Transportation Engineering Commons^™

Development Of A Machine Learning-Based Model To Determine The Optimum And Safe Restriping Timing Of Thermoplastic Pavement Markings In Hot And Humid Climates, Momen R. Mousa, Marwa Hassan

Data

Due to limited budget, most transportation agencies restripe their thermoplastic pavement markings based on a fixed schedule or based on visual inspection instead of monitoring the retroreflectivity and restriping when the retroreflectivity drops below a pre-determined threshold. These strategies are questionable in terms of efficiency and economy. Therefore, previous studies proposed degradation models to predict the retroreflectivity of thermoplastic markings based on key variables. Yet, most of these studies reported low R² (as low as 0.1), which placed little confidence in these models. Therefore, the objective of this study was to evaluate and predict the field performance of thermoplastics …

Alternative Supplementary Cementitious Materials In Ultra-High Performance Concrete, Craig Newtson, Seyedsaleh Mousavinezhad, Gregory J. Gonzales, William K. Toledo, Judit M. Garcia

Publications

Ultra-high performance concrete (UHPC) is an emerging material with remarkable mechanical and durability properties that contains large amounts of cementitious materials. Silica fume is a main supplementary cementitious material (SCM) in UHPC, however, it is more expensive than cement and other SCMs, so it is often substituted with inexpensive class F fly ash. Unfortunately, future availability of fly ash is uncertain as the energy industry moves toward renewable energy. Fly ash shortages create an urgent need to find cost-effective and environmentally-friendly alternatives for fly ash. This study investigated replacing cement, fly ash, and silica fume in UHPC mixtures with ground …

A Deep Learning Tool For The Assessment Of Pavement Smoothness And Aggregate Segregation During Construction, Mostafa Elseifi, Ramchandra Paudel, Md Tanvir Ahmed Sarkar, Hossam Abohamer, Nirmal Dhakal

Data

Pavement construction monitoring and quality assurance (QA) practices are mostly based on costly, discrete, and destructive methods. Most quality assurance programs are based on pavement construction procedures encompassing in-situ coring for layer thickness determination, density measurements, laboratory testing to measure volumetric properties, and smoothness measurements in case of the availability of a profiler. The main objective of this study was to develop a machine learning-based classifier for predicting pavement roughness and aggregate segregation based on digital image analysis, image recognition, and deep learning machine models. The developed Convolution Neural Networks (CNN) models were trained, tested, and validated using 600-pavement surface …

Using Rice Husk Ash (Rha) As Stabilizing Agent For Problematic Subgrade Soils And Embankments, Zahid Hossain, Rifat Bulut, Fares Tarhuni, Hussein Al-Dakheeli

Data

Arkansas produces the most of the rice in the United States. About 20% of poddy is rice husk (RH), which is burnt under controlled conditions to produce rice rusk ash (RHA). The RHA is considered an environmental hazard and a significant challenge for rice millers. However, RHA is rich in pozzolanic material, which is mainly silica. In this study, RHA is used to stabilize poor soils. Another commonly used stabilizer, hydrated lime (HL), has also been evaluated for comparison purposes. Thus, this study aimed to determine the optimum percentages of RHA, HL, or a combination of these two agents by …

Performance Monitoring Leveraging Advanced Ai Technique With Cnn, Suyun Ham Ph.D, Stefan Romanoschi, Yin Chao Wu, Dafnik Saril Kumar David, Sanggoo Kang

Publications

The main goal of this project is to study and develop a reliable nondestructive testing (NDT)-based structural performance prediction model framework leveraging the advanced machine learning convolutional neural network (CNN) technique and rapid crack evaluation system. There are two steps of application CNN technique in this project: 1) the first step is to identify delamination, noise, and the unexpected signal produced by the existing damage identification algorithm to improve the accuracy of NDT results. The input image or training data of NDT data for CNN is comprehensively studied with several features, such as the duration of the signal, the starting …

Increasing Bridge Durability And Service Life With Lidar Enhanced Unmanned Aerial Systems (Uas), Fernando Moreu, Mahsa Sanei, Chris Lippitt

