Transportation Engineering Commons^™

Statewide Corridor Evacuation Response And Re-Entry Behaviors In Florida During Hurricane Irma, Xin Wang, Yuan Zhu, Hong Yang, Kun Xie

Electrical & Computer Engineering Faculty Publications

Hurricane Irma stands as one of the most destructive tropical storms to make landfall in the United States, particularly impacting the State of Florida, where it prompted the largest evacuation in history with approximately 7 million residents. The profound consequences of mass evacuation underscore the critical need to understand travel behaviors during hurricane evacuation and the recovery process. This research analyzes statewide evacuation and re-entry patterns, leveraging diverse datasets, including TTMS data from main corridors and GIS data. A statewide corridor-based empirical analysis framework is constructed to characterize evacuation and re-entry response patterns using sensor-based traffic observations. The results show …

Seat Belt Data Collection Methods: A Comparison Between States And National Guidelines, Madison R A Richards

Williams Honors College, Honors Research Projects

Thousands of fatalities related to vehicle crashes occur every year. One method to reduce fatalities is to encourage seat belt use compliance. To promote statistics regarding seat belt use, there first must be reliable data on seat belt compliance and this comes from good survey design.

This report is a comparative analysis of seat belt data collection methodologies for Ohio, Michigan, and Indiana, in addition to an evaluation of how each state aligns with standards set by the National Highway Traffic Safety Administration (NHTSA). The framework for this analysis focuses on NHTSA’s five core survey design requirements: selection of observation …

A Novel Federated Llm Framework For Distributed Traffic Modelling In Intelligent Transportation Systems, Seerat Kaur

Theses and Dissertations (Comprehensive)

Intelligent transportation systems (ITS) depend on accurate traffic prediction to support congestion management, infrastructure planning, and real-time operational decisions. Despite substantial progress in data-driven forecasting, several challenges continue to limit practical deployment: traffic data is distributed across independent regional authorities, making centralized aggregation infeasible, standard federated aggregation strategies ignore traffic-specific characteristics that meaningfully affect model quality, and existing models produce only numerical outputs without interpretable reasoning that urban planners can act upon. This thesis addresses these challenges through four contributions that collectively advance privacy-preserving, explainable, and scalable traffic forecasting.

The first contribution provides a systematic review of 129 peer-reviewed publications, …

Enhancing Traffic State Estimation At Bottlenecks Through Improved Demand Modeling: A Greenshields-Grounded Approach, Yuyan Annie Pan, Xianbiao Hu, Qing Tang, Yanyan Chen, Xuesong (Simon) Zhou

Civil & Environmental Engineering Faculty Publications

Accurate estimation of traffic state under oversaturated conditions is fundamental to a wide range of transportation applications. While intuitive, volume-to-capacity (q/qc) ratio-based link performance functions (LPF) are challenged by the U-shaped pattern of real-world speed-flow plots, which contradict the monotonic assumptions of link performance models such as the Bureau of Public Roads (BPR) function, particularly when q/q_c ≥ 1. This study addresses this critical gap by proposing an enhanced demand estimation method grounded in the Greenshields model, incorporating a real-time inflow correction factor to more accurately capture traffic demand at bottlenecks. In parallel, a modified LPF is introduced, replacing …

Iuse: A Gamified Virtual Learning Platform For Connected Vehicle Applications To Enhance Undergraduate Transportation Education, Tianyu Shen, Di Yang, Kai Sun, Hong Yang, Kun Xie, Mansoureh Jeihani

Civil & Environmental Engineering Faculty Publications

Emerging transportation technologies are rapidly reshaping transportation systems and industry practice. However, most transportation undergraduate curricula still emphasize foundational topics such as geometric design, travel demand forecasting, pavements, and soil properties, typically delivered through lecture-centric instruction. While these subjects remain essential to the discipline, they do not fully reflect the pace of technological change or provide sufficient opportunities for experiential learning with modern tools and data. This gap limits students’ exposure to CV concepts and their ability to translate theory into practice.

Focusing on a key emerging technology, connected vehicles (CVs), this paper bridges the above gap by introducing a …

Feasibility Of Quantifying The Dosage Of Zycotherm In Its Modified Asphalt Binders, Susmita Acharjee

College of Graduate Studies: Theses & Dissertations

The quantification of low-percentage additives in asphalt binders is challenging due to their minimal concentration and the complex composition of the binder matrix. Zycotherm, a nano-organosilane anti-stripping additive, is typically used in very small dosages (0.05%–0.20%), making its detection and quantification particularly difficult. This study investigated the feasibility of estimating Zycotherm dosage in asphalt binders by examining chemical and rheological and moisture responses. Two asphalt binder grades, PG 64-22 and PG 76-22, were modified with Zycotherm at dosages of 0.05%, 0.10%, 0.15%, and 0.20% by weight of binder, along with corresponding base binders. Laboratory experiments were conducted using Fourier Transform …

Workshop Outcomes Report: 2nd International Workshop On Seismic Resilience Of Arctic Infrastructure And Social Systems, Majid Ghayoomi, Daniela Morganti

Faculty Publications

The report provides an overview of the second international workshop on Seismic Resilience of Arctic Infrastructure and Social Systems. The report discusses agenda, workshop activities, interdisciplinary working groups, and results. It ends with several strategic questions and investigation plans that were developed as part of the workshop activities.

Integrated Corridor Management Framework For Severe Freeway Incidents, Sanjida Afroz Iqra

Graduate Studies Theses and Dissertations 2026

Traffic incidents are a major source of non-recurrent congestion on urban freeways, generating substantial mobility, safety, and economic impacts. Severe incidents that block multiple or all travel lanes are particularly disruptive because they degrade freeway operations and propagate congestion onto surrounding arterials. Effective Integrated Corridor Management (ICM) requires the ability to identify severe incidents, estimate their network-wide impacts, and anticipate the traffic conditions and driver behaviors that contribute to instability. This dissertation develops a data-driven ICM framework to address these challenges using real-world incident, crash, detector, and connected vehicle data from major Central Florida corridors, including I-4 and SR-417. The …

Bond Behavior Of Uhpc-Nsc Interfaces For Bridge Deck Repair Under Flexural Loading, Larissa Santiago La Banca

Graduate Studies Theses and Dissertations 2026

The use of ultra-high performance concrete (UHPC) has increased due to its superior mechanical properties and strong bond with normal-strength concrete (NSC). It is widely used as a repair material, particularly in bridge decks, where maintenance remains a challenge. However, the interface between UHPC and NSC is often the weakest region of the composite system and requires careful evaluation.

This study investigates the bond behavior between UHPC and NSC using different surface preparations, test setups, and UHPC materials. The experimental program included unreinforced beams with vertical interfaces tested under three- and four-point flexural loading, and reinforced slabs with horizontal interfaces …

Predicting Safety And Mobility Parameters Based On Comprehensive Analytics Of Connected Vehicle Data, Lei Han

Graduate Studies Theses and Dissertations 2026

Traffic safety and mobility remain critical challenges for modern transportation systems. The emergence of connected vehicle (CV) data offers unprecedented opportunities to capture microscopic, non-aggregated driving dynamics to support precise and finer-grained traffic safety and mobility research. This dissertation develops a comprehensive CV data–driven analytical framework to advance traffic safety and mobility research across multiple roadway contexts, including intersections, segments, freeways, and urban arterial networks. For traffic safety, this research extracts both longitudinal and lateral risky driving behaviors from CV trajectories and integrates them with macro-level roadway, traffic, and visual environment features. A spatial machine learning framework is proposed for …