Tuesday, May 27, 2025

1:00pm - 5:00pm

Workshop - Driving Innovation: Practical AI Tools for Transportation Challenges

The advent of AI opens opportunities as well as presents challenges to the transportation community to serve our stakeholders better. The objectives of this workshop are to introduce participants to tools that encourage AI adoption in transportation by lowering the technical barriers to entry while providing a comprehensive understanding of how AI code generators work, their capabilities, potential use cases, and limitations.

1:00pm - 5:00pm

Workshop - Visual Storytelling: Data to Insights

Dive into the art of storytelling with data in this immersive four-hour workshop. This session will cover the latest techniques and tools for creating impactful visualizations, from foundational principles to advanced applications. You’ll explore AI-powered tools to simplify complex data, visualize it effectively, and build compelling narratives. This workshop includes hands-on activities, interactive discussions, and collaborative exercises to help you refine your skills and actively contribute to developing draft national guidance. Whether you’re new to data visualization or an experienced practitioner, you'll gain valuable insights to elevate your storytelling and enhance data-driven decision-making in your organization.

1:00pm - 5:00pm

Tour: Washington State Ferry

Take a guided tour of the new Coleman Dock facility, followed by a round-trip ferry ride that includes a tour of the vessel.

1:00pm - 5:00pm

Tour: Microsoft Campus

Explore Microsoft’s Redmond campus, including visits to labs focused on cybersecurity, cloud computing, quantum computing, and cutting-edge infrastructure projects.

1:00pm - 5:00pm

Tour: University of Washington STAR Lab

Visit UW’s Smart Transportation Applications and Research (STAR) Lab, where research on AI, ITS, big data, and more is conducted.

No additional cost for workshops or tours, but all have capacity limits.

Wednesday, May 28, 2025

7:00am - 5:00pm

Registration Open

7:00am - 8:30am

TRB Standing Committee on State & National Data (AED10) Meeting

7:30am - 8:30am

Breakfast (included in registration)

8:30am - 10:00am

Plenary Session

10:00am - 10:30am

Break

10:30am - 12:00pm

Session created by TRB Standing Committee on Visualization in Transportation (AED80)

Advancing Data and AI in Organizations from the CIO Perspective

Session created by TRB Standing Committee on Freight Data (AED70)

12:00pm - 1:00pm

Lunch (included in registration)

1:30pm - 3:00pm

Digital Twins

USDOT: Responsible Data for Responsible
AI Transportation Solutions

Moderator: Stuart Gluck, FRA

•   Towards a Standard for Identifying and Managing Bias in Artificial Intelligence: Reva Schwartz, NIST

•   Responsible Acquisition and Use of Data for Developing AI Tools for Transportation Applications: Chou-Lin Chen, NHTSA

•   Liquid Neural Networks: Reducing Data Needs for Self-Driving Cars: Daniela Rus, MIT

AI Data for Freight Logistics

Moderator: Sushant Sharma, TTI

•    Bo Wang, Amazon

•    Fatemeh Ranaiefar, Fehr & Peers

•    Kaveh Shabani, Cambridge Systematics

•    Jesse Newberry, HNTB

3:00pm - 3:30pm

Break

3:30pm - 5:00pm

Poster Lightning Session

Moderator: Mo Zhao, Virginia DOT

•   Advanced Demand Prediction for
Demand-Responsive Transit (DRT) Systems: Integrating Graph Convolutional Networks and Deep Learning Techniques, Diana Al-Nabulsi, Western Michigan University

•   Use of Machine Learning for Waterway Transportation Research at USACE, Magdalena Asborno, ARA

•   Testing Language Modeling Techniques for Travel Forecasting, Colby Brown, Manhan Group

•   Complete Streets AI Initiative: Phase I Lessons Learned, Jonah Chiarenza, USDOT Volpe

•   Supporting Truck Platooning Optimization
via AI: Ioannis Paraskevas Ioannou, Florida Atlantic University

•   Community-Based AI Solutions for Enhancing Vulnerable Road User Safety, Abolfazl Karimpour, SUNY Polytechnic

•   Analysis of Automated Driving System Disengagements, Mubassira Khan, USDOT

•   An Analytical Tool for Modeling Coordinated, Adaptive Ramp Metering (CARM) Strategies, Mingyang Li, WSP

•   From Raw Data to Realistic Trajectories: An AI-Powered Data Fusion Framework for Human Mobility Modeling, Haoxuan Ma, UCLA