Data

Bridge construction inspections require quantitative measurements and location information. The conventional approach is visual inspection, which in general, is rather time-consuming, expensive due to traffic closure, subjective, and needs special access. Therefore an automated rebar layout detection algorithm was developed to quickly extract quantitative rebar layout information from the LiDAR data. This systematic method can automatically cluster the bridge elements from a 3D point cloud by using LiDAR-equipped UAS data collection and unsupervised machine learning techniques. A new automated inspection system using a LIDAR-equipped UAS can eventually if developed and tested be more reliable as well as less expensive. In …

Performance Monitoring Leveraging Advanced Ai Technique With Cnn, Suyun Ham Ph.D, Stefan Romanoschi, Yin Chao Wu, Dafnik Saril Kumar David, Sanggoo Kang

Data

The main goal of this project is to study and develop a reliable nondestructive testing (NDT)-based structural performance prediction model framework leveraging the advanced machine learning convolutional neural network (CNN) technique and rapid crack evaluation system. There are two steps of application CNN technique in this project: 1) the first step is to identify delamination, noise, and the unexpected signal produced by the existing damage identification algorithm to improve the accuracy of NDT results. The input image or training data of NDT data for CNN is comprehensively studied with several features, such as the duration of the signal, the starting …

Development Of Distress Index Prediction Models For Rehabilitation Treatments In Louisiana Using Advanced Machine Learning Techniques, Momen R. Mousa, Marwa Hassan

Data

Performance prediction models are used by state agencies to predict future trends in distress indices, hence, determining the required maintenance and/or rehabilitation treatment as well as the deterioration rate and remaining pavement service life. However, most of these models are based on a limited number of parameters and cannot predict the performance distress indices reliably. Such limitation resulted in having, most of the time, a maximum prediction period of five years. As a solution and coping with the ever-increasing size of pavement data, machine learning techniques have become a promising alternative. The objective of this study was to develop a …

Covid-19 And Traffic Safety: Exploring Exposure, Crash Frequency And Severity, And Roadway And Network Design, Nicholas N. Ferenchak Ph.D

Publications

Early COVID-19 lockdowns in the first half of 2020 largely kept people at home, thereby reducing motor vehicle traffic levels. Theoretically, reduced traffic exposure should have resulted in reduced motor vehicle crashes. However, a variety of factors may have complicated this relationship. In order to better understand the impact of COVID-19 lockdowns on traffic safety outcomes, we explore fatalities, injuries, and total crashes before and during the lockdowns on both the national and state levels. We provide descriptive statistics and create negative binomial regressions exploring the role of vehicle, user, and built environment factors on traffic safety outcomes. Findings suggest …

Covid-19 And Traffic Safety: Exploring Exposure, Crash Frequency And Severity, And Roadway And Network Design, Nicholas N. Ferenchak Ph.D

Data

Early COVID-19 lockdowns in the first half of 2020 largely kept people at home, thereby reducing motor vehicle traffic levels. Theoretically, reduced traffic exposure should have resulted in reduced motor vehicle crashes. However, a variety of factors may have complicated this relationship. In order to better understand the impact of COVID-19 lockdowns on traffic safety outcomes, we explore fatalities, injuries, and total crashes before and during the lockdowns on both the national and state levels. We provide descriptive statistics and create negative binomial regressions exploring the role of vehicle, user, and built environment factors on traffic safety outcomes. Findings suggest …

Increasing Bridge Durability And Service Life With Lidar Enhanced Unmanned Aerial Systems (Uas), Fernando Moreu, Mahsa Sanei, Chris Lippitt

Publications

Bridge construction inspections require quantitative measurements and location information. The conventional approach is visual inspection, which in general, is rather time-consuming, expensive due to traffic closure, subjective, and needs special access. Therefore an automated rebar layout detection algorithm was developed to quickly extract quantitative rebar layout information from the LiDAR data. This systematic method can automatically cluster the bridge elements from a 3D point cloud by using LiDAR-equipped UAS data collection and unsupervised machine learning techniques. A new automated inspection system using a LIDAR-equipped UAS can eventually if developed and tested be more reliable as well as less expensive. In …

Krs And Kar Review Of Models As A Legal Contract Document, Bryan Gibson, Pam Clay-Young, Rachel Catchings, Chris Van Dyke

