US Federal Highway Administration Research Articles

Scaled Model Tests Investigating Deformation Characteristics of Geosynthetic Reinforced Soil (GRS) Abutments under Vertical Loads.

This study conducted plane-strain scaled model tests to investigate the deformation characteristics of geosynthetic reinforced soil (GRS) abutments subjected to vertical loads. Setback distance, i.e., the distance between the back of the abutment facing and the front of the loading plate, was chosen as the investigated influencing factor since it is one of the most frequently used variables by engineers for the design of GRS abutments. This study analyzed the settlements at the top of the abutment, the lateral displacements of the abutment facing, and the volumetric deformations of the abutment under the applied vertical loads. Test results showed that increasing the setback distance could effectively reduce the deformations of the GRS abutment. There existed an optimum setback distance and further increasing the setback distance beyond this optimum value did not have a significant effect on reducing the abutment deformations. The vertical, lateral, and total volumetric deformations of the GRS abutment showed an approximately linear increase with the increase of the applied vertical loads. The lateral volumetric deformations of the GRS abutment were larger than its vertical volumetric deformations and therefore the total volumetric strains of the GRS abutment were not zero based on the test results. However, the theory of zero volume change may still be suitable for the deformation calculation of the GRS abutment since the values of the volumetric strains were minimal. The measured maximum lateral facing displacements were compared with the calculated values using the US Federal Highway Administration (FHWA) method, which assumes zero volume change of the GRS abutment under vertical loads. Comparison results indicated that the FHWA method overestimated the maximum lateral facing displacements of the GRS abutment under vertical loads. An improved method was proposed in this study to calculate the maximum lateral facing displacements under vertical loads based on the theory of zero volume change and a revised distribution of the settlements at the top of the GRS abutment. Results showed that the improved method could better predict the maximum lateral facing displacements as compared to the FHWA method.

LiDAR Vehicle Point Cloud Reconstruction Framework for Axle-Based Classification

As Light Detection and Range (LiDAR) technology rapidly advances, it is becoming increasingly viable as a solution to collect vehicle classification data. The main challenge of LiDAR compared with video in vehicle classification lies in its resolution, which limits the ability of LiDAR-based models to classify vehicles in detail from a single captured frame. This paper proposes a novel framework for reconstructing the vehicle point clouds generated by a roadside LiDAR sensor, by considering ground plane constraints and developing a bootstrap aggregating deep neural network (bagging DNN) model to classify the reconstructed vehicle point clouds, according to the US Federal Highway Administration (FHWA) axle-based vehicle classification scheme. First, a probabilistic-based registration algorithm is used to estimate the transformation matrix between consecutive frames of each vehicle point cloud. Then, a multiway registration is conducted to fine-tune the estimated transformation matrices to rebuild the 3D model of each moving vehicle. Second, key features are extracted from the reconstructed vehicle models and fed into a bagging DNN model to provide classifications based on the FHWA scheme. The classification model with the reconstruction framework outperforms the latest developed LiDAR-based FHWA classification model in terms of both accuracy and robustness. The model has an 83 percent average correct classification rate (CCR) on the test set. Remarkably, the proposed model can accurately distinguish Classes 5 and 8 trucks, which have overlapping axle configurations, with a 97 percent and a 90 percent CCR, respectively.

An app for nationwide dynamic traffic noise prediction

Despite being so pervasive, road traffic noise can be difficult to model and predict on a national scale. Detailed road traffic noise predictions can be made on small geographic scales using the US Federal Highway Administration's Traffic Noise Model (TNM), but TNM becomes infeasible for the typical user on a nationwide scale because of the complexity and computational cost. Incorporating temporal and spectral variability also greatly increases complexity. To address this challenge, physics-based models are made using reported hourly traffic counts at locations across the country together with published traffic trends. Using these models together with TNM equations for spectral source emissions, a streamlined app has been created to efficiently predict traffic noise at roads across the nation with temporal and spectral variability. This app, which presently requires less than 700 MB of stored geospatial data and models, incorporates user inputs such as location, time period, and frequency, and gives predicted spectral levels within seconds.

