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Full-Text Articles in Civil and Environmental Engineering
Transportation Electrification In Interdependent Power And Transportation Systems - Analysis, Planning, And Operation, Sina Baghali
Transportation Electrification In Interdependent Power And Transportation Systems - Analysis, Planning, And Operation, Sina Baghali
Electronic Theses and Dissertations, 2020-
Electric vehicles (EVs) are one of the eminent alternatives to decarbonize the transportation sector. However, large-scale EV adoption brings new challenges and opportunities to both transportation and power systems (TPSs). The challenges include the lack of understanding of EV driving behaviors and the associated charging demand (CD) distribution, the complex interaction of the decentralized decision-makers from TPSs, and the insufficient infrastructure from TPSs to accommodate the growing CD of EVs. On the other hand, the opportunities include benefiting the power systems by leveraging vehicle-to-grid (V2G) technologies and improving transportation mobility by incorporating strategic infrastructure planning. The goal of this dissertation …
Understanding Evacuation Traffic Safety Issues During Hurricane Evacuation Using Machine Learning And Connected Vehicle Data, Zaheen E Muktadi Syed
Understanding Evacuation Traffic Safety Issues During Hurricane Evacuation Using Machine Learning And Connected Vehicle Data, Zaheen E Muktadi Syed
Electronic Theses and Dissertations, 2020-
Hurricane evacuation, ordered to save lives of people of coastal regions, generates high traffic demand with increased crash risk. To mitigate such risk, transportation agencies need to anticipate highway locations with high crash risks to deploy appropriate countermeasures. With ubiquitous sensors and communication technologies, it is now possible to retrieve micro-level vehicular data containing individual vehicle trajectory and speed information. Such high-resolution vehicle data, potentially available in real time, can be used to assess prevailing traffic safety conditions. Using vehicle speed and acceleration profiles, potential crash risks can be predicted in real time. Previous studies on real-time crash risk prediction …
Developing A Physics-Informed Deep Learning Paradigm For Traffic State Estimation, Jiheng Huang
Developing A Physics-Informed Deep Learning Paradigm For Traffic State Estimation, Jiheng Huang
Electronic Theses and Dissertations, 2020-
The traffic delay due to congestion cost the U.S. economy $ 81 billion in 2022, and on average, each worker lost 97 hours each year during commute due to longer wait time. Traffic management and control strategies that serve as a potent solution to the congestion problem require accurate information on prevailing traffic conditions. However, due to the cost of sensor installation and maintenance, associated sensor noise, and outages, the key traffic metrics are often observed partially, making the task of estimating traffic states (TSE) critical. The challenge of TSE lies in the sparsity of observed traffic data and the …
Modeling Individual Activity And Mobility Behavior And Assessing Ridesharing Impacts Using Emerging Data Sources, Jiechao Zhang
Modeling Individual Activity And Mobility Behavior And Assessing Ridesharing Impacts Using Emerging Data Sources, Jiechao Zhang
Electronic Theses and Dissertations, 2020-
Predicting individual mobility behavior is one of the major steps of transportation planning models. Accurate prediction of individual mobility behavior will be beneficial for transportation planning. Although previous studies have used different data sources to model individual mobility behaviors, they have several limitations such as the lack of complete mobility sequences and travel mode information, limiting our ability to accurately predict individual movements. In recent years, the emergence of GPS-based floating car data (FCD) and on-demand ride-hailing service platforms can provide innovative data sources to understand and model individual mobility behavior. Compared to the previously used data sources such as …
Development,Validation, And Integration Of Ai-Driven Computer Vision System And Digital-Twin System For Traffic Safety Dignostics, Ou Zheng
Electronic Theses and Dissertations, 2020-
The use of data and deep learning algorithms in transportation research have become increasingly popular in recent years. Many studies rely on real-world data. Collecting accurate traffic data is crucial for analyzing traffic safety. Still, traditional traffic data collection methods that rely on loop detectors and radar sensors are limited to collect macro-level data, and it may fail to monitor complex driver behaviors like lane changing and interactions between road users. With the development of new technologies like in-vehicle cameras, Unmanned Aerial Vehicle (UAV), and surveillance cameras, vehicle trajectory data can be collected from the recorded videos for more comprehensive …
