South Carolina Department Of Transportation Research Articles

Full-scale experimental investigation of prestressed concrete bridge girders strengthened with aluminium channels

The bridge network in South Carolina encompasses more than 9,000 structures, many of which were originally constructed to accommodate H10 (89 kN) or H15 (134 kN) truck loads and thus require strengthening to carry current loading standard (HL-93). The South Carolina Department of Transportation (SCDOT) has recognized that prestressed concrete channel bridge girders, a specific type of bridge superstructure, often face challenges in achieving adequate load ratings, based on flexural strength. Hence, it is imperative to explore strengthening methods for these girders. Aluminium alloys possess desirable properties that make them attractive as external reinforcement materials. While previous studies have investigated the use of aluminium alloys on small-scale reinforced concrete members, there is a lack of investigation on their use on full-scale prestressed concrete bridge girders. To address this gap, this study investigates the feasibility of utilizing aluminium alloy channels as an external reinforcement material on full-scale prestressed concrete channel bridge girders. The main goal of this paper is to propose a strengthening method for prestressed concrete channel girders that is cost effective and easily implemented in the field to reduce the number of load-posted bridges in the state of South Carolina. Nine girders from recently decommissioned bridges in South Carolina were tested under flexural loading conditions to failure. The test program consisted of six unstrengthened girders, one strengthened with bonded aluminium channels (SE), one strengthened with bonded and bolted aluminium channels (SEB), and one strengthened with bolted aluminium channels (SB). Before testing, a visual inspection of the girders was conducted to identify any existing deterioration, and each girder was given a condition rating based on the Specifications for the National Bridge Inventory (SNBI). Theflexuralicate that externally anchored aluminium alloy channels with bolts was the most effective strengthening method in terms of practicality and increase in the flexural strength. Moreover, the results also revealed that the measured flexural strength of the girders varied based on the extent of the observed girder deterioration.

Use of Traffic Speed Deflectometer Data in Project-Level Pavement Rehabilitation Design

Current traffic speed deflectometer (TSD) analyses have focused on the application of pavement structural-condition data at the network level. Pavement management systems use the deflection data to adjust the treatment as determined from the surface deflections and ride quality, resulting in better treatment selection. However, TSD data can also be used at the project level to inform pavement design decisions, though this has yet to be well documented in the U.S. A pilot study was conducted in 2021 to develop a methodology to analyze the TSD data for the South Carolina Department of Transportation (SCDOT) based on the AASHTO 1993 overlay design methodology. The TSD analysis methodology determines the effective structural number for each TSD datapoint. The results generated from this analysis were used for an ongoing construction project to assess the structural condition of the pavement within the project limits. Grade restrictions on the project presented a challenge in determining limits of pavement reconstruction and pavement overlay. The results of the TSD analysis were used to characterize the effective structural number at a 52 ft interval, allowing for optimization of the limits of pavement reconstruction. This paper presents the TSD analysis methodology used and how SCDOT incorporated the TSD results at the project level to perform rehabilitation designs of an ongoing construction project.

Shear-wave velocity model of reference site conditions in South Carolina for site response analysis and probabilistic seismic hazard mapping

This paper presents the development of a shear-wave velocity (VS) model of reference site conditions in South Carolina for site response analysis and seismic hazard mapping. Model development involves creating contour maps of two geologic surfaces in the Coastal Plain with high contrasts in VS and combining the results with median VS profiles that extend to hard rock (VS ≥ 3000 m/s). Uncertainties associated with the contour maps of depth are captured in maps of the standard prediction error. Values of time-averaged VS in the top 30 m (VS,30) ranging from 1183 to 1538 m/s and 354 to 385 m/s characterize the reference site conditions in the Blue Ridge and Piedmont regions and the Coastal Plain region, respectively. The model is divided into 14 zones to facilitate site response analysis and to avoid over-smoothing resonances due to the impedance contrasts. This study is part of a larger effort to develop statewide probabilistic seismic hazard maps for the South Carolina Department of Transportation.

