2 citations · 3 across the 5 of their papers we have counts for
5 papers
Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark
Chuyang Xiao, Dawei Wang, Xinzheng Tang +2
This paper presents a mixed traffic control policy designed to optimize traffic efficiency across diverse road topologies, addressing issues of congestion prevalent in urban enviro…
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…
LASIL: Learner-Aware Supervised Imitation Learning For Long-term Microscopic Traffic Simulation
Ke Guo, Zhenwei Miao, Wei Jing +4
Microscopic traffic simulation plays a crucial role in transportation engineering by providing insights into individual vehicle behavior and overall traffic flow. However, creating…
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…
Analyzing Emissions and Energy Efficiency at Unsignalized Real-world Intersections Under Mixed Traffic Control
Michael Villarreal, Dawei Wang, Jia Pan +1
Greenhouse gas emissions have dramatically risen since the early 1900s with U.S. transportation generating 28% of U.S. emissions. As such, there is interest in reducing transportat…