Understanding Changes In Land Use Patterns At A Parcel Level In Central Florida Counties (Orange, Seminole, Osceola), Youssef Mohamed Abdelaziz Elsebaie
Understanding Changes In Land Use Patterns At A Parcel Level In Central Florida Counties (Orange, Seminole, Osceola), Youssef Mohamed Abdelaziz Elsebaie
Electronic Theses and Dissertations, 2020-
In Florida, a state with significant population growth, it is essential to understand how land use change and transportation interact. Understanding these interactions between land use and transport is useful for transportation planners and land use modelers. Hence, in this research, we attempt to quantify the impact of the transportation system on land use and vice-versa. The research, using high-resolution land use data from 2011 to 2019, builds a binary logistic regression model of land use change. The model accounts for various independent variables, including socio-demographic attributes, built environment characteristics, and transportation network variables. The data set covers GIS data …
Assessing Public Perception And Proposing An Organized Questionnaire For The Deployment And Adoption Of Autonomous Vehicles, Md Rakibul Islam
Assessing Public Perception And Proposing An Organized Questionnaire For The Deployment And Adoption Of Autonomous Vehicles, Md Rakibul Islam
Electronic Theses and Dissertations, 2020-
Since the general public will play a central role in the evolution of AVs, research has been performed to assess their perception and acceptance of AVs. Nevertheless, the most potential users of AVs, i.e., young, students, and more educated people, have not received any particular focus in those studies. This research gap has motivated us to assess their perceptions. Extensive data analyses of the survey at the University of Central Florida with a sample of 315 reveal that on average 57% of the respondents were familiar with AVs, and about 44% of the respondents felt positive perceptions toward AVs. Around …
Generative Modeling Of Human Behavior: Social Interaction And Networked Coordination In Shared Facilities, Saumya Gupta
Generative Modeling Of Human Behavior: Social Interaction And Networked Coordination In Shared Facilities, Saumya Gupta
Electronic Theses and Dissertations, 2020-
Urbanization is bringing together various modes of transport, and with that, there are challenges to maintaining the safety of all road users, especially vulnerable road users (VRUs). Therefore, there is a need for street designs that encourages cooperation and resource sharing among road users. Shared space is a street design approach that softens the demarcation of vehicles and pedestrian traffic by reducing traffic rules, traffic signals, road markings, and regulations. Understanding the interactions and trajectory formations of various VRUs will facilitate the design of safer shared spaces. It will also lead to many applications, such as implementing reliable ad hoc …
Detecting And Tracking Vulnerable Road Users' Trajectories Using Different Types Of Sensors Fusion, Zhongchuan Wang
Detecting And Tracking Vulnerable Road Users' Trajectories Using Different Types Of Sensors Fusion, Zhongchuan Wang
Electronic Theses and Dissertations, 2020-
Vulnerable road user (VRU) detection and tracking has been a key challenge in transportation research. Different types of sensors such as the camera, LiDAR, and inertial measurement units (IMUs) have been used for this purpose. For detection and tracking with the camera, it is necessary to perform calibration to obtain correct GPS trajectories. This method is often tedious and necessitates accurate ground truth data. Moreover, if the camera performs any pan-tilt-zoom function, it is usually necessary to recalibrate the camera. In this thesis, we propose camera calibration using an auxiliary sensor: ultra-wideband (UWB). USBs are capable of tracking a road …
A Deep Learning Approach For Spatiotemporal-Data-Driven Traffic State Estimation, Amr Hatem Ragaa Abdelraouf
A Deep Learning Approach For Spatiotemporal-Data-Driven Traffic State Estimation, Amr Hatem Ragaa Abdelraouf
Electronic Theses and Dissertations, 2020-
The past decade witnessed rapid developments in traffic data sensing technologies in the form of roadside detector hardware, vehicle on-board units, and pedestrian wearable devices. The growing magnitude and complexity of the available traffic data has fueled the demand for data-driven models that can handle large scale inputs. In the recent past, deep-learning-powered algorithms have become the state-of-the-art for various data-driven applications. In this research, three applications of deep learning algorithms for traffic state estimation were investigated. Firstly, network-wide traffic parameters estimation was explored. An attention-based multi-encoder-decoder (Att-MED) neural network architecture was proposed and trained to predict freeway traffic speed …
