most citedA DRL-based Multiagent Cooperative Control Framework for CAV Networks: a Graphic Convolution Q Network

39 citations · 117 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2021★ 1 cited

Scalable Traffic Signal Controls using Fog-Cloud Based Multiagent Reinforcement Learning

Paul, Ha, Sikai Chen +2

Optimizing traffic signal control (TSC) at intersections continues to pose a challenging problem, particularly for large-scale traffic networks. It has been shown in past research…

eess.SY2020★ 10 cited

Using Empirical Trajectory Data to Design Connected Autonomous Vehicle Controllers for Traffic Stabilization

Yujie Li, Sikai Chen, Runjia Du +3

Emerging transportation technologies offer unprecedented opportunities to improve the efficiency of the transportation system from the perspectives of energy consumption, congestio…

eess.SY2020★ 24 cited

A Cooperative Control Framework for CAV Lane Change in a Mixed Traffic Environment

Runjia Du, Sikai Chen, Yujie Li +3

In preparing for connected and autonomous vehicles (CAVs), a worrisome aspect is the transition era which will be characterized by mixed traffic (where CAVs and human-driven vehicl…

cs.AI2020★ 39 cited

A DRL-based Multiagent Cooperative Control Framework for CAV Networks: a Graphic Convolution Q Network

Jiqian Dong, Sikai Chen, Paul Young Joun Ha +2

Connected Autonomous Vehicle (CAV) Network can be defined as a collection of CAVs operating at different locations on a multilane corridor, which provides a platform to facilitate…

cs.LG2020★ 20 cited

Leveraging the Capabilities of Connected and Autonomous Vehicles and Multi-Agent Reinforcement Learning to Mitigate Highway Bottleneck Congestion

Paul Young Joun Ha, Sikai Chen, Jiqian Dong +3

Active Traffic Management strategies are often adopted in real-time to address such sudden flow breakdowns. When queuing is imminent, Speed Harmonization (SH), which adjusts speeds…

eess.SY2020★ 23 cited

Leveraging Vehicle Connectivity and Autonomy to Stabilize Flow in Mixed Traffic Conditions: Accounting for Human-driven Vehicle Driver Behavioral Heterogeneity and Perception-reaction Time Delay

Yujie Li, Sikai Chen, Paul Young Joun Ha +3

The erratic nature of human driving tends to trigger undesired waves that amplify as successive driver reactions propagate from the errant vehicle to vehicles upstream. Known as ph…