Big data to streamlined app: Nationwide traffic noise prediction

A vast amount of data can be processed using high-performance computing (HPC), but sometimes, the HPC hardware requirements are cost prohibitive. However, by using HPC to create reduced-order models that require much less processing power and data storage, the benefits of HPC can be realized for a wider range of users. For example, detailed traffic noise predictions can be made on small geographic scales using the US Federal Highway Administration’s Traffic Noise Model (TNM), but when considering a nationwide scale, TNM becomes infeasible for the typical user because of computational cost. Additionally, though calculating an annually averaged overall level may be within a user’s computational capacity, incorporating temporal and spectral variability increases complexity. Using HPC on hourly traffic counts at locations across the country together with published traffic trends and TNM equations, a streamlined app has been made to efficiently predict traffic noise at roads across the nation with temporal and spectral variability. This app, which presently requires less than 700 MB of stored geospatial data and models, incorporates user inputs such as location, time period, and frequency, and gives predicted spectral levels within seconds.

Autonomous agent adaptive driving control based on fuzzy logic theory and normative behavior

Studying driver behaviors has become a major concern for the transportation community, businesses, and the public. Thus, based on the simulation, we proposed an adaptive driving model in the car-following driving behavior and based on the normative behavior of the driver during decision-making and anticipation, whose intention is to ensure the objectives of imitation of ordinary human behavior and road safety. The presented model is based on a software agent paradigm to model a human driver and the Fuzzy Logic Theory to reflect the driver agent’s reasoning. To validate our model, we used the dataset from the program of the US Federal Highway Administration. In this context, we notice an excellent homogeneity in the deviation of the adopted trajectory of the autonomous driver agent from the adopted trajectories by the human drivers. Moreover, the advantage of our model is that it works with different velocities.

Using updated roadway construction noise model acoustical noise data for simplified construction noise predictions.

In 2006 the US Federal Highway Administration (FHWA) issued the Roadway Construction Noise Model (RCNM) for use in predicting noise levels from construction activities, and this tool is still in wide use today among practitioners for evaluating construction noise for a variety of project types. The original RCNM included basic acoustical data for 57 different types of common construction equipment which was collected mostly in the late 1990s and early 2000s. More recently an effort was made to collect more detailed acoustical data for a wider range of more modern construction equipment for an updated version of RCNM (version 2.0). The new RCNM 2.0, runs on a new user interface platform, which may have resulted in a lower use rate by practitioners. This paper summarizes the updated construction equipment acoustical data collected for RCNM 2.0, a brief comparison to older data such as from the oroginal RCNM, and a more simplified, spreadsheet-based prediction methodology.

Driving control based on bilevel optimization and fuzzy logic

Driving control in the car-following (CF) driving behavior has two aspects. First, in what measure an approximation distance is taken as a safe distance guaranteeing the safety of the follower drivers. Second, how to control the follower's vehicle velocities based on the stimulus of the leading vehicle. In this context, to resolve the driving control problem in the CF driving behavior, a bilevel optimization is presented in this paper, based on the behaviors of the follower and leader drivers. Bearing in mind that mathematics has contributed to the imitation of human behaviors, they are now reaching a level of complexity requiring the entry on the scene of a new player, which is artificial intelligence. Thus, in this paper; we used the fuzzy logic theory for modeling a follower driver with a nonnormative behavior. To validate our model, we used a data set from the program of the US Federal Highway Administration. Therefore, according to the experimental results, there is homogeneity between the actual and the simulated travel trajectories in terms of deviation. Besides, the driver's behavior adopted (normative or nonnormative) is reflected in his reactions to the various components of the road.