Extraction of Construction Quality Requirements from Textual Specifications via Natural Language Processing

Construction inspection is an essential component of the quality assurance programs of state transportation agencies (STAs), and the guidelines for this process reside in lengthy textual specifications. In the current practice, engineers and inspectors must manually go through these documents to plan, conduct, and document their inspections, which is time-consuming, very subjective, inconsistent, and prone to error. A promising alternative to this manual process is the application of natural language processing (NLP) techniques (e.g., text parsing, sentence classification, and syntactic analysis) to automatically extract construction inspection requirements from textual documents and present them as straightforward check questions. This paper introduces an NLP-based method that: 1) extracts individual sentences from the construction specification; 2) preprocesses the resulting sentences; 3) applies Word2Vec and GloVe algorithms to extract vector features; 4) uses a convolutional neural network (CNN) and recurrent neural network to classify sentences; and 5) converts the requirement sentences into check questions via syntactic analysis. The overall methodology was assessed using the Indiana Department of Transportation (DOT) specification as a test case. Our results revealed that the CNN + GloVe combination led to the highest accuracy, at 91.9%, and the lowest loss, at 11.7%. To further validate its use across STAs nationwide, we applied it to the construction specification of the South Carolina DOT as a test case, and our average accuracy was 92.6%.

Assessing the likelihood of secondary crashes on freeways with Adaptive Signal Control System deployed on alternate routes

Introduction: Reducing the likelihood of freeway secondary crashes will provide significant safety, operational and environmental benefits. This paper presents a method for assessing the likelihood of freeway secondary crashes with Adaptive Signal Control Systems (ASCS) deployed on alternate routes that are typically used by diverted freeway traffic to avoid any delay or congestion due to a freeway primary crash. Method: The method includes four steps: (1) identification of secondary crashes, (2) verification of alternate routes, (3) assessment of the likelihood of secondary crashes for freeways with ASCS deployed on alternate routes and non-ASCS (i.e. pre-timed, semi- or fully-actuated) alternate routes, and (4) investigation of unobserved heterogeneity of the likelihood of freeway secondary crashes. Four freeway sections (i.e., two with ASCS deployed on alternate routes and two non-ASCS alternate routes) in South Carolina are considered. Results and Conclusions: Findings from the logistic regression modeling reveal significant reduction in the likelihood of secondary crashes for one freeway section (i.e., Charleston I-26 E) with ASCS deployed on alternate route. Other factors such as rear-end crash, dark or limited light, peak period, and annual average daily traffic contribute to the likelihood of freeway secondary crashes. Furthermore, random-parameter logistic regression model results for Charleston I-26 E reveal that unobserved heterogeneity of ASCS effect exists across the observations and ASCS are associated with the reduction of the likelihood of freeway secondary crashes for 84% of the observations (i.e., primary crashes). Location of the primary crash on the freeway is observed to affect the benefit of ASCS toward freeway secondary crash reduction as the primary crash’s location determines how many upstream freeway vehicles will be able to take the alternate route. Practical Applications: Based on the findings, it is recommended that the South Carolina Department of Transportation (SCDOT) considers deploying ASCS on alternate routes parallel to freeway sections where high percentages of secondary crashes are found.

Assessment of Crash Location Accuracy in Electronic Crash Reporting Systems

Over the past several years, traffic fatality rates in South Carolina have been consistently ranked among the highest in the country. Furthermore, South Carolina incurs an annual economic loss of over two billion dollars because of roadway traffic crashes. The South Carolina Department of Transportation, in collaboration with the South Carolina Department of Public Safety, has undertaken a series of initiatives to reduce the number of vehicle crashes, with a particular emphasis on injury and fatal crashes. One of these initiatives is the deployment of a map-based geocoded crash reporting system that has greatly improved the quality of crash location data. This paper provides an assessment of improvements in crash geocoding accuracy in South Carolina and how improved accuracy is beneficial to systematic statewide safety analysis. A case study approach is used to demonstrate practical applications and analysis techniques based on spatially accurate crash data. A survey of U.S. state highway agencies indicates that there are disparate crash reporting systems used across the country with regard to crash geocoding procedures and accuracies. Survey results indicate that not only does geocoded accuracy of crash locations vary by state, but accuracies often vary by jurisdiction within each state. Research results suggest that poorly geocoded crash data can bias certain types of safety analysis procedures and that many state safety initiatives, analysis methods, and outcomes can benefit from improving crash report geocoding procedures and accuracies.

