8 citations · 24 across the 9 of their papers we have counts for
9 papers
Phase Re-service in Reinforcement Learning Traffic Signal Control
Zhiyao Zhang, George Gunter, Marcos Quinones-Grueiro +4
This article proposes a novel approach to traffic signal control that combines phase re-service with reinforcement learning (RL). The RL agent directly determines the duration of t…
Field Deployment of Multi-Agent Reinforcement Learning Based Variable Speed Limit Controllers
Yuhang Zhang, Zhiyao Zhang, Marcos Quiñones-Grueiro +4
This article presents the first field deployment of a multi-agent reinforcement-learning (MARL) based variable speed limit (VSL) control system on the I-24 freeway near Nashville,…
FT-AED: Benchmark Dataset for Early Freeway Traffic Anomalous Event Detection
Austin Coursey, Junyi Ji, Marcos Quinones-Grueiro +5
Early and accurate detection of anomalous events on the freeway, such as accidents, can improve emergency response and clearance. However, existing delays and errors in event ident…
Designing, simulating, and performing the 100-AV field test for the CIRCLES consortium: Methodology and Implementation of the Largest mobile traffic control experiment to date
Mostafa Ameli, Sean Mcquade, Jonathan W. Lee +20
Previous controlled experiments on single-lane ring roads have shown that a single partially autonomous vehicle (AV) can effectively mitigate traffic waves. This naturally prompts…
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,…
Virtual trajectories for I-24 MOTION: data and tools
Junyi Ji, Yanbing Wang, Derek Gloudemans +3
This article introduces a new virtual trajectory dataset derived from the I-24 MOTION INCEPTION v1.0.0 dataset to address challenges in analyzing large but noisy trajectory dataset…