Transportation Commons^™

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 …

Interpretable Machine Learning For Bridge-Pier Scour Prediction And Flood Resilience, Adil Khan, Dalya Ismael

Engineering Technology Faculty Publications

Bridge-pier scour is a leading cause of flood-induced bridge failure, yet practice still lacks transparent, physics-informed tools that link data-driven prediction with design guidance. This study develops an interpretable, physics-aware machine-learning framework to predict equilibrium scour depth and translate those predictions into actionable strategies for flood-resilient infrastructure. Using the 2014 U.S. Geological Survey Pier-Scour Database (569 laboratory cases), five models: Gradient Boosting, AdaBoost (Tree), XGBoost, Gaussian Process (RBF kernel), and Kernel Ridge (polynomial), were trained and evaluated with K-fold cross-validation. Model performance was evaluated using R², RMSE, and MAE. Gradient Boosting performed best, achieving training and testing R² of 0.99 …

Modeling The Impacts Of Disruptive Events On Driving Behaviors, Transportation Safety, And Equity: Advanced Statistical Insights From The Covid-19 Pandemic, Xiaomeng Dong

Civil & Environmental Engineering Theses & Dissertations

This dissertation aims to understand how disruptive events —particularly the COVID-19 pandemic—affect driving behaviors, transportation safety and equity by leveraging advanced statistical modeling techniques and data from Virginia. This research pursues three overarching objectives. First, it employs multigroup structural equation modeling (SEM) to uncover the complex interrelationships among risky driving behaviors, injury severity, and pandemic-related factors, delineating the mechanisms through which COVID-19 has impacted crash outcomes via changing risky driving behaviors. Second, it leverages hidden Markov models to trace shifts in safety states over the pre-, during-, and post-pandemic periods, determining whether and when safety conditions return to pre-pandemic norms. …

Long-Term Traffic Prediction Using Deep Learning Long Short-Term Memory, Ange-Lionel Toba, Sameer Kulkarni, Wael Khallouli, Timothy Pennington

School of Cybersecurity Faculty Publications

Traffic conditions are a key factor in our society, contributing to quality of life and the economy, as well as access to professional, educational, and health resources. This emphasizes the need for a reliable road network to facilitate traffic fluidity across the nation and improve mobility. Reaching these characteristics demands good traffic volume prediction methods, not only in the short term but also in the long term, which helps design transportation strategies and road planning. However, most of the research has focused on short-term prediction, applied mostly to short-trip distances, while effective long-term forecasting, which has become a challenging issue …

Psychosocial Determinants Of Public Transportation Use Among Brazilian And American Users: An Integrated Modeling Approach, Ingrid Luiza Neto, Hartmut Günther, Bryan E. Porter, Taciano L. Milfont, Pastor Willy Gonzales Taco, Caroline Cardoso Machado

Psychology Faculty Publications

Overreliance on cars can promote individual, environmental, economic and social problems, requiring the development of measures to reduce car use and encourage the use of more sustainable transport options. Contributing to this call, here we report a cross-cultural study conducted in Brazil (n = 312) and the United States (n = 518) investigating the applicability of the model of Bamberg and Möser in predicting the use of public transport. Results indicated the model is equivalent across samples, regarding both the measures and the relations between the variables of the model. Intention strongly predicted self-reported public transport behaviour, explaining 70% of …

Tracing The Development Of Trust In Automation/Autonomy In A Multitasking Environment, Tetsuya Sato

Psychology Theses & Dissertations

Future Advanced Air Mobility (AAM) operations will likely involve autonomous systems that exceed the capabilities of a typical automation. However, human operators could use such systems counterproductively by either misusing unreliable systems or disusing reliable systems. One determinant for inappropriate use of autonomous systems is trust. Human factors theorists proposed numerous ways to characterize trust such as the tripartite model of trust that describes the bases of trust in automation (i.e., performance, process, and purpose; Lee & See, 2004). Previous works have indicated that participants rated lower performance- and process-based trust toward the automation when the tracking task required more …

Young Driver Training And Socioeconomic Status: A Human-In-The-Loop Driving Simulator Evaluation, Jeffrey Edward Glassman