Evaluating the impact of traffic volume on air quality in South Carolina

Abstract Many studies have reported associations between respiratory symptoms and resident proximity to traffic. However, only a few have documented information about the relationship between traffic volume and air quality in local areas. This study investigates the impact of traffic volume on air quality at different geographical locations in the state of South Carolina using multilevel linear mixed models and Grey Systems. Historical traffic volume and air quality data between 2006 and 2016 are obtained from the South Carolina Department of Transportation (SCDOT) and the United States Environmental Protection Agency (EPA) monitoring stations. The data are used to develop prediction models that relate Air Quality Index (AQI) to traffic volume for selected counties and schools. For the counties, two models are developed, one with Ozone ( O 3 ) and one with PM 2.5 as the dependent variable. For the schools, only one model is developed, with O 3 as the dependent variable. The number of counties and schools studied are limited by the availability of air monitoring stations dedicated to measuring O 3 and PM 2.5 . Several types of models were investigated. They include linear regression model (LM), linear mixed-effect regression model (LMER), Grey Systems (GM), error corrected GM (EGM), Grey Verhulst (GV), error corrected GV (EGV), and LMER + EGM. The LM model produced the least accurate estimate while the LMER + EGM model produced the most accurate estimate (average RMSE is less than 5%). The models’ estimates suggest that air quality in South Carolina will continue to get worse in the coming years due to increasing AADT. An interesting finding of this study is that some counties and schools will have higher levels of O 3 or PM 2.5 when AADT decreases. This finding suggests that there are other factors, other than AADT, that influence the air quality in these counties and schools.

Legal Issues When Managing Public Roads Affected by Sea Level Rise: South Carolina

In South Carolina, sea level rise and sinking land surface means that the coastal areas of the state will experience a relative sea level rise ranging between approximately 0.5 to 1.5 feet in 2030, 0.75 to 3.2 feet in 2050, and 1.75 and 10.8 feet by 2100. These ranges are based on scenarios that encompass uncertainties about physical processes and about future levels of greenhouse gas emissions. They cover low rates of sea level rise and low greenhouse gas emissions to high rates of sea level rise and high greenhouse gas emissions to convey the future risks for the purpose of long-term decision making. Many communities are already experiencing impacts of recurrent flooding, sometimes called nuisance flooding, associated with “king tides” and meteorological events. For the state and county and local governments, sea level rise and increased flooding pose a significant, costly, and persistent threat to roads and highways. These natural disasters and chronic flood damages will inevitably encourage South Carolinians to reconsider the status quo of road maintenance and repair. Under projected sea level rise, repetitive or severe damages will lead to tough decisions about whether to decrease routine maintenance, transfer control of the roads to different government authorities, or abandon existing roads. Although the South Carolina Department of Transportation (SCDOT) owns more than 50% of the roads and highways across the state, adaptation efforts related to road maintenance and abandonment can be expected to occur at both the state and local levels. The state, towns, cities, and counties have legal responsibilities to maintain roads, and they all certainly have an interest in ensuring that roads are safe and maintained. This white paper discusses how South Carolina law may impact local governments that are facing the effects of coastal flooding on their public roadways. The paper first outlines the statutory basis for road ownership and the duties that flow from such ownership. It then reviews potential causes of actions resulting from the breach of duties of maintenance and good repair. Finally, it addresses the procedural requirements for formal road abandonment and takings liability from loss of road access.

Development of Statewide Annual Average Daily Traffic Estimation Model from Short-Term Counts: A Comparative Study for South Carolina

Annual Average Daily Traffic (AADT) is an important parameter for traffic engineering analysis. Departments of Transportation continually collect traffic count using both permanent count stations (i.e., Automatic Traffic Recorders or ATRs) and temporary short-term count stations. In South Carolina, 87% of the ATRs are located on interstates and arterial highways. For most secondary highways (i.e., collectors and local roads), AADT is estimated based on short-term counts. This paper develops AADT estimation models for different roadway functional classes with two machine learning techniques: Support Vector Regression (SVR) and Artificial Neural Network (ANN). The models predict AADT from short-term counts. The results are first compared against each other, using the 2011 ATR data, to identify the best models. Then, the results of the best models are compared against both the regression-based model and factor-based model. The comparison reveals the superiority of the SVR model for AADT estimation for different roadway functional classes over all other methods. Among models for different roadway functional classes, developed with the 2011 ATR data, the SVR-based models show minimum errors in estimating AADT compared to the ANN-based, regression-based, and factor-based models, depicting the superiority of the SVR-based model for all roadway functional classes over other models in terms of AADT estimation accuracy. SVR models are validated for each roadway functional class using the 2016 ATR data and short-term count data collected by the South Carolina Department of Transportation (SCDOT). The validation results show that the SVR-based AADT estimation models can be used by the SCDOT as a reliable option to predict AADT from the short-term counts.