An Econometric Analysis Of Domestic Aviation In The Us, Sudipta Dey Tirtha
An Econometric Analysis Of Domestic Aviation In The Us, Sudipta Dey Tirtha
Electronic Theses and Dissertations, 2020-
In this dissertation, we examine two dimensions of domestic aviation - demand and delay - that directly influence economic impact of the sector. We conduct a comprehensive analysis of airline demand employing airline data compiled by Bureau of Transportation Statistics. The demand analysis is conducted in three steps. First, we propose a novel modeling approach for modeling airline demand evolution over time. Specifically, we develop a joint panel group generalized ordered probit (GGOP) model system for modeling air passenger arrivals and departures in a discretized framework that subsumes the traditional linear regression approach. Further, we consider the influence of observed …
Automated Vehicle To Vehicle Conflict Analysis At Signalized Intersections By Camera And Lidar Sensor Fusion, Alabi Mehzabin Anisha
Automated Vehicle To Vehicle Conflict Analysis At Signalized Intersections By Camera And Lidar Sensor Fusion, Alabi Mehzabin Anisha
Electronic Theses and Dissertations, 2020-
This research presents an approach for safety diagnosis using sensor fusion techniques. This work fuses the outputs of a roadside low-resolution camera and a solid-state LiDAR. For vehicle classification and detection in videos, the YOLO v5 object detection model was utilized. The raw 3D point clouds generated by the LiDAR are processed by two manual steps - ground plane transformation and background segmentation, and two real-time steps - foreground clustering, and bounding box fitting. Taking the generated 2D bounding boxes of both camera and LiDAR, we associate the common bounding box pairs by thresholding on the Euclidean distance threshold of …
Development Of Active Learning Data Fixing Tool With Visual Analytics To Enhance Traffic Near-Miss Diagnosis, Jinyu Pei
Electronic Theses and Dissertations, 2020-
This study proposes a software to upgrade the UCF SST's Automated Roadway Conflicts Identification System (ARCIS), a pixel-to-pixel manner automated safety diagnostics and conflict identification system. The system is developed to extract vehicles' trajectories and traffic parameters using unmanned aerial vehicles (UAV) video and utilizing deep learning techniques. A user-friendly tool to improve rapid system development with active-learning, data analysis, and visualization techniques is introduced, which is capable of traffic safety near-miss diagnostics based on the ARCIS output. Multiple approaches are used to enhance the system performance, including video stabilization, object filtering, stitching multiple videos, vehicle detection and tracing. In …
A Spatiotemporal Evaluation Of Freeway Traffic Demand In Florida During Covid-19 Pandemic, Md Istiak Jahan
A Spatiotemporal Evaluation Of Freeway Traffic Demand In Florida During Covid-19 Pandemic, Md Istiak Jahan
Electronic Theses and Dissertations, 2020-
This thesis contributes to our understanding of the changes in traffic volumes on major roadway facilities in Florida due to COVID-19 pandemic from a spatiotemporal perspective. Three different models were tested in this study- a) Linear regression model, b) Spatial Autoregressive Model (SAR) and c) Spatial Error Model (SEM). For the model estimation, traffic volume data for the year 2019 and 2020 from 3,957 detectors were augmented with independent variables, such as- COVID-19 case information, socioeconomics, land-use and built environment characteristics, roadway characteristics, meteorological information, and spatial locations. Traffic volume data was analyzed separately for weekdays and holidays. SEM models …
High Fidelity Injury Severity Analysis Using Econometric Modeling Approaches, Ahmed Kabli
High Fidelity Injury Severity Analysis Using Econometric Modeling Approaches, Ahmed Kabli
Electronic Theses and Dissertations, 2020-
Crash severity models are typically developed using police reported injury severity databases. However, several research studies have identified various challenges associated with police reported data. Therefore, the current dissertation is focusing on developing high resolution crash severity models based on medical professional driver injury severity reported using Abbreviated Injury Scale for eight body regions. The dissertation focused on developing a disaggregate injury severity modeling framework that can enhance the estimation accuracy of independent variable impacts on severity. Within this broad research vision, the dissertation has multiple objectives. First, a joint random parameters multivariate model structure with as many dimensions as …
