mi sections. In this paper, a new method to predict the federal performance measures of pavement networks from the state performance measures is provided, along with the mathematical models developed.

Developing novel pothole patching mixtures utilizing iron ore waste as substitute to conventional aggregates with anti-stripping agent

Development of potholes on roads and streets of prominent cities in India after the onset of monsoons is a common phenomenon. The remedy used for restoration of potholes is termed as “Patching” which prevents rapid pavement deterioration and provides smooth traffic flow. The present article aims at developing novel pothole patching mixtures utilizing Iron Ore Waste (IOW) as substitute to conventional aggregates (CA) with anti-stripping agent (ASA). Mix design, adhesion, cohesion, and moisture sensitivity of pothole patching mixtures were evaluated. Mix design properties were evaluated adopting the Marshall method, adhesion properties were evaluated as per Virginia Department of Transportation (DOT) test procedure, cohesion properties were evaluated as per AASHTO TP-44–94, and moisture sensitivity was evaluated using modified Lottman test. The strength of the initial and fully cured stages improved when IOW was substituted with conventional aggregates, and it was higher than 5.1 kN. As for Cohesion, every substance under investigation retained more than 60% of its original composition at the initial test conditions (4 °C and five blows). When tested at 25 °C and five blows, cohesiveness exhibited the same pattern as when tested at 4 °C. The findings of the adhesive test showed that IOW-Z has a maximum adhesion time of 35 s. Moreover, IOW-based pothole patching mixtures outperformed CA-based pothole patching mixtures in terms of resistance to moisture sensitivity. Results also indicate addition of ASA improved adhesion, cohesion, and moisture sensitivity properties of pothole patching mixtures regardless of aggregate type.

Monocular Camera Viewpoint-Invariant Vehicular Traffic Segmentation and Classification Utilizing Small Datasets.

The work presented here develops a computer vision framework that is view angle independent for vehicle segmentation and classification from roadway traffic systems installed by the Virginia Department of Transportation (VDOT). An automated technique for extracting a region of interest is discussed to speed up the processing. The VDOT traffic videos are analyzed for vehicle segmentation using an improved robust low-rank matrix decomposition technique. It presents a new and effective thresholding method that improves segmentation accuracy and simultaneously speeds up the segmentation processing. Size and shape physical descriptors from morphological properties and textural features from the Histogram of Oriented Gradients (HOG) are extracted from the segmented traffic. Furthermore, a multi-class support vector machine classifier is employed to categorize different traffic vehicle types, including passenger cars, passenger trucks, motorcycles, buses, and small and large utility trucks. It handles multiple vehicle detections through an iterative k-means clustering over-segmentation process. The proposed algorithm reduced the processed data by an average of 40%. Compared to recent techniques, it showed an average improvement of 15% in segmentation accuracy, and it is 55% faster than the compared segmentation techniques on average. Moreover, a comparative analysis of 23 different deep learning architectures is presented. The resulting algorithm outperformed the compared deep learning algorithms for the quality of vehicle classification accuracy. Furthermore, the timing analysis showed that it could operate in real-time scenarios.

Balanced Mix Design and Benchmarking: A Case Study in Establishing Performance Test Thresholds

A balanced mix design (BMD) approach for asphalt mixtures incorporates laboratory performance tests into the mix design acceptance process. However, test selection and subsequent performance thresholds must be selected, which is no easy endeavor when considering the number of promising tests and the variation in asphalt mix designs and components between states or regions. While the Virginia Department of Transportation’s (VDOT) BMD specification has been circulated for multiple years now, this article presents the approach taken by VDOT to investigate the various tests, considerations taken in selecting tests, and the establishment of performance thresholds. Data and discussion of six different performance tests encompassing durability, rutting, and cracking for 11 common Virginia mixes are presented. The performance threshold selection process is outlined. Further considerations in the final test selection process are discussed. In conclusion, the initial draft specification for BMD is provided.