Impacts of State-Specific Policy and Legislation on Safety Advancement by Departments of Transportation

The overall goal of this research was to identify proven successful safety programs used in other states and assess the potential for safety improvement if similar programs were implemented in South Carolina. The research team not only sought out engineering solutions, but also expanded the search to include programs for enforcement, education, licensing, legal proceedings, and emergency services—therefore incorporating a wide range of stakeholder groups. South Carolina has, for many years, had one of the highest mileage death rates of any state in the nation—far exceeding the national fatality rate. While South Carolina Department of Transportation has a federal requirement to develop and maintain the Strategic Highway Safety Plan, which identifies the state’s key safety needs and guides investment decisions toward strategies and countermeasures with the most potential to save lives and prevent injuries, South Carolina legislation and state policies have effectively blocked many paths to safety improvements. Tree protection ordinances, limited policies for graduated drivers licensing, bans on camera enforcement, and lack of universal helmet laws continue to undermine efforts to improve motor vehicle safety in the state. Using a data-driven approach to safety program selection will yield support for changes in programs, policies, and standards, and have positive impacts on safety, operational, and economic aspects of the South Carolina roadway system. Further, the implementation of a data-driven safety management program will help to assure that the most appropriate strategies are implemented. The successful implementation of this research would likely result in a substantial reduction in loss of life and injuries associated with motor vehicle crashes in the state of South Carolina.

Highway Cross-Slope Measurement using Mobile LiDAR

Ensuring adequate pavement cross-slope on highways can improve driver safety by reducing the potential for ponding to occur or vehicles to hydroplane. Mobile laser scanning (MLS) systems provide a rapid, continuous, and cost-effective means of collecting accurate 3D coordinate data along a corridor in the form of a point cloud. This study provides an evaluation of MLS systems in terms of the accuracy and precision of collected cross-slope data and documentation of procedures needed to calibrate, collect, and process this data. Mobile light detection and ranging (LiDAR) data were collected by five different vendors on three roadway sections. The results indicate the difference between ground control adjusted and unadjusted LiDAR derived cross-slopes, and field surveying measurements less than 0.19% at a 95% confidence level. The unadjusted LiDAR data incorporated corrections from an integrated inertial measurement unit and high-accuracy real-time kinematic GPS, however it was not post-processed adjusted with ground control points. This level of accuracy meets suggested cross-slope accuracies for mobile measurements (±0.2%) and demonstrates that mobile LiDAR is a reliable method for cross-slope verification. Performing cross-slope verification can ensure existing pavement meets minimum cross-slope requirements, and conversely is useful in identifying roadway sections that do not meet minimum standards, which is more desirable than through crash reconnaissance where hydroplaning was evident. Adoption of MLS would enable the South Carolina Department of Transportation (SCDOT) to address cross-slope issues through efficient and accurate data collection methods.

Data collection experience for preliminary calibration of the AASHTO pavement design guide for flexible pavements in South Carolina

The primary objective of this research was to identify existing historical data (i.e., climate, traffic, pavement design information, material properties, and pavement performance) within the South Carolina Department of Transportation for use in the local calibration of the Mechanistic Empirical Pavement Design Guide (MEPDG) for South Carolina. Based on all of the compiled information, 14 in-service asphalt concrete (AC) pavement sections were selected as suitable for this study, and information gaps were identified. Field and laboratory tests were performed to study the subgrade modulus at 3 sites. The data collected for the 14 sections were used to perform a preliminary analysis of the MEPDG AC rutting models and AC fatigue cracking models. Level 1 (project specific), Level 2 (region specific), or Level 3 (default) inputs were used, depending on data availability. This study was the first step in obtaining local calibration factors for South Carolina and provided guidance to perform the final local calibration. Currently, many highway agencies are looking to implement MEPDG for designing their pavements. Thus, this paper serves as a guide to other highway agencies in their preliminary phase of a MEPDG local calibration study.

