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Transportation Electrification In Interdependent Power And Transportation Systems - Analysis, Planning, And Operation, Sina Baghali Aug 2023

Transportation Electrification In Interdependent Power And Transportation Systems - Analysis, Planning, And Operation, Sina Baghali

Electronic Theses and Dissertations, 2020-2023

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 Aug 2023

Understanding Evacuation Traffic Safety Issues During Hurricane Evacuation Using Machine Learning And Connected Vehicle Data, Zaheen E Muktadi Syed

Electronic Theses and Dissertations, 2020-2023

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 …


Investigation Of Ground Deformations And Vibrations Due To Impact Pile Driving: Measurements And Prediction Model, Berk Turkel Aug 2023

Investigation Of Ground Deformations And Vibrations Due To Impact Pile Driving: Measurements And Prediction Model, Berk Turkel

Electronic Theses and Dissertations, 2020-2023

Pile driving, a commonly used method for installing deep foundations, has gained prominence as a foundation solution to transfer structural loads to deep competent strata. However, this method of installation can generate noise, ground vibrations, and deformations. These effects pose risks to adjacent structures and buried utilities, jeopardizing the safety and serviceability of urban infrastructure. Researchers and public and private agencies have proposed many vibration limit criteria to avoid damage to infrastructure. However, these criteria for construction vibrations are not linked to the ground densification associated with repetitive and cumulative loadings in sandy soils. This dissertation focuses on developing a …


Optimizing Information Values In Smart Mobility, Fatima Afifah Aug 2023

Optimizing Information Values In Smart Mobility, Fatima Afifah

Electronic Theses and Dissertations, 2020-2023

Smart mobility, enabled by advanced sensing, communication, vehicle, and emerging mobility technologies, has transformed transportation systems. Real-time information shared by public and private entities plays a pivotal role in smart mobility, which facilitates informed decision-making, including effective mode choice, dynamic vehicle control, optimized travel routing, and strategic vehicle relocation. While more information is believed to benefit individual decision makers, it is crucial to acknowledge that the effects of information on transportation network performance are contingent; more information may not always benefit the safety and mobility of the whole system. The goal of this dissertation is to investigate the effects of …


Modeling Individual Activity And Mobility Behavior And Assessing Ridesharing Impacts Using Emerging Data Sources, Jiechao Zhang Jan 2023

Modeling Individual Activity And Mobility Behavior And Assessing Ridesharing Impacts Using Emerging Data Sources, Jiechao Zhang

Electronic Theses and Dissertations, 2020-2023

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 …


Time-Specific Safety Performance Functions For Different Advanced Traffic Management Strategies, Jingwan Fu Jan 2023

Time-Specific Safety Performance Functions For Different Advanced Traffic Management Strategies, Jingwan Fu

Electronic Theses and Dissertations, 2020-2023

Time-specific Safety Performance Functions (SPFs) were proposed to achieve accurate and dynamic crash frequency predictions and bridge the gap between annual crash frequency prediction and real-time crash likelihood prediction. This research proposed time-specific SPFs considering the temporal variation in crashes and traffic characteristics. Firstly, the developed time-specific SPFs that include different ATM strategies (i.e., HOV, merge, diverge and reversible lanes segments) were investigated in this study. The results indicate that the traffic turbulence during specific hours would relate to crash occurrence. Further, the variables that represent the speed and occupancy differences between the HOV lanes/reversible lanes and general-purpose lanes were …


Developing A Physics-Informed Deep Learning Paradigm For Traffic State Estimation, Jiheng Huang Jan 2023

Developing A Physics-Informed Deep Learning Paradigm For Traffic State Estimation, Jiheng Huang

Electronic Theses and Dissertations, 2020-2023

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 …


Development,Validation, And Integration Of Ai-Driven Computer Vision System And Digital-Twin System For Traffic Safety Dignostics, Ou Zheng Jan 2023

Development,Validation, And Integration Of Ai-Driven Computer Vision System And Digital-Twin System For Traffic Safety Dignostics, Ou Zheng

Electronic Theses and Dissertations, 2020-2023

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 …


Social Media-Based Crisis Communication: Analysis Of Twitter Data From Local Agencies During Hurricane Irma, Naiyara Noor Jan 2023

Social Media-Based Crisis Communication: Analysis Of Twitter Data From Local Agencies During Hurricane Irma, Naiyara Noor

Electronic Theses and Dissertations, 2020-2023

As social media platforms have become vital means of communications, it has become imperative for emergency managers and policy makers to understand how people are interacting with different agencies on these platforms for enhancing community response coordination during disasters. Although many public agencies have already adopted social media platforms for crisis communication purposes, empirical evidence on whether and how these agencies are effectively engaged on these platforms is lacking. This research aims to examine crisis communication activities of a variety of agencies on Twitter in response to Hurricane Irma in 2017. In this study, we analyzed 13,353 hurricane-related tweets posted …


A Generalized Accelerated Failure Time Model To Predict Restoration Time From Power Outages, Tasnuba Binte Jamal Jan 2023

A Generalized Accelerated Failure Time Model To Predict Restoration Time From Power Outages, Tasnuba Binte Jamal

Graduate Thesis and Dissertation 2023-2024

Major disasters such as wildfire, tornado, hurricane, tropical storm, flooding cause disruptions in infrastructure systems such as power outage, disruption to water supply system, wastewater management, telecommunication failures, and transportation facilities. Disruptions in electricity infrastructures have negative impacts on sectors throughout a region, including education, medical services, financial, and recreation sectors. In this study, we introduce a novel approach to investigate the factors which can be associated with longer restoration time of power service after a hurricane. Considering restoration time as the dependent variable and utilizing a comprehensive set of county-level data, we have estimated a Generalized Accelerated Failure Time …