Equity and Understanding User Needs

How Effective Are Attitudinal Variables at Improving Travel Behavior Models? Evaluation Using an Overlapping Sample From an Attitude-Rich Survey and the 2017 National Household Travel Survey

A line of research has recently been launched on attitude imputation using machine learning (ML) functions trained on variables common to two survey datasets (Mokhtarian, 2024). It was discovered that using a handful of attitudinal marker variables (i.e., the one or two attitudinal items most strongly associated with each attitude) as common variables for imputation […]

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Improving Mobility Options through Transit Signal Priority (TSP)

TSP seeks to optimize the interaction between busses and the infrastructure, creating a minimum resistance path for transit buses through signalized intersections. TSP may improve travel time reliability (TTR), schedule adherence, and ultimately the quality of service and ridership for transit systems. Bhat and Sardesai explicitly includes of TTR in mode choice, demonstrating the significance

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How Complete are Your City’s Streets? Evaluating the Completeness of Urban Streets Using Big Data and Computer Vision

The main objectives of this project are: (1) development and validation of detection methods on the presence and width of individual elements of complete streets at street level, (2) development of a numeric index and typology to rate the completeness of streets, (3) curation of a publicly accessible database of various elements of complete street

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Exploring Top-Down Visual Attention for Transportation Behavior Analysis

This project stands at the intersection of cognitive psychology, AI and computer vision, and transportation safety and efficiency. By focusing on the nuanced ways in which humans allocate their visual attention, and how this can inform the development of artificial intelligence (AI) and machine learning (ML) to aid in self-driving cars, transportation safety automation, and

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Investigation of Emerging Sensing and AI/ML Technologies to Enhance the Safety of Vulnerable Roadway Users at Signalized Intersection

Accurately identifying and analyzing vulnerable roadway users (VRUs) such as pedestrians, bicyclists, and other non-vehicle occupants, are a crucial yet difficult undertaking. VRUs’ behavior is influenced by localized factors such as land use, and their movements are not confined to predefined paths. This study will investigate the use of emerging technologies such as LiDAR, network

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Addressing Mobility-Related Challenges for AAPI Older Adults

This project will use qualitative and quantitative research methods to better understand mobility-related challenges for Asian Americans and Pacific Islanders (AAPI) older adults in order to provide government agencies and organizations such as National Asian Pacific Center on Aging (NAPCA) with recommendations for policy and program changes to pursue. Older adults are typically defined as

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Vehicle Edge Computing for Travel Behavior and Demand in Future Intelligent Transportation Systems (ITS)

Meeting the diverse needs of stakeholders such as passengers, drivers, and service providers is imperative. Modern travelers seek real-time updates and personalized journey experiences. Drivers need consolidated data for safety and punctuality (Chen et al., 2021), while service providers rely on data analytics to optimize resources and enhance reliability (Wang et al., 2020). Traditional centralized

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Smart Transportation Digital Infrastructure: Advancing System Equity, Resilience, and Safety through Multi-Source Open-Standard Data Integration

The recently emerging trend of sensor technology, ubiquitous and high-performance computing is creating a revolutionary paradigm shift in the coming years. Through data and feedback, both simulated and real, a Digital Infrastructure (DI) for smart cities has received increasing attention. The pandemic, in many cases, is accelerating this need, as there are critical needs for

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From Cross-Sectional to Longitudinal: The Impact of Sampling Strategies on Measuring Mobility Choices

The transportation profession has long relied on surveys as a main source of data. These surveys are used across a broad range of applications, including but not limited to, travel demand forecasting, travel behavior analysis, policy evaluation, environmental impact assessment, equity analysis, and economic evaluation. Despite the increasing accessibility of passive data collection methods, such

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