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Lily Elefteriadou - University of Florida. Gainesville, FL, US

Lily Elefteriadou

Professor | University of Florida

Gainesville, FL, UNITED STATES

Lily Elefteriadou is an expert on traffic flow theory and traffic operations.


Lily Elefteriadou is a nationally and internationally recognized expert on traffic operations, traffic flow theory and simulation, with research funding exceeding $25M in the past 10 years.

Areas of Expertise (7)

Highway Capacity Analysis

Connected Vehicles

Traffic Management

Traffic Flow Theory

Traffic Simulation

Autonomous Vehicles

Traffic Signal Control


Articles (3)

An Examination of Two Diverse Communities: Residents' Transportation Behaviors, Challenges, and Opportunities

OTJR: Occupational Therapy Journal of Research

Mary Jeghers, et. al


The Smart Cities Collaborative aims to mitigate transportation challenges and inequities with new approaches and technologies (e.g., ridesharing). Therefore, assessing community transportation needs is essential. The team explored the travel behaviors, challenges, and/or opportunities among low- and high-socioeconomic status (SES) communities. Using Community-Based Participatory Research principles, four focus groups were conducted to investigate residents' behaviors and experiences...

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Platooning Trajectory Optimization for Connected Automated Vehicles in Coordinated Arterials

National Academies of Sciences

Agustin Guerra, Lily Elefteriadou


This paper proposes heuristic methods to optimize the trajectories of connected automated vehicles (CAVs) along an arterial assuming fully automated traffic condition. CAV trajectories are adjusted to form platoons at the saturation headway, guaranteeing the arrival of vehicles at the downstream intersection during the green interval. On the arrival of CAVs, an algorithm enables a smooth transition to the system target speed.

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Long-Range Multi-Object Tracking at Traffic Intersections on Low-Power Devices

Institute of Electrical and Electronics Engineers

Patrick Emami, et. al


The next generation of intelligent traffic signal control systems needs multi-object tracking (MOT) algorithms that can track vehicles hundreds of meters away from traffic intersections. To facilitate the integration of long-range MOT into existing traffic infrastructure, the tracker must achieve a good balance of cost-effectiveness, accuracy, and efficiency.

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