activity
20172025
most citedUnified Automatic Control of Vehicular Systems with Reinforcement Learning

58 citations · 68 across the 10 of their papers we have counts for

collaborators

12 papers

cs.SI2025

S2Vec: Self-Supervised Geospatial Embeddings for the Built Environment

Shushman Choudhury, Elad Aharoni, Chandrakumari Suvarna +4

Scalable general-purpose representations of the built environment are crucial for geospatial artificial intelligence applications. This paper introduces S2Vec, a novel self-supervi…

cs.LG2024

Scalable Learning of Segment-Level Traffic Congestion Functions

Shushman Choudhury, Abdul Rahman Kreidieh, Iveel Tsogsuren +3

We propose and study a data-driven framework for identifying traffic congestion functions (numerical relationships between observations of traffic variables) at global scale and se…

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…

cs.RO2022

Learning energy-efficient driving behaviors by imitating experts

Abdul Rahman Kreidieh, Zhe Fu, Alexandre M. Bayen

The rise of vehicle automation has generated significant interest in the potential role of future automated vehicles (AVs). In particular, in highly dense traffic settings, AVs are…