Construction of a Composite Pavement (Asphalt over Concrete) in Virginia

The U.S. Strategic Highway Research Program 2 (SHRP2) identified composite pavement as a “renewal solution” and the Virginia Department of Transportation (VDOT) received implementation funding to demonstrate its feasibility. In 2017, this funding was applied to support major rehabilitation of two westbound lanes of US 60 in Henrico County, Virginia, a project that essentially replaced 1.1 mi of deteriorated concrete pavement with a new composite system consisting of continuously reinforced concrete pavement (CRCP) overlaid with stone matrix asphalt (SMA). This paper documents the design and construction of this new composite pavement. It also includes results from through-the-thickness temperature monitoring and a summary of performance for the first 4 years after opening to traffic. Close oversight by researchers provided a review of challenges and associated lessons learned from the design and construction process. Current VDOT specifications and standards were sufficient for successful construction. The asphalt overlay appeared to reduce the temperature gradient within the CRCP and to moderate daily temperature swings. This insulating effect of asphalt is expected to lower curling and associated stresses in the concrete pavement, which may permit reduced concrete thickness requirements in designs and also enable longer service life. The cracks in CRCP were tight and were not expected to reflect through the SMA. Moreover, the SMA mixture was tested to be crack and rut resistant. Therefore, a crack- and rut-free long service life for this composite pavement is expected. A recent visual survey by researchers found no observable distresses after 4 years under traffic.

Evaluating the Potential Environmental Benefits of Cold Recycling-Based Methods for Flexible Pavement Rehabilitation in Virginia

This paper describes a study conducted to quantify the potential environmental benefits of recycled asphalt pavement projects completed in Virginia. Three restorative maintenance projects were evaluated: (i) a 5-in. hot-mix asphalt (HMA) over 5-in. cold in-place recycling (CIR) with foamed asphalt stabilization; (ii) a 3.5-in. HMA over 5-in. CIR with emulsion stabilization; and (iii) one non-recycling structural overlay (5-in. HMA over an existing pavement). In addition, the following reconstruction projects—the first three constructed on primary roads and the last two constructed on interstates—were assessed: (i) a 2.5-in. HMA over 9.6-in. full depth reclamation (FDR) with asphalt stabilization; (ii) a 3.5-in. HMA over 9.0-in. cement stabilized FDR; (iii) a non-recycling reconstruction project (7-in. HMA over 12-in. aggregate base and subbase); (iv) a 6-in. HMA over 6-in. asphalt-stabilized cold central plant recycled layer over a 12-in. lime-stabilized FDR base; and (v) a non-recycling reconstruction project (8-in. HMA over 18-in. aggregate base and subbase). When considering exclusively cradle-to-laid system boundaries, the results show that pavement recycling projects used for interstate reconstruction and primary route restorative maintenance yielded lower global warming (GW) than non-recycling approaches. When considering the entire life cycle, the study found that approximately 98% of the total GW came from pavement–vehicle interaction that takes place during the use stage. Finally, to reduce GW, the Virginia Department of Transportation could encourage (or even incentivize) practices that improve the initial pavement smoothness for recycling projects and use structural designs that are expected to have a low annual deterioration rate.

Use of Solar Photovoltaic Energy Systems in Department of Transportation Facilities: A Review of Practice and Preliminary Assessment for Virginia Department of Transportation

Use of Solar Photovoltaic Energy Systems in Department of Transportation Facilities: A Review of Practice and Preliminary Assessment for Virginia Department of Transportation

High-Performance Fiber Reinforced Concretes in Virginia

High-performance fiber reinforced concretes (HPFRCs) provide high workability, high compressive and tensile strengths, high ductility, and high durability. They exhibit strain and deflection hardening. The Virginia Department of Transportation (VDOT), U.S., has been experimenting with various types of HPFRC, including high early strength versions, to control cracking in transverse and longitudinal connections, shear keys, blockouts that connect adjacent members, overlays, and inverts of corrugated metal pipe culverts. This paper presents laboratory and field work using three classes of HPFRC for different VDOT applications. They have high ductility and very low permeability. In addition, Class I has normal compressive strength, Class II has high compressive strength, and Class III has high early compressive strength. Laboratory work consisted of preparing and testing of in-house or prepackaged HPFRC with varying ingredients and proportions using compression, indirect tension, flexure, and pull-out tests. Synthetic and steel fibers were added in different amounts. Mixtures were prepared in the mortar or pan mixers that produce good fiber dispersion. Laboratory and field testing indicated that all three classes of HPFRC had high ductility; strengths varied according to the class. Engineered cementitious composite in Class I had normal strength, ultra-high-performance concrete in Class II had the highest strength, and concretes in Class III had high early strength, enabling minimal traffic interruption. HPFRC selected from an appropriate class can be used successfully to enable early opening to traffic, provide a short splice length, achieve satisfactory adjacent member connections, and restrict crack width for a longer service life.

