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20172025
most citedFlow: A Modular Learning Framework for Mixed Autonomy Traffic

193 citations · 261 across the 11 of their papers we have counts for

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5 papers · 1 filter

eess.SY2024★ 7 cited

Traffic Control via Connected and Automated Vehicles: An Open-Road Field Experiment with 100 CAVs

Jonathan W. Lee, Han Wang, Kathy Jang +61

The CIRCLES project aims to reduce instabilities in traffic flow, which are naturally occurring phenomena due to human driving behavior. These "phantom jams" or "stop-and-go waves,…

eess.SY2024

Hierarchical Speed Planner for Automated Vehicles: A Framework for Lagrangian Variable Speed Limit in Mixed Autonomy Traffic

Han Wang, Zhe Fu, Jonathan Lee +14

This paper introduces a novel control framework for Lagrangian variable speed limits in hybrid traffic flow environments utilizing automated vehicles (AVs). The framework was valid…

eess.SY2023

Cooperative Driving for Speed Harmonization in Mixed-Traffic Environments

Zhe Fu, Abdul Rahman Kreidieh, Han Wang +3

Autonomous driving systems present promising methods for congestion mitigation in mixed autonomy traffic control settings. In particular, when coupled with even modest traffic stat…

eess.SY2022

Non-local Evasive Overtaking of Downstream Incidents in Distributed Behavior Planning of Connected Vehicles

Abdul Rahman Kreidieh, Yashar Farid, Kentaro Oguchi

The prevalence of high-speed vehicle-to-everything (V2X) communication will likely significantly influence the future of vehicle autonomy. In several autonomous driving application…

eess.SY2021

Integrated Framework of Vehicle Dynamics, Instabilities, Energy Models, and Sparse Flow Smoothing Controllers

Jonathan W. Lee, George Gunter, Rabie Ramadan +25

This work presents an integrated framework of: vehicle dynamics models, with a particular attention to instabilities and traffic waves; vehicle energy models, with particular atten…