NextScour for improving bridge scour design in the United States

The US Federal Highway Administration (FHWA) is developing the next-generation scour programme – that is, NextScour – to improve scour analysis for safe and economical bridge foundation design. NextScour recognises that scour phenomena consist of two major components: (a) water and hydraulic forces and (b) erosion resistance of soils and their associated geotechnical effects. Consequently, the programme consists of two focus areas: NextScour-Hydraulic and NextScour-Geotechnical. NextScour seeks to research and develop a design tool that computes hydraulic loads across the bathymetric domain. When linked to geotechnically derived subsurface erosion maps/stratigraphy and information of NextScour, the design tool produces instantaneous three-dimensional scour bathymetries around all bridge foundation elements. A bridge replacement project from the Virginia Department of Transportation provided an excellent case study of the potential cost saving by considering NextScour proof-of-concept results in the design process. The J. Sterling Jones Hydraulics Research Laboratory erosion tests determined the erosion resistance of the clay layer at the bridge foundation, and a hydraulic force depth decay function was developed along with the soil depth. The proof-of-concept analysis showed a potential reduced pier scour estimate by 15.7 feet (ft) (4.8 m) and contraction scour estimate by 16.4 ft (5.0 m), 44 and 65% reductions from the original scour analysis, respectively. NextScour empowers FHWA’s future scour analysis with the goal to improve significantly the accuracy of bridge scour estimates.

Axial performance of micropile groups in cohesionless soil from full-scale tests

Hollow bar micropile (HBMP) groups are used for supporting large loads as an alternative foundation option to large diameter drilled shafts. In such cases, it may be necessary to increase the micropile’s diameter by increasing the drill bit diameter (Db). This paper investigates experimentally and numerically the effect of increasing Dband micropile spacing on the group performance. A field load testing program was conducted on four groups of HBMPs installed in sand; each group comprised four micropiles arranged in a square configuration. All micropiles were constructed with the same size hollow bar, Dh= 51 mm; two groups comprised micropiles constructed with drill bit, Db= 115 mm, and two groups comprised micropiles constructed with drill bit, Db= 152 mm. One group of each set was installed with spacing to micropile diameter ratio, S/Db= 3 and the other group with S/Db= 5. In addition, full 3D finite element model (FEM) was developed and calibrated to simulate the behaviour of micropile groups and to evaluate the failure load for groups that were not loaded to failure. The results demonstrated that micropile groups constructed with the large diameter drill bits displayed higher stiffness and load carrying capacity than the groups constructed with small diameter bits, which confirms the effectiveness of using a larger drill bit. In addition, the group efficiency ratio values at both working load and ultimate capacity were found to be close to unity for all groups. The ultimate skin friction values of grouted micropiles obtained from this study were higher than the values suggested by the US Federal Highway Administration for medium to very dense sand. It was also found that the settlement of the 4-HBMP group increased by 25% to 33% over that of a single HBMP due to group effect.

Exposure assessment to road traffic noise levels and health effects in an arid urban area.

Road traffic noise exposures have been recognized as serious environmental health concerns, especially in most developing countries with arid climate conditions, rapid increase in vehicle population, and limited traffic management systems. The excessive noise exposure level is associated with increase in the incidence of cardiovascular diseases and anxiety, including annoyance. This study aimed at determining traffic noise levels in residential areas, including the assessment of its annoyance and health effects based on the people's perception and reportage. To do so, field measurement and traffic noise modeling were carried out in six road points to estimate the current noise levels along various roads close to human inhabitants in Muscat Governorate, Sultanate of Oman. The detailed measured noise levels in urban residential areas across the selected roads showed that noise levels have exceeded the local and international threshold limits at all locations during the entire day. The high sound levels (48.0-56.3 dBA) were observed using the US Federal Highway Administration's Traffic Noise Model (TNM, version 2.5) results, which were in agreement with the observed (56.3-60.4 dBA) data. To assess health implication to residents through interviews (n = 208), annoyance at home was found to be little (32%), moderate (28%), and high (9%) in comparison with workplace settings of 42%, 43%, and 15%, respectively. Nineteen percent of the interviewees had difficulties in sleeping, while 19.8% experienced stress due to road traffic noise exposures. Moreover, a strong association (p < 0.05) was established between the use and objection of noise barriers. The study revealed high noise levels and the prevalence of annoyance and health effects among the exposed population. Therefore, immediate action is required to tackle the current noise levels.