Psychology Theses & Dissertations

Previous research consistently shows that young drivers are poor at anticipating latent hazards on the roadway compared to more experienced drivers. The Road Awareness and Perception Training (RAPT) program is a driver training program that aims to accelerate young drivers’ learning of hazard anticipation (HA) skills. More recent research has started showing evidence that RAPT may be even more effective at reducing accidents for young drivers with a lower socioeconomic status (SES), though the direct impact of RAPT on HA skills in the driver population is yet unclear. The current experiment thus directly evaluated the effectiveness of RAPT on the …

Adopt: An Environmentally-Friendly System For Alerting Drivers To Occluded Pedestrians Traffic, Abrar Abdulrahman Alali

Computer Science Theses & Dissertations

The emergence of sensing technologies and vehicular communications has brought significant opportunities for enhancing pedestrian safety on city streets. However, existing solutions rely on costly technologies such as computer vision and trajectory prediction to detect crossing pedestrians, while they have limits in detecting pedestrians who are occluded by parked cars. Despite the presence of collaborative perception by surrounding vehicles and infrastructure, there is a notable absence of incorporating existing parked cars themselves due to their insufficiency in detecting pedestrians and communicating with other cars while they are turned off. Furthermore, accommodating pedestrians on streets has been linked to an additional …

Preserving Location Authenticity: Multi-Sensor System To Thwart Gps Spoofing In Self-Driving Vehicles, Peng Jiang

Electrical & Computer Engineering Theses & Dissertations

The ubiquity of the Global Positioning System (GPS) has cemented its role as the cornerstone for an array of location-based services and navigation systems, spanning applications from autonomous vehicles and drones to maritime vessels and wearable technology. Nonetheless, ensuring the integrity of reported geographical coordinates poses a formidable challenge, owing to the proliferation of diverse GPS spoofing tools. This predicament is compounded by the pervasive availability of tools like Fake GPS, Lockito, and software-defined radios, enabling even unsophisticated users to commandeer and disseminate counterfeit GPS coordinates. This dissertation undertakes the task of devising an encompassing and resilient framework, integrating a …

Modeling The Impact Of Connected And Automated Vehicles On Driving Behaviors And Safety: A Driving Simulator Study, Abdalziz Alruwaili

Civil & Environmental Engineering Theses & Dissertations

Connected vehicles (CVs), equipped with advanced sensors, can communicate safety messages to drivers. Automated vehicles (AVs), designed with the ability to automate safety critical control functions, will redefine the traditional role of drivers. This dissertation aims to investigate the impact of connected and automated vehicles (CAVs) on driving behaviors and safety outcomes using data from driving simulator experiments. More specifically, the research objectives include:

1. Modeling the impacts of CVs on driving aggressiveness and situational awareness in highway crash scenarios.

2. Modeling the impacts of CV technologies on driving behaviors and safety outcomes in highway crash scenarios under diverse weather …

A Comparison Of Machine Learning Surrogate Models Of Street-Scale Flooding In Norfolk, Virginia, Diana Mcspadden, Steven Goldenberg, Binata Roy, Malachi Schram, Jonathan L. Goodall, Heather Richter

Community & Environmental Health Faculty Publications

Low-lying coastal cities, exemplified by Norfolk, Virginia, face the challenge of street flooding caused by rainfall and tides, which strain transportation and sewer systems and can lead to personal and property damage. While high-fidelity, physics-based simulations provide accurate predictions of urban pluvial flooding, their computational complexity renders them unsuitable for real-time applications. Using data from Norfolk rainfall events between 2016 and 2018, this study compares the performance of a previous surrogate model based on a random forest algorithm with two deep learning models: Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU). The comparison of deep learning to the random …

Note On Fuel Consumption In Ocean Container Shipping: Bounds On Fuel Usage, Manwo Ng

Information Technology & Decision Sciences Faculty Publications

This paper contributes to the literature by deriving upper and lower bounds on the fuel consumption in container shipping. The bounds are derived from sailing distances, port times, and the possible arrival times at ports/ the berth windows negotiated between the ocean carrier and the port operators. Crucially, the derived bounds can be used in conjunction with any of the common fuel consumption functions proposed in the literature. This latter is especially important since currently there is no consensus on a specific functional form for the fuel consumption function. The behavior of the bounds will be illustrated with numerical examples.

