10 citations · 34 across the 16 of their papers we have counts for
18 papers
Leveraging Multi-stream Information Fusion for Trajectory Prediction in Low-illumination Scenarios: A Multi-channel Graph Convolutional Approach
Hailong Gong, Zirui Li, Chao Lu +2
Trajectory prediction is a fundamental problem and challenge for autonomous vehicles. Early works mainly focused on designing complicated architectures for deep-learning-based pred…
Graph Reinforcement Learning Application to Co-operative Decision-Making in Mixed Autonomy Traffic: Framework, Survey, and Challenges
Qi Liu, Xueyuan Li, Zirui Li +5
Proper functioning of connected and automated vehicles (CAVs) is crucial for the safety and efficiency of future intelligent transport systems. Meanwhile, transitioning to fully au…
Prediction-Based Reachability Analysis for Collision Risk Assessment on Highways
Xinwei Wang, Zirui Li, Javier Alonso-Mora +1
Real-time safety systems are crucial components of intelligent vehicles. This paper introduces a prediction-based collision risk assessment approach on highways. Given a point mass…
A Comparative Study of Deep Reinforcement Learning-based Transferable Energy Management Strategies for Hybrid Electric Vehicles
Jingyi Xu, Zirui Li, Li Gao +3
The deep reinforcement learning-based energy management strategies (EMS) have become a promising solution for hybrid electric vehicles (HEVs). When driving cycles are changed, the…
An Ensemble Learning Framework for Vehicle Trajectory Prediction in Interactive Scenarios
Zirui Li, Yunlong Lin, Cheng Gong +4
Precisely modeling interactions and accurately predicting trajectories of surrounding vehicles are essential to the decision-making and path-planning of intelligent vehicles. This…
Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Mixed Traffic Environments
Qi Liu, Zirui Li, Xueyuan Li +2
An efficient and reliable multi-agent decision-making system is highly demanded for the safe and efficient operation of connected autonomous vehicles in intelligent transportation…