Precision Estimates and Statements for Performance Indices from the Indirect Tensile Cracking Test at Intermediate Temperature

The Virginia Department of Transportation (DOT) has taken initiatives to implement the Balanced Mix Design (BMD) method to assure the long-term service life of its pavement network from a mixture quality standpoint. As part of this initiative, the cracking tolerance (CT) index obtained from the indirect tensile (IDT) test at intermediate temperature in accordance with ASTM D8225-19 was selected for evaluating the cracking potential of dense-graded surface asphalt mixtures. This prompted the need to generate the precision estimates (repeatability and reproducibility) for the test method for proper implementation during quality measurement practices. Thus, this interlaboratory study was undertaken to determine the precision estimates of the CT index calculated from the IDT test and to develop the associated precision statements. In addition, fracture strain tolerance (FST) and indirect tensile strength were included. Two asphalt mixes with significantly different CT index values were designed for the evaluation. Forty-six pairs of five replicate sets of compacted specimens (one set for each mix) were sent to 41 participating laboratories to be tested at 25°C. The test results were checked for data quality. The effects of loading rate and manufacturers on the indices were also evaluated. The test results indicated that one third of the sets were not tested in full accordance with the ASTM standard, indicating a need for training. The results also indicated that the specified loading rate of 50 ± 2 mm/min in ASTM D8225-19 for the IDT test may need revision. Finally, the precision estimates and associated statements for the three indices were presented.

Validation of Performance-Based Specifications for Surface Asphalt Mixtures in Virginia

The Virginia Department of Transportation (VDOT), like many owner agencies, is interested in ways to facilitate the increased durability of asphalt mixes in an effort to make its roadway network more sustainable, longer lasting, and more economical. The balanced mix design (BMD) method proposes to address this through the incorporation of performance criteria into mix design and acceptance. VDOT has committed to the implementation of the BMD method in an effort to improve asphalt mix performance. The purpose of this study was to continue advancing efforts toward implementation of BMD through the evaluation of 13 asphalt mixes using performance-indicating laboratory tests, validation of the initial performance tests selected for BMD use, and validation of the initial test threshold criteria. Based on the results, the asphalt pavement analyzer (APA) rut test, indirect tensile cracking test (IDT-CT), and Cantabro test were found suitable for continued use in BMD. The current threshold criteria for all three tests were found reasonable based on additional mix testing. The study recommends that APA rut test and IDT-CT results should be compared and correlated to fundamental rutting and cracking tests, respectively, as well as to performance predictions obtained from mechanistic-empirical pavement design simulations, and to field performance for full assurance that test threshold values are appropriate. It was further recommended to evaluate the Cantabro, IDT-CT, and APA rut tests to determine acceptable variability and establish precision statements.

Multi-Level Laboratory Performance Evaluation of Conventional and High Polymer-Modified Asphalt Mixtures

Asphalt concrete (AC) overlays have been one of the most common treatments used by the Virginia Department of Transportation (VDOT) for maintaining/rehabilitating pavements. However, when the overlay is placed on existing composite pavements or cracked AC pavements, differential movements across any cracks or joints can result in physical tearing of the AC overlay. Thus, the long-term performance of many AC overlays will highly depend on their ability to resist cracking. The purpose of this study was to assess the viability of using high polymer-modified (HP) AC mixtures in Virginia as a crack mitigation technique or when deemed appropriate as a tool for increased resistance to rutting and cracking on higher volume facilities. Another objective was to assess the ability of various testing protocols to discern the performance of pavements through a comprehensive evaluation of three conventional polymer-modified (PMA) and five HP field-produced mixtures placed in Virginia. This included laboratory testing at multiple levels of complexity (basic, intermediate, and advanced) on collected asphalt binders, plant-produced asphalt mixtures, and field cores. The performance characteristics of PMA and HP mixes were evaluated in the laboratory in relation to durability and resistance to rutting and cracking. Based on the mixes tested, stone matrix asphalt (SMA) mixes showed better performance than dense-graded surface mixes (SM) regardless of the asphalt binder type. Moreover, HP mixes showed better performance than PMA mixes regardless of the mixture type. Overall, SMA-HP mixes showed the most promising performance among all evaluated mixes.