Using Machine Learning Technique To Develop A Deterioration Predicting Model For Pavement Marking In Florida, Ehab Abdelmaksoud
Using Machine Learning Technique To Develop A Deterioration Predicting Model For Pavement Marking In Florida, Ehab Abdelmaksoud
Electronic Theses and Dissertations, 2020-
Longitudinal pavement markings play a significant role on the roadways by delivering information to motorists to help them navigate and follow the road. These markings are also considered to be a crucial control device that can enhance ideal nighttime visibility, especially on rural roads where the surrounding luminance is insufficient. Hence, the main question for public agencies or officials is about when the replacement of the pavement markings needs to take place. The Federal Highway Administration (FHWA) is considering proposing a minimum level of retroreflectivity standard and based on that, the Manual on Uniform Traffic Control Devices (MUTCD) set aside …
Machine Learning Algorithms For Forecasting The Impacts Of Connected And Automated Vehicles On Highway Construction Costs, Amirsaman Mahdavian
Machine Learning Algorithms For Forecasting The Impacts Of Connected And Automated Vehicles On Highway Construction Costs, Amirsaman Mahdavian
Electronic Theses and Dissertations, 2020-
A multitude of externalities affects transport efficiency and numbers of trips. Population expansion, urban development, political issues, fiscal trends, and growth in the field of connected, automated, shared, and electric (CASE) vehicles have all played prominent roles. While the market is keenly aware of the upcoming shift to the CASE vehicles, the transformation itself is reliant upon the development of technologies, customer outlook, and guidelines. The purpose of this research is to establish an overview of the possible network design problems, as well as potential consequences to vehicle automation systems by employing machine learning and system dynamics analysis. Finally, the …
Analytical Study Of Deep Learning Methods For Road Condition Assessment, Elham Eslami
Analytical Study Of Deep Learning Methods For Road Condition Assessment, Elham Eslami
Electronic Theses and Dissertations, 2020-
Automated pavement distress recognition is a key step in smart infrastructure assessment. Advances in deep learning and computer vision have improved the automated recognition of pavement distresses in road surface images. This task, however, remains challenging due to the high variations in road objects and pavement types, variety of lighting condition, low contrast, and background noises in pavement images. In this dissertation, we propose novel deep learning algorithms for image-based road condition assessment to tackle current challenges in detection, classification and segmentation of pavement images. Motivated by the need for classifying a wide range of objects in road monitoring, this …
Distracted Driving And Pedestrians' Effects On Headway At Signalized Intersections, Bassel Elgamal
Distracted Driving And Pedestrians' Effects On Headway At Signalized Intersections, Bassel Elgamal
Electronic Theses and Dissertations, 2020-
Distracted driving and pedestrians pose one of the most difficult challenges to ensuring a safe and efficient transportation system. Modern communications have delivered greater convenience. However, this has come at the cost of attention spans. Safety has been thoroughly explored in terms of distracted driving and pedestrians. However, impacts on traffic operations have received minimal research attention. Few studies provided a theoretical mechanism on how intersection operations can be affected but failed to quantify the real-life impacts on traffic operations. Furthermore, new Florida laws prohibit cellphone usage while driving but is allowed when the vehicle is stationary, which may result …
Effect Of Various Speed Management Strategies On Bicycle Crashes For Urban Roads In Central Florida, Jorge Ugan
Effect Of Various Speed Management Strategies On Bicycle Crashes For Urban Roads In Central Florida, Jorge Ugan
Electronic Theses and Dissertations, 2020-
In recent years, cycling has become an increasingly popular transportation mode around the world. In contrast to other popular modes of transportation, cycling is more economic and energy efficient. While many studies have been conducted for the bicycle safety analysis, most of them were limited in terms of bicycle exposure data and on-street data. This study tries to improve the current safety performance functions for bicycle crashes at urban corridors by utilizing crowdsource data from STRAVA and on-street speed management strategies data. Speed management strategies are any roadway alterations that causes a change in motorists' driving behavior. In Florida, these …
Data Driven Methods For Large Scale Network Level Traffic Modeling, Rezaur Rahman
Data Driven Methods For Large Scale Network Level Traffic Modeling, Rezaur Rahman
