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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 …


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 …


Understanding Changes In Land Use Patterns At A Parcel Level In Central Florida Counties (Orange, Seminole, Osceola), Youssef Mohamed Abdelaziz Elsebaie Jan 2023

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, 2020-2023

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 …


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 …


Assessment Of Midblock Pedestrian Crossing Facilities Using Surrogate Safety Measures And Vehicle Delay, Nafis Anwari Jan 2023

Assessment Of Midblock Pedestrian Crossing Facilities Using Surrogate Safety Measures And Vehicle Delay, Nafis Anwari

Graduate Thesis and Dissertation 2023-2024

This dissertation has contributed to the pedestrian safety literature by assessing and comparing safety benefits and traffic efficiency among midblock Rectangular Rapid Flashing Beacon (RRFB) and Pedestrian Hybrid Beacon (PHB) sites. Video trajectory data were used to calculate pedestrian Surrogate Safety Measures (SSMs) and vehicles' delay. Regression models of SSMs and vehicles' delay revealed that PHB sites offer more safety benefits, at the expense of increased vehicles' delay, compared to RRFB sites. The presence of the PHB, weekday, signal activation, lane count, pedestrian speed, vehicle speed, land use mix, traffic flow, time of day, and pedestrian starting position from the …


Spatial Ensemble Distillation Learning Based Real-Time Crash Prediction And Management Framework, Md Rakibul Islam Jan 2023

Spatial Ensemble Distillation Learning Based Real-Time Crash Prediction And Management Framework, Md Rakibul Islam

Graduate Thesis and Dissertation 2023-2024

Real-time crash prediction is a complex task, since there is no existing framework to predict crash likelihood, types, and severity together along with a real-time traffic management strategy. Developing such a framework presents various challenges, including not independent and identically distributed data, imbalanced data, large model size, high computational cost, missing data, sensitivity vs. false alarm rate (FAR) trade-offs, estimation of traffic restoration time after crash occurrence, and real-world deployment strategy. A novel spatial ensemble distillation learning modeling technique is proposed to address these challenges. First, large-scale real-time data were used to develop a crash likelihood prediction model. Second, the …


Enabling Large-Scale Transportation Electrification For Shared And Connected Mobility Systems, Md Rakibul Alam Jan 2023

Enabling Large-Scale Transportation Electrification For Shared And Connected Mobility Systems, Md Rakibul Alam

Graduate Thesis and Dissertation 2023-2024

Owing to advancements in technology, substantial investments within the automotive industry, and the formulation of supportive state policies, the future landscape of the transportation sector is poised to witness a shift from traditional internal combustion engine vehicles (ICEVs) to electric vehicles (EVs). While EVs have made inroads in the market, they still face significant hurdles in the form of range anxiety and prolonged charging durations, inhibiting their widespread adoption. To tackle these challenges, a comprehensive approach to smart transportation electrification is proposed, emphasizing the pivotal roles of infrastructure development, particularly in the allocation of charging stations, and strategic operational decisions, …


Safety Considerations For Setting Variable Speed Limits On Freeways, Md Tarek Hasan Jan 2023

Safety Considerations For Setting Variable Speed Limits On Freeways, Md Tarek Hasan

Graduate Thesis and Dissertation 2023-2024

This thesis focuses on evaluating the appropriate speed at which vehicles should travel under different traffic conditions on freeways and its impact on crash frequency. The common belief is that the lower speed results in fewer crashes as reduced speed provides drivers with more time to react effectively and avoid collisions. However, this perspective overlooks the interplay among traffic speed, average spacing between consecutive vehicles, and the distance available for stopping a vehicle. Hence, we propose a safety parameter termed ‘Safety Correlate' (SCORE), which is defined as the proportion of average spacing relative to the stopping distance. To determine the …