10 citations · 52 across the 40 of their papers we have counts for
8 papers · 1 filter
Continual Interactive Behavior Learning With Traffic Divergence Measurement: A Dynamic Gradient Scenario Memory Approach
Yunlong Lin, Zirui Li, Cheng Gong +3
Developing autonomous vehicles (AVs) helps improve the road safety and traffic efficiency of intelligent transportation systems (ITS). Accurately predicting the trajectories of tra…
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…
Adaptive Decision Making at the Intersection for Autonomous Vehicles Based on Skill Discovery
Xianqi He, Lin Yang, Chao Lu +2
In urban environments, the complex and uncertain intersection scenarios are challenging for autonomous driving. To ensure safety, it is crucial to develop an adaptive decision maki…
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…