Georgia Institute of Technology

Characterizing Operational Disruptions in Urban Freight Networks: Patterns, Propagation, and Recovery Behaviors in Atlanta

Urban freight systems are subject to recurring disruptions that can degrade travel time reliability and operational efficiency. Despite their cumulative effects on freight movement and supply chain performance, these disruptions remain relatively understudied at the network level, particularly when only publicly funded and openly accessible data are used. This project develops a data-driven analytical framework

Characterizing Operational Disruptions in Urban Freight Networks: Patterns, Propagation, and Recovery Behaviors in Atlanta Read More »

Generative AI-based Framework for Modeling Longitudinal Travel Behavior Adaptation Under Transportation Interventions

Transportation agencies deploy a wide range of interventions to influence travel behavior and manage demand. While a broad range of approaches have been used to model travel behavior dynamics, modeling how behavioral responses manifest, strengthen, or decay over repeated exposure to transportation interventions remains relatively underexplored. This project will address this gap by developing a

Generative AI-based Framework for Modeling Longitudinal Travel Behavior Adaptation Under Transportation Interventions Read More »

Investigating the Stability and Evolution of Transportation-related Attitudes: Evidence from Two Longitudinal Survey Samples

Despite extensive evidence linking attitudes to behavior in the academic literature, challenges in measuring and forecasting attitudes remain key barriers to incorporating travelers’ attitudes into practice-oriented regional travel demand models. Recent studies have focused primarily on addressing measurement challenges, exploring and validating several approaches including the marker variable approach, which involves including an abbreviated set

Investigating the Stability and Evolution of Transportation-related Attitudes: Evidence from Two Longitudinal Survey Samples Read More »

Towards Building-Level Modeling: Human-Driven Agentic Workflows for Multi-Source Data Synthesis

Travel demand modeling is limited by the aggregation problem: data are often synthesized at census-tract or traffic-zone scales that obscure building-level mobility patterns. This project develops a human-directed agentic workflow in which a transportation planner orchestrates specialized artificial intelligence agents that discover, evaluate, and integrate open geospatial data from sources such as OpenStreetMap, building footprint

Towards Building-Level Modeling: Human-Driven Agentic Workflows for Multi-Source Data Synthesis Read More »

The Infrastructure-Perception Gap: Examining the Role of Transportation Infrastructure in Mediating Safety Perceptions for Active Travel

While extensive research demonstrates that perceived safety influences active travel behavior, the relationship between safety perceptions and transportation infrastructure characteristics remains inadequately understood. Traditional safety studies rely primarily on crash data, which often fails to align with how travelers perceive safe environments. This research addresses a critical gap by investigating how transportation infrastructure mediates safety

The Infrastructure-Perception Gap: Examining the Role of Transportation Infrastructure in Mediating Safety Perceptions for Active Travel Read More »

Fostering Multimodal Travel Options through Behavioral Interventions and Emerging Mobility Solutions

This project focuses on the practical implementation and validation of a systematic framework to progress towards transportation system goals of mobility, accessibility, and active lifestyle by leveraging the Peachtree Corners (PTC), GA, community as a living lab. The framework integrates behavioral interventions and emerging mobility solutions to address challenges related to low adoption of multimodal

Fostering Multimodal Travel Options through Behavioral Interventions and Emerging Mobility Solutions Read More »

From Perception to Policy: Measuring Road Driver Behavior and Public Support for Autonomous Truck Regulation

This project will investigate how human drivers respond when sharing the road with autonomous trucks, generating behavioral evidence to guide public policy, risk communication, and regulatory design for the safe and economically beneficial deployment of freight automation. Truck automation is projected to deliver major efficiency and safety gains to the United States economy by addressing

From Perception to Policy: Measuring Road Driver Behavior and Public Support for Autonomous Truck Regulation Read More »

Enhancing the Use of Attitudinal Marker Variables in Travel Behavior Models: Evaluation of Latent Class Modeling Approaches Using a Nationwide Travel Survey

Recent studies have shown that an abbreviated set of attitudinal marker variables (MVs) can serve as proxies for attitudinal factor scores from the full set of attitudinal variables, either directly or through machine learning-based imputation. Compared to models without attitudes, these MVs enhance model fit, identify additional significant explanatory variables, and improve prediction of less-often

Enhancing the Use of Attitudinal Marker Variables in Travel Behavior Models: Evaluation of Latent Class Modeling Approaches Using a Nationwide Travel Survey Read More »

Neutralizing Onerous Heat Effects on Active Transportation (NO-HEAT) in Atlanta

This project advances research at the intersection of heat resilience and multimodal transportation by combining urban microclimate modeling and sensing tools with big data and travel behavioral frameworks. We aim to explore how, and to what extent, people modify their activity-mobility patterns during periods of extreme heat in Atlanta, GA. We will extend recently developed

Neutralizing Onerous Heat Effects on Active Transportation (NO-HEAT) in Atlanta Read More »

Empirical Investigation of Post-Disaster Travel Behavior to Points of Distribution of Relief Supplies

The world has seen a surge in extreme weather events and increased challenges of disaster response. One overlooked factor complicating the distribution of relief supplies is the immediate decisions survivors make when seeking aid, which impacts the realized demand at various points of distribution (PODs) of relief supplies. This project aims to understand these critical

Empirical Investigation of Post-Disaster Travel Behavior to Points of Distribution of Relief Supplies Read More »

Scroll to Top