Macroscopic effect of distance from seacoast on bridge deterioration – Statistical data assessment of structural condition recordings

Airborne sea chlorides that are transported inland by wind and deposited on structures’ surfaces are a principal deterioration factor for coastal bridges. In this paper, a dataset for almost 20,000 coastal bridges, which was extracted from the National Bridge Inventory (NBI) of the US Federal Highway Administration, is exploited to conduct a macroscopic statistical study on the deterioration effect of airborne chlorides. The study focuses directly at the very final stage of the overall physical phenomenon, in which deterioration due to seacoast effect is evident. To distinguish this effect, the extracted coastal bridge sample was segmented to produce consistent subsamples in terms of other coexisting factors influencing deterioration, including use of deicing salt and earthquake hazard. Year of bridge construction/reconstruction, structural materials (reinforced/prestressed concrete, structural steel) and structural types (simple/continuous spans) were also taken into account. Moreover, bridge groups based on the bridges’ distances from the seacoast were formed using high accuracy coastline and bridge coordinates. Hence, structural condition ratings for bridge components recorded in the NBI database were statistically assessed with respect to corresponding coastal distances. It was statistically deduced that, under certain conditions, bridges can be noticeably affected by sea chlorides at coastal distances up to 2–3 km inland.

Modeling and Prediction of Driver-Vehicle-Unit Velocity Using Adaptive Neuro-Fuzzy Inference System in Real Traffic Flow

Prediction of the driver-vehicle-unit (DVU) future state is a challenging problem due to many dynamic factors influencing driver capability, performance and behavior. In this study, a soft computing method is proposed to predict the accelerating behavior of driver-vehicle-unit in the genuine traffic stream that is collected on the California urban roads by US Federal Highway Administration’s NGSIM. This method is used to predict DVU velocity for different time-steps ahead using adaptive neuro-fuzzy inference system (ANFIS) predicator. To evaluate the performance of proposed method, standard time series forecasting approach called autoregressive (AR) model is considered as a rival method. The predictions accuracy of two methods are compared using root mean square error (RMSE), mean absolute percentage error (MAPE) and coefficient of determination or R-squared (R2) as three error criteria. The results demonstrate the adequacy of proposed algorithm on real traffic information and the predicted speed profile shows that ANFIS is able to predict the dynamic traffic changes. The proposed model can be employed in intelligent transportation systems (ITS), collision prevention systems (CPS) and etc.

ANALYSIS OF IMPEDIMENTS TO A SUCCESSFUL CONSTRUCTABILITY PROCESS IN HIGHWAY CONSTRUCTION

The US Federal Highway Administration (FHWA) Every Day Counts Program (EDC) has resulted in state Departments of Transportation (DOTs) putting evermore emphasis on speeding up the delivery of highway and bridge construction projects for use by the driving public. This has resulted in an increase in the use of integrated project delivery methods and adding alternative technical concepts (ATCs) to traditional design-bid-build (DBB) contracts. ATCs have exhibited great potential for delivering substantial benefits like cost savings, increased constructability, and quicker project delivery. Previous research has found that knowledge of project constructability was lacking in state DOT planning, programming, and environmental staffs. At the same time, the permitting process for several government agencies has become increasingly restrictive. The intent of this paper is to report on the research team's progress in an ongoing effort to furnish the US government with a uniform set of guidelines for the application of the constructability process during all phases of project development and delivery. The research uses surveys, focus groups and interviews to determine which states have implemented formal programs to ensure that the constructor is furnished with a set of contract documents that affords said constructor with the best possible opportunity to successfully construct the project with the highest quality standards, within the contract duration and without exceeding the construction budget.

Effects of scour-hole dimensions on lateral behavior of piles in sands

Scour is a process of soil erosion around foundations caused by currents and waves, which can severely compromise the performance of the foundations. The scour process forms a scour hole around the foundation. The existence of the scour hole has been considered by many design standards for pile foundations such as those from the US Federal Highway Administration (FHWA) and American Petroleum Institute (API). However, these standards recommend different procedures to evaluate lateral responses of piles subjected to local scour that forms three dimensions of scour hole. This paper presents a series of three-dimensional finite element (FE) parametric analyses to examine the feasibility of the standard methods (FHWA and API) as well as an analytical solution proposed by the authors through varying scour-hole dimensions, soil properties, and pile properties. The results showed that the analytical solution provided conservative results while the standard methods provided mixed results compared with the FE analyses. The loss of pile lateral capacity due to scour was more significant in dense sands than in loose sands (approximately 10% more). For a given relative scour depth, the increase in pile diameter increased the scour-induced loss of pile lateral capacity.