Use of Laboratory and Field Data to Evaluate the Pier Scour Equation from Hydraulic Engineering Circular 18

The Hydraulic Engineering Circular 18 (HEC-18) pier scour prediction equation is the most widely used pier scour prediction equation in the United States, if not the world, and understanding the equation’s performance is of interest to the bridge engineering community. Previous evaluations of the equation’s performance were limited to smaller sets of laboratory and field data. In 2014, the U.S. Geological Survey, in cooperation with the South Carolina Department of Transportation, published a U.S. Geological Survey pier scour database, consisting of 569 laboratory and 1,858 field measurements of pier scour. This extensive database is a valuable resource for evaluating the HEC-18 pier scour equation, which is the primary focus of the investigation presented in this paper. Although comparing predicted and measured values is a common method for evaluating the performance of a prediction equation, the present investigation used a different approach and evaluated the HEC-18 equation by comparing selected data from the USGS database with the dimensionless relationship used to develop the original equation. This alternative approach highlighted some of the strengths and weaknesses of the equation, which are not as evident in the more common approach of comparing predicted and measured values. The findings of the investigation are presented in this paper.

Superpave evaluation of higher RAP contents using WMA technologies

In this study, the objective was to conduct an investigation of Superpave mix design characteristics of WMA technologies in terms of various high percentages of reclaimed asphalt pavements (RAPs). One PG 58-28 binder, two PG 64-22 binders, and two RAP sources were selected from South Carolina. In addition, three mix technologies (e.g. hot mix asphalt (HMA), foaming technology, and Evotherm additive) were employed to produce the mixtures. Meanwhile, four RAP contents of 20%, 30%, 40%, and 50% (by weight of total mixture) were utilized to blend with virgin materials. 36 Superpave mix designs were conducted to explore the volumetric characteristics of various mixtures. In this study, the results indicated that, all mixtures have an optimum asphalt content (OAC) less than 5.0%, and most of these values are close to a minimum OAC value of 4.5% set by South Carolina Department of Transportation (SCDOT). No noticeable increases at the mixing and compaction temperatures for these mixtures containing a higher percentage of RAP (i.e., over 40%) were found in this study. In addition, the voids in mineral aggregate (VMA), voids filled with asphalt (VFA), dust/asphalt ratios, and moisture susceptibility meet the requirements of SCDOT’s specifications. Therefore, these specific mix designs could be used as the guidelines for developing a set of specifications for a higher percentage of RAP in terms of warm mix asphalt technology.

Investigation of Los Angeles value and alternate aggregate gradations in OGFC mixtures

Open Graded Friction Course (OGFC) mixes with high air voids are mainly used to provide better service on the highway pavement during the rainy weather through draining water from the surface of the pavement. The objective of this study was to investigate performance characteristics of one low L.A. Abrasion aggregate compared to three high L.A. Abrasion aggregates as measured by various laboratory mix testing procedures to determine if overall OGFC mix performance was affected by an aggregate durability standpoint. In addition, three alternate aggregate gradations on the performance of OGFC mixtures were investigated. The main tests include permeability, Cantabro loss, and breakdown in the lab and asphalt plant of OGFC materials. The test results indicated that the high L.A. materials performed as well as the low L.A. material (Control) in most cases. In addition, various blends of similarly sized aggregates perform equally as well as the current South Carolina Department of Transportation (SCDOT) OGFC blend based on the limited laboratory testing conducted in this study. In the field testing, both the low L.A. Abrasion aggregate and high L.A. aggregates exhibited significant breakdown as measured from laboratory results of samples taken at various points in the production process as well as from visual observation during sampling. Constructing test sections using alternate gradations while maintaining desired OGFC mix properties is generally recommended.