Sustainable Maritime Shipping, Manwo Ng, Wayne K. Talley

Information Technology & Decision Sciences Faculty Publications

[Introduction] The maritime industry has witnessed an increasingly loud call to contribute to the global trend towards environmentally sustainable practices in recent years. In this context, the International Maritime Organization (IMO) has set the ambitious goal to reduce the greenhouse gas (GHG) emissions from shipping by at least 50% by 2050, compared to levels in 2008. To achieve such dramatic reductions, research contributing to sustainable maritime shipping has flourished in recent years. The goal of this special issue is to bring together the latest sustainable maritime transportation research in one place.

Advanced Air Mobility, Economic Impacts, And Equity Considerations, Robert M. Mcnab

Economics Faculty Publications

Advanced Air Mobility (AAM) may, in the coming decades, result in tens of thousands of new jobs and billions of dollars in additional economic activity. While much of the discussion surrounding AAM focuses on the technical aspects of the nascent industry, estimates of the potential economic impact vary significantly. Much less attention has been paid in the literature to potential externalities, positive and negative, and how these externalities may impact estimates of economic impact. We argue that much work remains to be done before policy advisors and decisions makers can formulate and implement strategies based on the projections of future …

Analysis Of Traffic Conflicts With Right Turning Vehicles At Unsignalized Intersections In Suburban Areas, Abbas Sheykhfard, Farshidreza Haghighi, Sarah Bakhtiari, Sara Moridpour, Kun Xie, Grigorios Fountas

Civil & Environmental Engineering Faculty Publications

Right-turn collisions at intersections are one of the most dominant crash types in suburban areas, especially at unsignalized intersections. There is, however, a lack of comprehensive research on the speed patterns of vehicles during right-turn manoeuvres and their impact on crashes. To provide an in-depth investigation of the factors determining the safety of right-turn manoeuvres, driving behaviour data were collected through an instrumented vehicle study. Using this data, binary logistic regression models were developed to identify the factors affecting the probability of Vehicle-Vehicle (V-V) and Vehicle-Pedestrian (V-P) conflicts at six suburban intersections in Babol, Iran, during right-turn stage manoeuvres. In …

Implications Of Alternative Communications And Sensing Technologies For Implementing Variable Speed Limit Control Through Connected Vehicles: Sag Curve As A Case Study, Reza Vatani Nezafat, Mecit Cetin, Elizabeth Williams, George F. List

Civil & Environmental Engineering Faculty Publications

Connected vehicles (CVs) will enable various applications to improve traffic flow. This paper's focus is to investigate how the potential implementation of variable speed limit (VSL) through different types of communication and sensing technologies on CVs makes it possible to mitigate congestion at a sag curve bottleneck. A VSL algorithm is developed and implemented in a simulation environment for controlling the inflow of vehicles to a sag curve to minimize delays and increase throughput. Both vehicle-to-vehicle (V2V) and infrastructure-to-vehicle (I2V) options for CVs are investigated when implementing the VSL control strategy in a simulation environment. Also, for measuring traffic density …

The Geometry Of Dynamic Time-Dependent Best-Worst Choice Pairs, Sasanka Adikari, Norou Diawara, Haim Bar

Mathematics & Statistics Faculty Publications

There has been increasing interest in best–worst discrete choice experiments (BWDCEs) in health economics, transportation research, and other fields over the last few years. BWDCEs have distinct advantages compared to other measurement approaches in discrete choice experiments (DCEs). A systematic study of best–worst (BW) choice pairs can be traced back to the 1990s. Recently, new ideas have been introduced to the subject. Calculating utility helps measure the attractiveness of BW choices. The goal of this paper is twofold. First, we extend the idea of the BW choice pair to include dynamic, time-dependent transition probability and capture utility at each time …

Quantification Of Landside Congestion In Ports: An Analysis Based On Gps Data, Kumushini Thennakoon, Namal Bandaranayake, Senevi Kiridena, Asela K. Kulatunga