Kentucky Transportation Center Research Report

State departments of transportation (DOTs) are expanding the use of electronic engineering data (EED) throughout highway projects — from design and construction through asset management. Included under the umbrella of EED are technologies such as building information modelling (BIM), digital terrain models (DTMs), and 3D models and plan sets. The Kentucky Transportation Cabinet’s (KYTC) Digital Project Delivery (DPD) Initiative is spearheading the transition to EED in the state. While digital delivery promises to streamline project development and management it does not come without hurdles. This report discusses methods for agency wide implementation of EED and highlights best practices for managing, …

Effectiveness Assessment Of E-Ticketing Technology In Construction Of Transportation Projects, Sharareh Kermanshachi, Karthik Subramanya

Publications

The construction of highway infrastructure has devoted significant resources towards e-Construction to reduce the paperwork and automate the tasks in daily operations. Electronic Ticketing (e-Ticketing) is one such component of e-Construction that aids in the digital transfer of material tickets such as asphalt and concrete which accounts for more than fifty per cent of construction costs. Despite the benefits of e-Ticketing, many state departments and agencies are unwilling to transition into this technology. No studies have identified the cause of the delay in the implementation process, developed a framework to comprehend the platform's full potential, quantified savings, and suggested strategies …

Optimal Scheduling Of Connected And Autonomous Vehicles At A Reservation-Based Intersection., Muting Ma

Electronic Theses and Dissertations

Reservation-based intersection control has been evaluated with better performance over traditional signal controls in terms of intersection safety, efficiency, and emission. Controlling connected and autonomous vehicles (CAVs) at a reservation-based intersection in terms of improving intersection efficiency is performed via two factors: trajectory (speed profile) and arrival time of CAVs at the intersection. In an early stage of the reservation-based intersection control, an intersection controller at the intersection may fail to find a feasible solution for both the trajectory and arrival time for a CAV at a certain planning horizon. Leveraging a deeper understanding of the control problem, reservation-based intersection …

Influence Of Specimen Geometry And Anisotropy On Dynamic Modulus Of Asphalt Mixes In South Carolina, Srinivasan Nagarajan

All Dissertations

The objective of this study was to characterize the variability of dynamic modulus of asphalt mixes in South Carolina on the basis of geometry and anisotropy. High priority mixes Surface Type B, and C; Intermediate Type B and C and Base Type A from three different days of production were collected from seven different contractors each having a different aggregate source and the dynamic modulus was measured using the Asphalt Mixture Performance Tester (AMPT) at temperatures of 40, 70, 100 and 130℉ (4.4, 21.1, 37.8, and 54.4℃) and at frequencies of 25, 10, 5, 1, 0.5, and 0.1 Hz. One-way …

Crack Control And Bond Performance Of Alternative Coated Reinforcements In Concrete, Sachin Sreedhara

All Dissertations

Concrete cracking in structures is a ubiquitous problem which can lead to the deterioration of the structure. Other than affecting the strength aspect of a structure, cracking impacts the serviceability criteria as well. Although cracking phenomenon in any structure is highly inevitable, it has to be minimized in order to maintain a structure’s life effectively. Cracking in reinforced concrete structures is related to the bond strength developed between the bar and the concrete. It also depends on an ability of the bar to resist the stresses due to shrinkage to minimize the crack. Another important aspect is the resistance offered …

Development Of Distress Index Prediction Models For Rehabilitation Treatments In Louisiana Using Advanced Machine Learning Techniques, Momen R. Mousa, Marwa Hassan

Publications

Performance prediction models are used by state agencies to predict future trends in distress indices, hence, determining the required maintenance and/or rehabilitation treatment as well as the deterioration rate and remaining pavement service life. However, most of these models are based on a limited number of parameters and cannot predict the performance distress indices reliably. Such limitation resulted in having, most of the time, a maximum prediction period of five years. As a solution and coping with the ever-increasing size of pavement data, machine learning techniques have become a promising alternative. The objective of this study was to develop a …

Using Rice Husk Ash (Rha) As Stabilizing Agent For Problematic Subgrade Soils And Embankments, Zahid Hossain, Rifat Bulut, Fares Tarhuni, Hussein Al-Dakheeli

Publications

Arkansas produces the most of the rice in the United States. About 20% of poddy is rice husk (RH), which is burnt under controlled conditions to produce rice rusk ash (RHA). The RHA is considered an environmental hazard and a significant challenge for rice millers. However, RHA is rich in pozzolanic material, which is mainly silica. In this study, RHA is used to stabilize poor soils. Another commonly used stabilizer, hydrated lime (HL), has also been evaluated for comparison purposes. Thus, this study aimed to determine the optimum percentages of RHA, HL, or a combination of these two agents by …

