Lily Elefteriadou
Professor | University of Florida
Gainesville, FL, UNITED STATES
Lily Elefteriadou is an expert on traffic flow theory and traffic operations.
Biography
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 ResearchMary Jeghers, et. al
2023-04-27
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...
Platooning Trajectory Optimization for Connected Automated Vehicles in Coordinated Arterials
National Academies of SciencesAgustin Guerra, Lily Elefteriadou
2022-08-12
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.
Long-Range Multi-Object Tracking at Traffic Intersections on Low-Power Devices
Institute of Electrical and Electronics EngineersPatrick Emami, et. al
2021-10-04
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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