Computer Science Faculty Publications

Hinterland transport is a critical segment in maritime cross-border logistics, which links the end-users of global supply chains to the maritime segment. Truck-based hinterland transport is known to cause congestion in and around ports. This study aimed to quantify the congestion caused by trucks at the Port of Colombo, which has not been a subject of a systematic study. To this end, the study makes use of GPS data. In addition to revealing heavy congestion within the port, the study also reveals significant variations in congestion during different times of the day with the duration of journeys peaking from 1200hrs …

Framing Automation Trust: How Initial Information About Automated Driving Systems Influences Swift Trust In Automation And Trust Repair For Human Automation Collaboration, Scott Anthony Mishler

Psychology Theses & Dissertations

The study examines how trust in automation is influenced by initial framing of information before interaction and how later active calibration methods can further influence trust repair or dampening after an automation error in a three-experiment study. As more human drivers begin to use automated driving systems (ADSs) for the first time, their initial understanding of the system can influence their trust leading to a miscalibration of trust. Prior studies have investigated how trust develops through interactions with an automated system, but few have looked at integrating swift trust and framing to calibrate trust before interaction and investigate further active …

Attention And Task Engagement During Automated Driving, James Richard Unverricht

Psychology Theses & Dissertations

Many young drivers suffer fatal crashes each year in the United States at a rate approximately three times greater than more experienced drivers. Automated driving systems may serve to mitigate young drivers high crash rates but remain underexplored in research. This dissertation project examined the effects of levels of automation and interestingness of auditory clips on latent hazard anticipation in young drivers during simulated driving. Participants drove a vehicle at varying levels of vehicle automation (SAE Level 0, 2, or 3) in simulated scenarios, each containing a latent hazard event during which a boring, neutral, or interesting auditory clip was …

An Advanced Simulation Architecture For Testing Autonomous And Connected Vehicles Enabled By Virtual Reality, Defu Cui

Electrical & Computer Engineering Theses & Dissertations

With the advancement of intelligent transportation systems, autonomous driving and connected driving are seen as potential solutions to alleviate traffic congestion, enhance traffic safety, and improve efficiency. Extensive testing and validation of autonomous vehicles (AVs) and connected vehicles (CVs) including connected autonomous vehicles are crucial to ensure their safety and reliability. However, testing and validating AVs and CVs on public roads faces challenges such as high costs, inadequate support from transportation infrastructure with communication technologies, and safety concerns, among others. Simulations have become essential tools for testing autonomous driving and connected driving. As mixed traffic involves multiple domains including traffic …

Electric Vehicle Routing Problem – Models And Algorithms, Hesamoddin Tahami

Engineering Management & Systems Engineering Theses & Dissertations

The transportation sector is a major greenhouse gas emitter that is heavily regulated to reduce its dependence on oil. These regulations along with the growing customer awareness of global warming have led to the investigation of new transportation problems that consider using eco-friendly vehicle fleets. Promising alternatives to traditional fleets include alternative fuel vehicles (AFVs) and electric vehicles (EVs). These twenty-first-century vehicles offer an appealing advantage of consistently reducing their environmental impact, but due to the current technology, they exhibit bothersome limitations. The short driving range along with limited charging infrastructure may consequently cause issues related to range anxiety, i.e., …

Improving Safety Service Patrol Performance, Mecit Cetin, Hong Yang, Kun Xie, Sherif Ishak, Guocong Zhai, Junqing Wang, Giridhar Kattepogu

Civil & Environmental Engineering Faculty Publications

Safety Service Patrols (SSPs) provide motorists with assistance free of charge on most freeways and some key primary roads in Virginia. This research project is focused on developing a tool to help the Virginia Department of Transportation (VDOT) optimize SSP routes and schedules (hereafter called SSP-OPT). The computational tool, SSP-OPT, takes readily available data (e.g., corridor and segment lengths, turnaround points, average annual daily traffic) and outputs potential SSP configurations that meet the desired criteria and produce the best possible performance metrics for a given corridor. At a high level, the main components of the developed tool include capabilities to: …

Economic Freedom And One-Way Truck Rental Prices: An Empirical Note, Alexander Cardazzi, Robert A. Lawson

Economics Faculty Publications

This study examines the one-way truck rental prices for 378 cities. There are large price differentials in one-way rental prices between city pairs. The pull of people toward higher economic freedom locales and push away from lower economic freedom locales is found to be an important determinant of the city-pair price differentials.