Evaluation of vertical effective stress and pile lateral capacities considering scour-hole dimensions

Determination of vertical effective stress along piles is an essential part of calculation of both pile axial and lateral capacities under scour conditions. However, the current design manuals including those from the US Federal Highway Administration (FHWA) and American Petroleum Institute (API) recommend different methods for calculating vertical effective stress. Moreover, they are effective only for restricted scour-hole dimensions. This study presents an improved closed-form solution that allows estimation of the vertical effective stress for a wide range of scour-hole dimensions including scour depth, width, and slope angle. Using the improved analytical solution for stress, API p–y curves for sand were modified to compute pile lateral capacity at different scour-hole conditions. Based on a series of parametric analyses for laterally loaded piles in sand, errors of calculation using the existing methods were quantified and a simplified method was proposed for practical applications. Effects of different scour-hole dimensions on both vertical effective stress and pile lateral capacity were also discussed.

The impact of automated transit, pedestrian, and bicycling facilities on urban travel patterns

ABSTRACTThis article reports on an integrated modeling exercise, conducted on behalf of the US Federal Highway Administration, on the potential for frequent automated transit shuttles (‘community transit’), in conjunction with improvements to the walking and cycling environment, to overcome the last-mile problem of regional rail transit and thereby divert travelers away from car use. A set of interlocking investigations was undertaken, including development of urban visualizations, distribution of a home-based survey supporting a stated-preference model of mode choice, development of an agent-based model, and alignment of the mode-choice and agent-based models. The investigations were designed to produce best-case estimates of the impact of community transit and ancillary improvements in reducing car use. The models in combination suggested significant potential to divert drivers, especially in areas that were relatively transit-poor to begin with.

Mitigation of alkali–silica reaction in US highway concrete

This paper provides an overview of the various field trials performed by the US Federal Highway Administration aimed at mitigating the effects of alkali–silica reaction on highway concrete elements, including pavements, bridges and barriers. The different methods used to attempt to reduce the expansion and cracking of affected concrete are described, including the use of sealings and coatings, the application of lithium nitrate and the application of external confinement. The field trials were conducted and monitored between 2005 and 2014, and the overall findings from each trial are briefly summarised. The use of silane products was found to be the most effective means of reducing the expansion and cracking due to alkali–silica reaction, with the most significant improvement seen in highway barriers. Topical and vacuum application of lithium compounds showed little or no benefit in reducing expansion and cracking, mainly due to the lack of lithium penetration. Electrochemical application of lithium nitrate was more effective in driving the lithium into the affected concrete, but had a negligible impact on the expansion and cracking induced by alkali–silica reaction. Owing to the limited time that was available to monitor most of the field trials, future monitoring is essential to delineate the efficacy of the various treatments.

An inland waterway traffic noise prediction model for environmental assessment in China

This paper aimed at proposing an inland waterway traffic noise prediction model for environmental assessment in China. The study was the first to predict inland waterway traffic noise levels considering water surface condition and absorption influence in China. The analysis results indicated that the inland waterway traffic noise exposure levels can be influenced by water surface. The model was developed based on the Germany Schall 03 model by adding the water surface condition and absorption correction terms to the governing equations. Results showed that the predicted noise levels by the developed model correlated well with the measurements. In addition, the developed model had higher precision compared with the existing models such as the Schall 03 model, the modified US Federal Highway Administration (FHWA) model and the modified Germany Richtlinien für den Lärmschutz an Straßen (RLS 90) model. The proposed model can be utilized to assess inland waterway traffic noise exposure in China.