Process for Developing Asynchronous Online Training for Transportation Agency Professionals: Case Study

Efficient training is an essential component of work force development for transportation agencies. The South Carolina Department of Transportation (DOT) recognized one such training need in its management of contracts for professional services consultants. This recognition led to a research effort to identify standardized procedures in the procurement and administration of these contracts, resulting in the development of a training manual and daylong pilot training session. Although the session received positive feedback, it limited the time and location for delivery. This traditional, in-class method is no longer the only available option. Asynchronous online training presents agencies with the option of providing training to employees regardless of their spatial or schedule variabilities while minimizing the need for instructor effort and availability. In light of this change, the South Carolina DOT commissioned a subsequent research effort to study best practices for development, delivery, and assessment of online training and to use these findings to create training modules of the previously completed manual and training session. The focus of this paper is to present the process for developing asynchronous online training employed for the 10 modules, which total roughly 5 h. Although this process is based on best practices, they are not discussed at length; rather, references to findings are made where they pertain. The process, unique lessons learned, and advisable practices are discussed. The paper’s presentation of the online development process can be applied to other transportation agencies intending to implement asynchronous online training for professional development.

Upper Bound of Pier Scour in Laboratory and Field Data

The U.S. Geological Survey (USGS), in cooperation with the South Carolina Department of Transportation, conducted several field investigations of pier scour in South Carolina and used the data to develop envelope curves defining the upper bound of pier scour. To expand on this previous work, an additional cooperative investigation was initiated to combine the South Carolina data with pier scour data from other sources and to evaluate upper-bound relations with this larger data set. To facilitate this analysis, 569 laboratory and 1,858 field measurements of pier scour were compiled to form the 2014 USGS Pier Scour Database. This extensive database was used to develop an envelope curve for the potential maximum pier scour depth encompassing the laboratory and field data. The envelope curve provides a simple but useful tool for assessing the potential maximum pier scour depth for effective pier widths of about 30 ft or less.

Upper Bound of Abutment Scour in Laboratory and Field Data

The U.S. Geological Survey, in cooperation with the South Carolina Department of Transportation, conducted a field investigation of abutment scour in South Carolina and used those data to develop envelope curves that define the upper bound of abutment scour. To expand on this previous work, an additional cooperative investigation was initiated to combine the South Carolina data with abutment scour data from other sources and evaluate upper bound patterns with this larger data set. To facilitate this analysis, 446 laboratory and 331 field measurements of abutment scour were compiled into a digital database. This extensive database was used to evaluate the South Carolina abutment scour envelope curves and to develop additional envelope curves that reflected the upper bound of abutment scour depth for the laboratory and field data. The envelope curves provide simple but useful supplementary tools for assessing the potential maximum abutment scour depth in the field setting.

Estimation of Pavement and Bridge Damage Costs Caused by Overweight Trucks

This study adopted a damage quantification framework to estimate bridge and pavement damage caused by overweight trucks. The framework was applied to estimate unit overweight truck damage costs for the highway system maintained by the South Carolina Department of Transportation. The analysis revealed that pavement and bridge damage increased significantly when trucks were above legal weight limits. Tradeoffs between the most common overweight truck fee types were estimated to examine their relative efficacy. The study found the axle-based damage cost recovery fee for the additional per trip damage cost above the legal weight limit for an overweight truck loaded up to the maximum overweight limit. The fee varied between $14 and $165 per trip, depending on the type of overweight truck. The flat damage cost recovery fee was $55 per trip for all overweight trucks (about two times the current flat damage fee in South Carolina). The study revealed that ignoring the axle distribution in the flat damage cost recovery fee caused some truck types to pay more and others to pay less than the actual damage they imparted. In a weight-based damage cost recovery fee system, the per trip damage cost recovery fee varied between $2.77 and $36.57 per ton; in a weight-distance-based damage cost recovery fee system, the damage fee varied between 2 and 14 cents per ton-mile. A comparative analysis between damage cost recovery fee types, such as the one presented in this paper, will provide insight to decision makers for setting policies regarding overweight trucking fees.

Exposing Minority Students to Careers in Transportation and Science, Technology, Engineering, and Mathematics

The aging of the American workforce will lead to shortages in skilled workers throughout the country in the near future. Minorities are already underrepresented in the transportation industry, and without immediate intervention the conditions will not improve. To address the anticipated shortfall in skilled minority labor, FHWA, in coordination with the South Carolina Department of Transportation and South Carolina State University, developed the Summer Transportation Institute. In the Texas Gulf Coast region, the Center for Transportation Training and Research at Texas Southern University has introduced the transportation industry to minority high school students while emphasizing the importance of science, technology, engineering, and mathematics skills in tomorrow's workplace through summer education programs for nearly 10 years. A study examines the core curriculum of those programs and discusses their potential applicability in other regions of Texas.