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Found 8 papers, 1 papers with code
Reinforcement Learning Based Oscillation Dampening: Scaling up Single-Agent RL algorithms to a 100 AV highway field operational test
In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles.
Traffic Control via Connected and Automated Vehicles: An Open-Road Field Experiment with 100 CAVs
The upper layer is called Speed Planner, and is a centralized optimal control algorithm.
Hierarchical Speed Planner for Automated Vehicles: A Framework for Lagrangian Variable Speed Limit in Mixed Autonomy Traffic
The Speed Planner comprises two modules: a TSE enhancement module and a target speed design module.
Mesoscale Traffic Forecasting for Real-Time Bottleneck and Shockwave Prediction
Accurate real-time traffic state forecasting plays a pivotal role in traffic control research.
Traffic smoothing using explicit local controllers
The dissipation of stop-and-go waves attracted recent attention as a traffic management problem, which can be efficiently addressed by automated driving.
So you think you can track?
This work introduces a multi-camera tracking dataset consisting of 234 hours of video data recorded concurrently from 234 overlapping HD cameras covering a 4. 2 mile stretch of 8-10 lane interstate highway near Nashville, TN.
Cooperative Driving for Speed Harmonization in Mixed-Traffic Environments
Autonomous driving systems present promising methods for congestion mitigation in mixed autonomy traffic control settings.
Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments
Traffic waves are phenomena that emerge when the vehicular density exceeds a critical threshold.
Systems and Control