Life Cycle Engineering for Roads (LCE4ROADS), The New Sustainability Certification System for Roads from the LCE4ROADS FP7 Project

There are many initiatives in the market capable to assess some aspects of sustainability for roads (mainly environmental). For instance, in America it should be noted the Greenroads, Envision and Invest certification systems. In Europe, it must be highlighted some sustainability assessment systems such as Ceequal in UK as well as rating and awards scheme for civil engineering or many tools to evaluate CO2 and Carbon Footprint, for example, the Dutch CO2 Performance Ladder.However, a complete evaluation of sustainability has not been implemented yet as a consequence of that some approaches do not cover all life cycle phases or all sustainability pillars. What is more, there is a lack of regulation in terms of a framework for sustainability assessment of civil constructions, for instance, CENTC 350 is still under development In addition, there are regional peculiarities which are not always considered in the evaluation systems and sometimes there are some stakeholders refusing the idea of road comparison. The EC by means of the Joint Research Centre (DG-JRC) is developing the Green Public Procurement Criteria (GPP) for design, construction and maintenance of roads, as useful method for the pre-selection criteria for contractors and for ensuring compliance of performance.This paper summarizes the new sustainability certification system for roads named “LCE4ROADS”, under development as part of the FP7 project: “Life Cycle Engineering approach to develop a novel EU-harmonized sustainability certification system for cost-effective, safer and greener road infrastructures”.LCE4ROADS will integrate by a Life Cycle Engineering (LCE) approach, all the aspects of sustainability (Environmental, Economic, Social, Technical) to asses roads projects and works (both new construction and rehabilitation/maintenance) with the final goal of creating a holistic and EU-harmonized methodology to increase the sustainability roads.The certification system developed is based on current EN and ISO standards for sustainability in construction (EN15804) and LCA and LCC (ISO 14040-44 and ISO15686) and considers previous developments from other research projects like MIRAVEC, EVITA, COST 354 among others.Key aspects at European level like the adaptation and resilience to Climate Change and the implementation of freight corridors (the so called TEN-T: Trans European Transport Network) will be considered in this new certification system.With the goal of refining the certification system and the parameters and key performance indicators to be considered, it should be mentioned that LCE4ROADS has been already presented to different key stakeholders such as:•National and Regional Road Authorities in six EU countries (France, The Netherlands, Spain, Germany, Sweden, Poland) and in Turkey (The Turkish Ministry of Transport (KGM) is partner of the FP7 Project).•The European Commission (DG Research, DG Environment, DG JRC, and DG Move-Transport)•Sectorial Platforms and Associations like the European Committee for Standardization (CEN), The European Road Federation (ERF), the Spanish Construction Technology Platform (mirror of the European ECTP) among others.The US Federal Highway Administration (FHWA) is also interested in this topic and is working closely to the FP7 project team (the EC selected the project to collaborate with the most important transport research center in America).The feedback received for future implementation from the key stakeholders has been taken into consideration to modify the scope of the certification system, the phases covered and the certification moments.This system, together with a guide for application and a multi-criteria software tool to be developed could be really useful for future procurement and GPP processes in Europe.

MINIMIZING THE NUMBER OF VEHICLES IDLING AT AN INTERSECTION

The objective of this project is to find an optimal solution minimizing the number of vehicles idling at the Kapiolani-McCully intersection during the evening peak period (6 pm-8 pm), by assigning appropriate traffic signal times for each direction. This duration would also take into account pedestrian safety constraints, set by the US Federal Highway Administration, i.e., that standard walking rates for pedestrians should be 4 feet per second for safe crosswalk countdown times. Signal times for four directions, i.e., McCully straight turn, McCully left turn, Kapiolani straight turn, and Kapiolani left turn, were determined using linear programming based on queue length, crosswalk countdown time, and vehicle arrival rates. Average vehicle arrival rates for each direction were measured to calculate the cumulative number of vehicles waiting. Since all vehicles in all directions can use the “right on red” rule for right turns without waiting for a green signal, the study focused on the number of vehicles waiting in the left-turn and straight-turn lanes. The study found that, in order to minimize the number of vehicles waiting under the constraints, a green-light time assigned for straight turns on McCully should be 23 seconds, a green-light time for straight turns on Kapiolani should be 20 seconds, and a green-light time of 9 seconds for all the left turns.