814 citations · 913 across the 23 of their papers we have counts for
8 papers · 1 filter
Strategizing Equitable Transit Evacuations: A Data-Driven Reinforcement Learning Approach
Fang Tang, Han Wang, Maria Laura Delle Monache
As natural disasters become increasingly frequent, the need for efficient and equitable evacuation planning has become more critical. This paper proposes a data-driven, reinforceme…
Highway Congestion Reduction through Reinforcement Learning Based Eulerian Headway Control
Yaron Veksler, Sharon Hornstein, Han Wang +2
Connected automated vehicles (CAVs) equipped with adaptive cruise control (ACC) create new opportunities for highway congestion mitigation. Traditional practice relies on Eulerian…
On the Analytical Properties of a Nonlinear Microscopic Dynamical Model for Connected and Automated Vehicles
H. Nick Zinat Matin, Y. Yeo, X. Gong +1
In this paper, we propose an integrated dynamical model of Connected and Automated Vehicles (CAVs) which incorporates CAV technologies and a microscopic car-following model to impr…
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…
Mesoscale Traffic Forecasting for Real-Time Bottleneck and Shockwave Prediction
Raphael Chekroun, Han Wang, Jonathan Lee +4
Accurate real-time traffic state forecasting plays a pivotal role in traffic control research. In particular, the CIRCLES consortium project necessitates predictive techniques to m…
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,…
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…
Reinforcement Learning Based Oscillation Dampening: Scaling up Single-Agent RL algorithms to a 100 AV highway field operational test
Kathy Jang, Nathan Lichtlé, Eugene Vinitsky +10
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 smoot…