A Deep Learning Tool For The Assessment Of Pavement Smoothness And Aggregate Segregation During Construction, Mostafa Elseifi, Ramchandra Paudel, Md Tanvir Ahmed Sarkar, Hossam Abohamer, Nirmal Dhakal

Publications

Pavement construction monitoring and quality assurance (QA) practices are mostly based on costly, discrete, and destructive methods. Most quality assurance programs are based on pavement construction procedures encompassing in-situ coring for layer thickness determination, density measurements, laboratory testing to measure volumetric properties, and smoothness measurements in case of the availability of a profiler. The main objective of this study was to develop a machine learning-based classifier for predicting pavement roughness and aggregate segregation based on digital image analysis, image recognition, and deep learning machine models. The developed Convolution Neural Networks (CNN) models were trained, tested, and validated using 600-pavement surface …

Autonomous Vehicles On The Smart Roads: Challenges And Potentials, Laura Cristancho, Baleki Campbell, Mahyar Amirgholy

The Kennesaw Journal of Undergraduate Research

Self-driving vehicles and smart roads are not new concepts. These ideas have been discussed for many years but for much of this time, the required technology was not available to make them a reality. Just recently has our technology caught up to our ideas and we are beginning to see progress towards the realization of the automated highway system. As the transition to a complete automated system is still in progress, this leaves many questions that still need to be answered as well as allowing for novel solutions to be presented. Using modern research papers to formulate a sound basis …

Causes Of Cement Concrete Pavement Diseases In High-Cold And High-Altitude Areas And Progress In Repairing Techniques, Tiejun Hou

International Conference on Durability of Concrete Structures

The climatic characteristics of high-cold and high-altitude areas are low temperature, large temperature differences, and strong ultraviolet radiation. This paper analyzes the causes of cement concrete pavement diseases in high-cold and high-altitude areas and summarizes the common disease types of cement concrete pavements in high-cold and high-altitude areas. Moreover, new repair techniques to improve the maintenance quality of cement concrete pavements in high-cold and high-altitude areas are introduced.

Dlr Covid-19 Mobility Review - Coastal Mobility Route (Ph1b): Mobility Update, Sarah Rock Dr, Dave O'Connor, Michael Banim

Reports

The Phase 1b study is a follow up to the evaluation and review of the Phase 1 'Covid-19 Mobility and Public Realm Works' undertaken by Dun Laoghaire- Rathdown County Council in 2020, which included the development of the Coastal Mobility Route (new cycle infrastructure). These works were part of the Council's response to some of the urban and transport planning challenges associated with Covid-19.

This study reports on ongoing monitoring and evaluation of the changing mobility patterns in the region of the Coastal Mobility Route throughout 2021 and 2022, as government and societal responses to the Covid-19 pandemic changed and …

Wastewater-Derived Ammonia For A Green Transportation Fuel, Joseph Kalman, Maryam Haddad

Mineta Transportation Institute

The energy-water nexus (i.e., availability of potable water and clean energy) is among the most important problems currently facing society. Ammonia is a carbon-free fuel that has the potential to reduce the carbon footprint in combustion related vehicles. However, ammonia production processes typically have their own carbon footprint and do not necessarily come from sustainable sources. This research examines wastewater filtration processes to harvest ammonia for transportation processes. The research team studied mock wastewater solutions and was able to achieve ammonia concentrations above 80%(nanofiltration) and 90% (reverse osmosis). The research team also investigated the influence of transmembrane pressure and flow …

Manual For Asphalt Pavement Repair And Resurfacing Preparation, Dingxin Cheng, Gary Hicks, Roger D. Smith

Mineta Transportation Institute

Timely repairs of pavement defects are essential in protecting an important investment and asset that public agencies have. These repairs may be made as durable “stand-alone” repairs of isolated problems, or as part of preparations for a total resurfacing. This manual provides basic information on the planning, materials and construction aspects of common pavement repairs such as crack sealing, crack filling, and patching, as well as a broader look at other preparations needed for total resurfacing a pavement, whether the resurfacing is a surface treatment or a thin hot mix asphalt (HMA) overlay.

