2 citations · 2 across the 2 of their papers we have counts for
4 papers · 1 filter
CARL: Congestion-Aware Reinforcement Learning for Imitation-based Perturbations in Mixed Traffic Control
Bibek Poudel, Weizi Li, Shuai Li
Human-driven vehicles (HVs) exhibit complex and diverse behaviors. Accurately modeling such behavior is crucial for validating Robot Vehicles (RVs) in simulation and realizing the…
Learning to Change: Choreographing Mixed Traffic Through Lateral Control and Hierarchical Reinforcement Learning
Dawei Wang, Weizi Li, Lei Zhu +1
The management of mixed traffic that consists of robot vehicles (RVs) and human-driven vehicles (HVs) at complex intersections presents a multifaceted challenge. Traditional signal…
Large-scale Mixed Traffic Control Using Dynamic Vehicle Routing and Privacy-Preserving Crowdsourcing
Dawei Wang, Weizi Li, Jia Pan
Controlling and coordinating urban traffic flow through robot vehicles is emerging as a novel transportation paradigm for the future. While this approach garners growing attention…
EnduRL: Enhancing Safety, Stability, and Efficiency of Mixed Traffic Under Real-World Perturbations Via Reinforcement Learning
Bibek Poudel, Weizi Li, Kevin Heaslip
Human-driven vehicles (HVs) amplify naturally occurring perturbations in traffic, leading to congestion--a major contributor to increased fuel consumption, higher collision risks,…