Event Type: Seminar

Event Overview

This talk covers the theory, empirical validation, and control of the capacity drop phenomenon at sag and tunnel bottlenecks. We first overview a continuum theory of capacity drop at these bottlenecks, which clearly explains the connection between the bottleneck effect and the resulting capacity drop. The theory is then validated both qualitatively and quantitatively using empirical data from multiple sites in Japan. New control strategies for mitigating capacity drop are also introduced and compared. Finally, based on these insights, we discuss case studies on evaluating an existing control method and on designing a new control method grounded in the theoretical framework.

Dr. Kentaro Wada is an Associate Professor at the University of Tsukuba, Japan. He received his Ph.D. in Information Sciences from Tohoku University in 2013. His research covers a wide range of topics in transportation systems, including traffic flow theory with emphasis on capacity drop phenomena, dynamic equilibrium models of departure time and route choice, market-based demand management such as tradable network permits, and traffic signal optimization. Dr. Wada was a Visiting Scholar at UCI in 2017–2018.

Abstract

This research addresses the challenge of efficiently processing sensor data across vehicles, edge, and cloud platforms to support resource-intensive perception tasks in autonomous driving.

We investigate distributed processing of perception data from three perspectives to enhance perception accuracy, optimize network and computing resources, and meet real-time latency constraints: (1) offloading computationally intensive tasks to edge or cloud platforms for greater processing capacity and reduced on-board load, (2) evaluating the impact of compression techniques such as H.265 and JPEG on perception quality and transmission latency, and (3) exploring feature-vector transmission as an alternative to raw or compressed data to reduce bandwidth usage while maintaining perception accuracy and minimizing end-to-end delay.

To evaluate performance under realistic conditions, the study utilized both simulation-based assessments and real-world experiments. Using Vehicle-to- Everything (V2X) communication technologies, we analyzed compression and feature-sharing strategies for seamless data exchange between vehicles and infrastructure. Our findings demonstrated that the proposed cooperative and distributed perception strategies significantly improved detection accuracy and reduced processing delays compared to standalone on-board systems.

Raphaël Frank is a Professor / Senior Research Scientist and Entrepreneur at the Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg. He is the Head of the UBIX Research Group, which conducts research on distributed artificial intelligence. Since 2023 he is a member of the University of Luxembourg Council and adjunct Professor at HEC Liège Luxembourg. Since 2024 he is the director of the IPBG ATLAS Industrial PhD Program.

Event Overview

Lan Zhou is a 20+-year veteran of the California Department of Transportation (Caltrans). She currently serves as the Caltrans District 12 Director, where she previously served as Deputy Director of Planning and Local Assistance for eleven years, and before that as the Corridor System Management Program Manager and Regional Planning and Local Development Review Branch Chief. She began her Caltrans career in District 4 (Bay Area) as a lead engineer in Maintenance and Toll Bridge Engineering. Zhou has a long history in strategic planning, organizational excellence, and partnership building, and has a wide breadth of experience including working for universities, a Metropolitan Planning Organization (MPO), local government and multiple State Departments of Transportation. As the District 12 Director, Zhou leads
nearly 1,000 employees and serves 3.2 million residents.

Dina El-Tawansy has 23 years of service with Caltrans and her leadership experience spans three Districts and multiple Divisions. She is currently the District Director, Caltrans, District 4, Bay Area. Prior, she served as Chief Deputy District Director for Caltrans District 4. While much of her career has been in District 4 and District 7, Dina also served in District 12, Orange County, as the Deputy District Director of Operations and Maintenance. In her current capacity, Ms. El-Tawansy manages a $2 Billion budget of inhouse and oversight investments and leading nearly 3,500 staff. As Director of District 4, she implements the Department’s new Mission, Vision and Goals, builds and strengthens partnerships, and continues the work towards multimodal, safe and reliable transportation solutions that serve all people of the Bay Area. Dina possesses a B.S. degree in Civil Engineering from Cal Poly Pomona and an M.S. degree from Long Beach State University in Construction Management. She is a licensed Professional Engineer (PE) and Project Management Professional (PMP)

Event Overview

Public agencies are taking actions to promote multimodal transportation, while the emergence of multimodality raises challenges. With diverse service designs and
operational strategies, modeling, evaluating, and managing such systems from a holistic
perspective becomes more difficult.