Connected Simulation For Work Zone Safety Application, Vahid Balali

Mineta Transportation Institute

Every year, over 60,000 work zone crashes are reported in the United States (FHWA 2016). Such work zone crashes have resulted in over 4,400 fatal and 200,000 non-fatal injuries in the last 5 years (FHWA 2016, BLS 2014). Apart from the physical and emotional trauma, the annual cost of these injuries exceeds $4 million-representing significant wasted resources. To improve work zone safety, this research developed a system architecture for unveiling high-risk behavioral patterns among highway workers, equipment operators, and drivers within dynamic highway work zones. This research implemented the use of a connected virtual environment, which is an immersive hyper-realistic …

Contracting Strategies: A Different Approach To Address Long-Term Performance, Maria Calahorra-Jimenez

Mineta Transportation Institute

For cost-efficiency, public safety, and sustainability, improving long-term performance in highway projects is imperative for public administrations. Project delivery and procurement methods provide an opportunity to align design and construction processes with this goal. While previous studies have explored whether project delivery methods impact the long-term performance of highway projects, these studies did not focus on how core elements within project procurement relate to long-term performance. Thus, to fill this gap, this research explores how and to what extent long-term evaluation criteria are considered in design-build best-value procurement of highway projects. To this end, the team conducted content analysis on …

Managing The Curb: Understanding The Impacts Of On-Demand Mobility On Public Transit, Micromobility, And Pedestrians, Susan Shaheen, Elliot Martin, Adam Cohen, Jacquelyn Broader, Richard Davis

Mineta Transportation Institute

In recent years, innovative mobility and shifts in travel and consumption behavior are changing how people access and use the curb. Shared mobility—the shared use of a vehicle, bicycle, scooter, or other mode—coupled with outdoor dining, curbside pick-up, and robotic delivery are creating new needs related to the planning, management, and enforcement of curb access. This study examines curb planning and management from several angles, such as safety, social equity, and multimodal connections. This research employs a multi-method approach to identify the changing needs for curb space management and how to meet these needs through new planning and implementation policies …

Modelling Monthly Rainfall Of Calabar, Nigeria Using Box-Jenkins (Arima) Method, Francis Ogbozige

Tanzania Journal of Engineering and Technology (TJET)

Rainfall has both positive and negative effects on human activities hence, correct prediction of the period of occurrence is very essential. However, the traditional method of predicting months of heavy rainfall is gradually fading out as irregular rainfall pattern is been experienced in most regions of the world. The rainfall pattern in Calabar city in Southern Nigeria has been reported in past literatures of being irregular. Hence, this research applied the Auto-Regressive Integrated Moving Average (ARIMA) also known as Box-Jenkins method to model the rainfall pattern of Calabar. This was achieved by subjecting 50years monthly rainfall (1971 – 2020) to …

Phased Construction Bridges: Monitoring And Analysis For Traffic-Induced Vibration, Khalid Al-Kady, Christine E. Wittich, Richard L. Wood, George Morcous

Nebraska Department of Transportation: Research Reports

Phased construction is a common technique utilized to allow bridges to remain partially open to traffic throughout the construction process. The segment of the bridge deck that is constructed second cures under the effect of traffic-induced vibration transmitted from the adjacent bridge-deck segment, which is open to traffic. However, subjecting bridge decks to traffic-induced vibration during early-age curing raises concerns about the durability of the decks. The primary goal of this study is to generate a fundamental understanding of the transmission of traffic-induced vibration, the extent of degradation on phased construction bridge decks, and the impact of potential mitigation measures. …

Specialized Safety Training And Tracking For Kytc Construction And Maintenance Personnel, Gabriel Dadi, Ashtarout Ammar, Seth Atkins, Martha Horseman

Kentucky Transportation Center Research Report

High-quality safety training is critical for educating employees in the highway construction and maintenance industry about workplace hazards and giving them tools to remove and/or minimize associated risks. But researchers and state transportation agencies have not committed enough resources to develop safety trainings that address the unique needs of this sector. This report fills in this gap for the Kentucky Transportation Cabinet (KYTC) by cataloguing safety training resources available through other state and federal transportation agencies, documenting trainings available to Cabinet staff, identifying and prioritizing training gaps, and critically evaluating the content, quality, and duration of training resources. A web-based …