Electronic Theses and Dissertations, 2020-
Rapid growth in population along with urban-centric activities impose a massive demand on existing transportation systems, thus increasing traffic congestion and other mobility related challenges. To overcome such challenges, we need network-scale models to accurately predict real-time traffic demand and associated congestion. However, traditional network modeling approaches have shortcomings due to the complexity in traffic flow modeling, limited scope to incorporate real-time data available from emerging data sources and requiring excessive computation time to generate accurate estimation of traffic flows. Advancement in traffic sensing technologies with big data has created a new opportunity to overcome these challenges and implement deployable …
Modeling Of Crash Risk For Realistic Artificial Data Generation: Application To Naturalistic Driving Study Data, Lauren Hoover
Modeling Of Crash Risk For Realistic Artificial Data Generation: Application To Naturalistic Driving Study Data, Lauren Hoover
Electronic Theses and Dissertations, 2020-
Most safety performance analysis employs cross-sectional and time-series datasets, posing an important challenge to safety performance and crash modification analysis. The traditional safety model analysis paradigm relying on observed data only allows relative comparisons between analysis methods and is unable to establish how well the methods mimic the true underlying crash generation process. Assumptions are made about the data, but whether the assumptions truly characterize the safety data generation in the real world remains unknown. To address this issue, this thesis proposes the generation of realistic artificial data (RAD). In developing a prototype RAD generator for crash data, we mimic …
Improving Pedestrian Safety Using Video Data, Surrogate Safety Measures And Deep Learning, Shile Zhang
Improving Pedestrian Safety Using Video Data, Surrogate Safety Measures And Deep Learning, Shile Zhang
Electronic Theses and Dissertations, 2020-
The research aims to improve pedestrian safety at signalized intersections using video data, surrogate safety measures and deep learning. Machine learning (including deep learning) models are proposed for predicting pedestrians' potentially dangerous situations. On the one hand, pedestrians' red-light violations can expose the pedestrians to motorized traffic and pose potential threats to pedestrian safety. Thus, the prediction of pedestrians' crossing intention during red-light signals is carried out. The pose estimation technique is used to extract features on pedestrians' bodies. Machine learning models are used to predict pedestrians' crossing intention at intersections' red-light, with video data collected from signalized intersections. Multiple …
Remediation Of Roadway Runoff Nutrients: Querying Sources Delivery Mechanism, Efficacy Of Stormwater Best Management Practices, And Stormwater Routing Through Karst Geology, Mohammad Shokri
Electronic Theses and Dissertations, 2020-
Stormwater road runoff is a widespread non-point source of contaminants such as nutrients, which endangers water bodies, especially in vulnerable karst areas such as Florida. While roadside vegetated filter strips (VFSs) and stormwater basins are generally accepted best management practices (BMPs) for stormwater management, uncertainties about VFS nutrient removal are reported and stormwater basins are concerned of facilitating contaminant transport. In this dissertation, the application and efficacy of engineered infiltration media was tested as a subgrade for the enhanced nutrient removal from roadway runoff. Results of field-scale laboratory testing indicated that a VFS with engineered biosorption activated media (BAM) outperformed …
Evaluation Of Unconventional Signalized Intersections On Arterial Roads And A Proposition For A Novel Intersection Design, Ma'en Al-Omari
Evaluation Of Unconventional Signalized Intersections On Arterial Roads And A Proposition For A Novel Intersection Design, Ma'en Al-Omari
Electronic Theses and Dissertations, 2020-
Several unconventional intersection designs were proposed and implemented to enhance traffic safety and operation at intersections. The efficiency of these intersection designs was not sufficiently evaluated in the previous research because of the limited implementation of such designs. However, with the growing interest in the implementation of unconventional intersections by municipalities and transport agencies, it has become a need for a comprehensive evaluation of their safety and operational benefits. Therefore, this dissertation aims to evaluate the safety and operational aspects of unconventional intersection designs by employing different research approaches: crash analysis, microscopic simulation, and driving simulation. Firstly, this dissertation evaluated …