Regulators require modeling tools capable of handling multiple stakeholders and various operational strategies. To incorporate different types of operational strategies, we extend the traditional
assignment game into a nonlinear mixed-integer programming model that integrates
both fixed-route and on-demand services.

The model captures decision-making from
both travelers and operators to form a market equilibrium and we propose a stochastic assignment game and define its core. We further adapted this approach into a stochastic Stackelberg game to model urban mobility markets, where the regulator is the leader and stochastic coalitions of travelers and operators form as the followers.

SPEAKER

Bingqing Liu received her Ph.D. in Transportation Systems at Tandon School of Engineering, New York University. She is currently a postdoctoral scholar at UCLA, affiliated with the Center of Excellence on New Mobility and Automated Vehicles. Her research focuses on network modeling of multimodal transportation systems, with game theory, operations research, and simulation approaches.

Event Overview

Traffic congestion is a pervasive worldwide problem. In this webinar. we explain how to harness existing technologies together with new methods in time-and-location markets to eradicate traffic congestion along with its attendant social harms. Our market design for road use builds on congestion pricing and models of efficient pricing in the electricity sector. The market maximizes the value of a transport network through efficient scheduling, routing and pricing of road use. Privacy and equity concerns are addressed. Transparent price information provides essential information for efficient long-term investment in transport.

Dr. Rick Geddes is currently a Visiting Fellow with the Hoover Institution at Stanford University, on a one-year sabbatical from his permanent position as professor in Cornell’s Jeb E. Brooks School of Public Policy and Professor of Economics at Cornell. He is Founding Director of the Cornell Program in Infrastructure Policy, or CPIP; is a member of the graduate fields of Systems Engineering, Regional Science, and Economics; and is a Non-Resident Senior Scholar at the American Enterprise Institute in Washington, DC.

Dr. Geddes research centers on funding, financing and delivery of major infrastructure projects, road pricing, and utility regulation. His publications have appeared in numerous academic journals and he authored the 2011 AEI book entitled, The Road to Renewal: Private Investment in U.S. Transportation Infrastructure. Dr. Geddes holds MA and Ph.D. degrees in economics from the University of Chicago, and a BS in economics and finance from Towson State University.

Event Overview

The Tennessee Department of Transportation’s I-24 Mobility Technology Interstate Observation Network (MOTION) is a four-mile section of I-24 in the Nashville-Davidson County Metropolitan area with 294 ultra-high definition cameras. Those images are converted into a digital model of how every vehicle behaves with unparalleled detail. This is all done anonymously using trajectory processing algorithms developed by Vanderbilt University. By unlocking a new understanding of how these vehicles influence traffic, vehicle and infrastructure design can be optimized to reduce traffic concerns in the future to improve safety, air quality, and fuel efficiency. For more details, data, and tools, visit i24motion.org.

SPEAKER
Junyi Ji is a PhD Candidate at Vanderbilt University working with Prof. Daniel B. Work. He is mainly focusing on the TDOT I-24 MOTION, a real-world freeway testbed generating billion-level vehicle trajectory data. His primary research focuses on the multi-scale dynamics of traffic waves. His research vision is to integrate computational methods and cyber-physical systems (CPS) for sustainable transportation solutions aligned with the UN Sustainable Development Goals (SDGs). He is a strong advocate for open science. He is the initiator of the workshop on vehicle trajectory data camp and actively volunteers with organizations such as RERITE, Citipedia, and MoveVU.