•   Functional Data Analysis for Change Detection in Bicycling Patterns, Avipsa Roy, UC Irvine

•   Evaluating the Effectiveness of Large Language Models in Transportation Case Studies: A Comparative Analysis of Prompt Strategies and Model Selection, Chenyu Yuan, UC Irvine

Agency Experience

•   Harnessing Generative AI for Enhanced Community Engagement and Equity-Focused Survey Analysis: David Wasserman and Kelly Dunn, Alta Planning + Design

•   AI for Transportation: Challenges and Potential Solutions, Insights, and Lessons Learned: Haley Townsend, Noblis

•   Kicking the AI and ML Tires at Missouri DOT: Mark Egge, High Street Consulting

•   Leveraging Generative Scheduling to Deliver Transportation Agency Portfolios and Plans: Bryan Pounds, McKinsey & Company

Traffic Simulation 1

•   Congestion Prediction Using Weighted Samples, Connected Vehicle Data and Machine Learning: The Chesapeake Bay Bridge Queue Detection and Prediction Web Application: Michael Pack, UMD CATT Lab

•   Generative Artificial Intelligence (GenAI) Solution for Traffic Mobility Insights: Naveen Juwa, Deloitte

•   Leveraging New Data and AI for Freeway Operations: Junyi Ju, Vanderbilt University

•   Machine Learning for Traffic Forecasting: A Practical Approach Deployed in the Future Road Lab of the C-32 Motorway in Spain: Ferran Torrent-Fontbona, Aimsun

5:00pm - 7:00pm

Posters and Reception (included in registration)

Thursday, May 29, 2025

Registration Open

Breakfast (included in registration)

Plenary Session

Break

Computer Vision

•   Customized Computer Vision with Transfer-learning for TAMU Gameday Pedestrian and Vehicle Counting: Yalong Pi, Texas A&M

•   AI-Enhanced Traffic Monitoring: Real-Time Anomaly Detection and Predictive Analytics Using Computer Vision: Juliana Chengula, HNTB

Modeling

•   A Review of AI-DCM Models and Preliminary Findings on their Application to Destination Choice: Vince Bernardin, Caliper Corporation

•   An Application of Explainable Artificial Intelligence (XAI) to Trip and Tour Generation Modeling: Vince Bernardin, Caliper Corporation

Toward Sustainable Computing in Artificial Intelligence

Moderator: Hao Frank Yang, Johns Hopkins University

Lunch (included in registration)

Asset Management

Moderator: Ben McCulloch, TxDOT

•   Asset Management AI - From Concept to Mainstream: Jonathan Groeger, Transconomy

•   Integrating Big Data and Using Machine Learning Modeling for Predictive Asset Management: Craig Bettmann, HNTB

•   Democratizing Transportation Infrastructure Maintenance using Data and Machine Learning: The Swedish Experience: Kristin Eklöf, Salbo.ai

Surveys/Unstructured Data

Moderator: Krishnan Viswanathan, WRA LLP

•   Advancing Synthetic Mobility Data Generation for Transportation Practitioners: Brian He, University of Louisville

•   STEAM+ (AI Fusion of Transportation Data for Predictive Analytics): Aysha Alkhazraji, Abu Dhabi Mobility

•   CTPP Data Portal AI Assistant: Stacey Bricka, MacroSys

Break

Traffic Simulation 2

•   AADT Estimation on Non-Federal Aid System Roadways: Praveen Pasumarthy, Cambridge Systematics

•   Evaluating AI-Based Incident Detection Platforms: Lessons for Improved Decision-Making: Silvy Munira, UT Austin

•   Reinforcement Learning Based Adaptive Transit Signal Priority: Dickens Kwesiga, Georgia Tech

Safety

Moderator: Jennifer Steen, HDR

•   AI-Driven Road Winter Maintenance, Advantages and Challenges: Johan Casselgren, Lulea University of Technology

•   AI Framework for Integrated Real-Time Intersection Detection and Signal Optimization: Suyash Vishnoi, Georgia Tech

•   Enhancing Vulnerable Road User (VRU) Safety with Generative Artificial Intelligence (GenAI): A Proactive Approach: Indeer Preet Singh, Caltrans

Transportation Research and Applications in the Generative AI Era

Moderator: Hao Frank Yang, Johns Hopkins University