Crash Analysis And Development Of Safety Performance Functions For Florida Roads In The Framework Of The Context Classification System, Ma'en Al-Omari
Crash Analysis And Development Of Safety Performance Functions For Florida Roads In The Framework Of The Context Classification System, Ma'en Al-Omari
Electronic Theses and Dissertations, 2020-
Nowadays, technology is employed in many safety applications and countermeasures that would enhance traffic safety by influencing some crash-related factors. Therefore, crash-related factors must be determined for every roadway element by the development of safety performance functions. Safety performance functions (SPF) are employed to predict crash counts at the different roadway elements. Several SPFs have been developed for the various roadway elements based on different classifications such as functional classification and area type. Since a more detailed classification of roadway elements leads to more accurate crash predictions, multiple states have developed new system to categorize roads based on a comprehensive …
Identifying The Links Between Mental Frameworks, Context Features, And Driver Attention In Complete Streets Environments, Patricia Tice
Identifying The Links Between Mental Frameworks, Context Features, And Driver Attention In Complete Streets Environments, Patricia Tice
Electronic Theses and Dissertations, 2020-
Complete street systems integrate a wide range of users in the same space, with unequal risks and responsibilities. This makes driver attention a critical factor in assuring the safety of vulnerable users. The Conditioned Anticipation of People psychological model of driver attention proposes that drivers reflexively reengage their metacognitive processes when they anticipate visually interacting with the human face or form due to the neurological priority that the brain places on human recognition. To test this model, an eye-tracking tabulation was generated from the SHRP2 Naturalistic Driving Study that measured midsegment percent of time on-task and multitasking behavior for 200 …
Monitoring Of Microscopic Traffic Behavior For Safety Applications Using Temporal Logic, Mariam Wessam Hassan Mohamed Nour
Monitoring Of Microscopic Traffic Behavior For Safety Applications Using Temporal Logic, Mariam Wessam Hassan Mohamed Nour
Electronic Theses and Dissertations, 2020-
Smart cities are revolutionizing the transportation infrastructure by the integration of technology. However, ensuring that various transportation system components are operating as expected and in a safe manner is a great challenge. One of the proposed solutions is traffic monitoring systems which collect and analyze traffic data for the safe operation and management of the overall system. Even though traffic safety analysis has been tied to crash data, surrogate safety measures (SSM) have recently emerged as a replacement. SSM can provide a convenient alternative for understanding the impact of conflicts on overall road safety. Traditionally, conflicts were studied through manual …
Applying Machine Learning Techniques To Improve Safety And Mobility Of Urban Transportation Systems Using Infrastructure- And Vehicle-Based Sensors, Zubayer Islam
Electronic Theses and Dissertations, 2020-
The importance of sensing technologies in the field of transportation is ever increasing. Rapid improvements of cloud computing, Internet of Vehicles (IoV), and intelligent transport system (ITS) enables fast acquisition of sensor data with immediate processing. Machine learning algorithms provide a way to classify or predict outcomes in a selective and timely fashion. High accuracy and increased volatility are the main features of various learning algorithms. In this dissertation, we aim to use infrastructure- and vehicle-based sensors to improve safety and mobility of urban transportation systems. Smartphone sensors were used in the first study to estimate vehicle trajectory using lane …
Safety And Operations Of Urban Arterials Incorporating The Context Classification System, Nada Mahmoud
Safety And Operations Of Urban Arterials Incorporating The Context Classification System, Nada Mahmoud
Electronic Theses and Dissertations, 2020-
Urban arterials connect multiple areas in the city and encourage non-motorist activities. Hence, the safety and operations on urban arterials is vital as they improve the mobility of daily commuters and road users. This research aims to facilitate traffic operations on urban arterials by proposing multiple mythological approaches to estimate and predict turning movement counts at signalized intersections using traffic data from adjacent intersections. Further, it aims to improve the safety by developing crash prediction models, identifying the hotspots for multiple crash types, and indicating the factors contributing to operating speed as well as non-motorist crashes. The analyses included tuning, …