Are Ride-Hailing Services Safer Than Taxis? A Multivariate Spatial Approach With Accomodation Of Exposure Uncertainty, Guocong Zhai, Kun Xie, Hong Yang, Di Yang

Civil & Environmental Engineering Faculty Publications

Despite many research efforts on ride-hailing services and taxis, limited studies have compared the safety performance of the two modes. A major challenge is the need for reliable mode-specific exposure data to model their safety outcomes. Moreover, crash frequencies of the two modes by injury severities tend to be spatially and inherently correlated. To fully address these issues, this study proposes a novel multivariate conditional autoregressive model considering measurement errors in mode-specific exposures (MVCARME). More specially, a classical measurement error structure is used to accommodate the uncertainty of mode-specific exposures estimated, and a multivariate spatial specification is adopted to capture …

The Effects Of Flood Warning Information On Driver Decisions In A Driving Simulator Scenario, Katherine Rose Garcia

Psychology Theses & Dissertations

Flood warnings are a type of risk communication that alerts the public of potential floods. Flood warnings can be communicated through mobile devices and should convey enough information to keep the user safe during a flood situation. However, the amount of detail included in the warning, such as the depth of the flood, may vary. The purpose of this study was to: (a) extend our prior research on flood warnings by recreating the written driving scenarios into the driving simulator; (b) deepen the understanding of human decision-making in risky situations; and (c) investigate how to best inform drivers of floods …

The Impact Of First-Person Perspective Text And Images On Drivers’ Comprehension, Learning Judgments, Attitudes, And Intentions Related To Safe Road-Sharing Behaviors, Alexandra Bryson Proaps

Psychology Theses & Dissertations

Drivers and cyclists lack an alignment of road sharing knowledge, attitudes, and expectations, resulting in unnecessary fatalities. Educational countermeasures need to present information that captures drivers’ interest by being personally relevant, facilitate elaboration and synthesis of new information with existing knowledge, and change attitudes, intentions, and behavior. Well-documented health-related communication methods were employed to determine their effectiveness in a transportation domain. Health countermeasure designers use first-person perspective to improve narrative instruction outcomes, based on the Elaboration Likelihood Model (ELM; Petty & Cacioppo, 1986). Exploring narrative perspective-taking as a design tool requires the integration of multiple disciplines.

Our design case stems …

Data-Driven Framework For Understanding & Modeling Ride-Sourcing Transportation Systems, Bishoy Kelleny

Civil & Environmental Engineering Theses & Dissertations

Ride-sourcing transportation services offered by transportation network companies (TNCs) like Uber and Lyft are disrupting the transportation landscape. The growing demand on these services, along with their potential short and long-term impacts on the environment, society, and infrastructure emphasize the need to further understand the ride-sourcing system. There were no sufficient data to fully understand the system and integrate it within regional multimodal transportation frameworks. This can be attributed to commercial and competition reasons, given the technology-enabled and innovative nature of the system. Recently, in 2019, the City of Chicago the released an extensive and complete ride-sourcing trip-level data for …

A Field Study In An Urban Area: Examining Distracted Pedestrian Unsafe Crossing Behavior, Emma Hood

Undergraduate Research Symposium

A field study examining distracted pedestrian unsafe crossing behavior in an urban area. The study is among the first to contribute knowledge to environmental alterations impact on crossing behavior. Portions of the abstract are a part of a manuscript that will be submitted to Psi Chi Journal of Psychological Research for undergraduate students.

Development Of Guidelines For Collecting Transit Ridership Data, Hong Yang, Kun Xie, Sherif Ishak, Qingyu Ma, Yang Liu

Computational Modeling & Simulation Engineering Faculty Publications

Transit ridership is a critical determinant for many transit applications such as operation optimizations and project prioritization under performance-based funding mechanisms. As a result, the quality of ridership data is of utmost importance to both transit administrative agencies and transit operators. Many transit operators in Virginia report their ridership data to the Department of Rail and Public Transportation (DRPT) and the National Transit Database (NTD). However, with no specific guidelines available to transit agencies in Virginia for collecting ridership data, the heterogeneous mixture of diverse data collection methods and technologies has often raised concerns about the consistency and quality of …