collaborators

5 papers

eess.SY2024

Enforcing Cooperative Safety for Reinforcement Learning-based Mixed-Autonomy Platoon Control

Jingyuan Zhou, Longhao Yan, Jinhao Liang +1

It is recognized that the control of mixed-autonomy platoons comprising connected and automated vehicles (CAVs) and human-driven vehicles (HDVs) can enhance traffic flow. Among exi…

cs.RO2024

Interaction-Aware Trajectory Prediction for Safe Motion Planning in Autonomous Driving: A Transformer-Transfer Learning Approach

Jinhao Liang, Chaopeng Tan, Longhao Yan +3

A critical aspect of safe and efficient motion planning for autonomous vehicles (AVs) is to handle the complex and uncertain behavior of surrounding human-driven vehicles (HDVs). D…

eess.SY2024

Bi-Level Control of Weaving Sections in Mixed Traffic Environments with Connected and Automated Vehicles

Longhao Yan, Jinhao Liang, Kaidi Yang

Connected and automated vehicles (CAVs) can be beneficial for improving the operation of highway bottlenecks such as weaving sections. This paper proposes a bi-level control approa…

eess.SY2024

Enhancing System-Level Safety in Mixed-Autonomy Platoon via Safe Reinforcement Learning

Jingyuan Zhou, Longhao Yan, Kaidi Yang

Connected and automated vehicles (CAVs) have recently gained prominence in traffic research due to advances in communication technology and autonomous driving. Various longitudinal…

cs.RO2024

Control-Aware Trajectory Predictions for Communication-Efficient Drone Swarm Coordination in Cluttered Environments

Longhao Yan, Jingyuan Zhou, Kaidi Yang

Swarms of Unmanned Aerial Vehicles (UAV) have demonstrated enormous potential in many industrial and commercial applications. However, before deploying UAVs in the real world, it i…