Tightening Procedures for Proper Installation of Anchor Rods in Ancillary Structures

In the last 2 decades, many ancillary structures have collapsed, with several instances traceable to loose anchor nuts. According to a quality assurance inspection conducted by the Virginia Department of Transportation (VDOT) in 2012, approximately 30% of the anchor nuts on the inspected ancillary structures across the state of Virginia were found to be loose. The exact cause of the loose anchor nuts is not known; however, one theory is that specified tightening procedures were not properly followed or were not adequate. Currently, a turn-of-the-nut method is used for the tightening of anchor nuts on double-nut moment connections at the base of ancillary structures. This research reviewed current tightening procedures for anchor nuts on ancillary structures. The relationship between three critical tightening parameters—applied torque, nut rotation, and pretension in the rod—was examined. One hundred galvanized steel anchor rods of five different diameters and three different grades were tested. The experimental tests serve as a benchmark to validate the current tightening procedures, as well as to recommend changes.

Deep Learning-Based Visual Identification of Signs of Bat Presence in Bridge Infrastructure Images: A Transfer Learning Approach

Bat inventory surveys on bridges, structures, and dwellings are an important step in protecting threatened and endangered bat species that use the infrastructure as roosting locations. Observing guano droppings and staining is a common indicator of bat presence, but it can be difficult to verify whether certain stains originated from bats or other sources such as water seeps, rust staining, asphalt leaching, or other structural deterioration mechanisms. While humans find it hard to distinguish bat indicators without training, from a computer vision perspective they show different features that, coupled with expert opinion, can be used for automated detection of bat presence. To facilitate bat presence detection and streamline bat surveys, this paper leverages recent advances in visual recognition using deep learning to develop an image classification system that identifies bat indicators. An array of state-of-the-art convolutional neural networks were investigated. To overcome the shortage of data, parameters previously trained on large-scale datasets were used to transfer the learned feature representations. Using a pool of digital photographs collected by Virginia Department of Transportation (VDOT), a visual recognition model was developed and achieved 92.0% accuracy during testing. To facilitate the application of the developed model, a prototype web application was created to allow users to interactively upload images of stains on structures and receive classification results from the model. The web application is being deployed by VDOT in a pilot study and the success of the proposed approach is expected to help facilitate bat inventory surveys and the resulting conservation efforts.

Development of Roughness Prediction Models for Life Cycle Assessment Studies of Recycled Pavement Projects

The few existing life cycle assessment studies considering pavement recycling techniques usually omit the stages of maintenance and rehabilitation (M&R) and use. The reason for this omission is the lack of information about how the pavement’s performance evolves over time and absence of methods to determine the M&R frequency and service life for completed projects. As a result, the deterioration of pavement recycling projects in the long term is not clearly understood. Few projects have available data, the majority of which are on low volume primary and secondary roads. This paper describes an approach to develop a family of roughness models for recycling projects in Colorado using functional data analysis, and individual models for selected projects in Virginia to support ongoing life cycle assessment (LCA) studies. In the case of Colorado, full depth reclamation (FDR) projects will most likely deteriorate following an average group rate of 1.4 in./mi/year, with an initial international roughness index (IRI) between 52 and 70 in./mi. For the individual roughness models developed for Virginia projects, the initial IRI values and the rate of change for the treatments analyzed were found to range between 49 and 107 in./mi and between 0.7 and 5.2 in./mi/year, respectively, depending on the recycling method and type of stabilization treatment. The results of an LCA case study show that, in addition to recycling, Virginia Department of Transportation can achieve statewide emission reduction goals if focus is placed on achieving smoother roads while measures are taken to keep the annual rates of deterioration low.