10 citations · 26 across the 13 of their papers we have counts for
14 papers
Learning from Mistakes: Rollout-Retrieval Lifelong Policy Learning for Autonomous Driving
Cheng Gong, Haoyang Wang, Chao Lu +2
Autonomous driving policies should be able to improve continually as deployment exposes them to increasingly diverse and long-tail traffic situations. However, most learning-based…
Complementary Learning System Empowers Online Continual Learning of Vehicle Motion Forecasting in Smart Cities
Zirui Li, Yunlong Lin, Guodong Du +5
Artificial intelligence underpins most smart city services, yet deep neural network (DNN) that forecasts vehicle motion still struggle with catastrophic forgetting, the loss of ear…
H2C: Hippocampal Circuit-inspired Continual Learning for Lifelong Trajectory Prediction in Autonomous Driving
Yunlong Lin, Zirui Li, Guodong Du +5
Deep learning (DL) has shown state-of-the-art performance in trajectory prediction, which is critical to safe navigation in autonomous driving (AD). However, most DL-based methods…
Motion planning for off-road autonomous driving based on human-like cognition and weight adaptation
Yuchun Wang, Cheng Gong, Jianwei Gong +1
Driving in an off-road environment is challenging for autonomous vehicles due to the complex and varied terrain. To ensure stable and efficient travel, the vehicle requires conside…
Beyond Imitation: A Life-long Policy Learning Framework for Path Tracking Control of Autonomous Driving
C. Gong, C. Lu, Z. Li +3
Model-free learning-based control methods have recently shown significant advantages over traditional control methods in avoiding complex vehicle characteristic estimation and para…
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…
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…
Driver-Specific Risk Recognition in Interactive Driving Scenarios using Graph Representation
Jinghang Li, Chao Lu, Penghui Li +3
This paper presents a driver-specific risk recognition framework for autonomous vehicles that can extract inter-vehicle interactions. This extraction is carried out for urban drivi…
Prediction of Pedestrian Spatiotemporal Risk Levels for Intelligent Vehicles: A Data-driven Approach
Zheyu Zhang, Boyang Wang, Chao Lu +3
In recent years, road safety has attracted significant attention from researchers and practitioners in the intelligent transport systems domain. As one of the most common and vulne…
Life-Long Multi-Task Learning of Adaptive Path Tracking Policy for Autonomous Vehicle
Cheng Gong, Jianwei Gong, Chao Lu +2
This paper proposes a life-long adaptive path tracking policy learning method for autonomous vehicles that can self-evolve and self-adapt with multi-task knowledge. Firstly, the pr…
Orientation-Aware Planning for Parallel Task Execution of Omni-Directional Mobile Robot
Cheng Gong, Zirui Li, Xingyu Zhou +3
Omni-directional mobile robot (OMR) systems have been very popular in academia and industry for their superb maneuverability and flexibility. Yet their potential has not been fully…
Autonomous Driving Strategies at Intersections: Scenarios, State-of-the-Art, and Future Outlooks
Lianzhen Wei, Zirui Li, Jianwei Gong +2
Due to the complex and dynamic character of intersection scenarios, the autonomous driving strategy at intersections has been a difficult problem and a hot point in the research of…
High-precision target positioning system for unmanned vehicles based on binocular vision
Xianqi He, Zirui Li, Xufeng Yin +2
Unmanned vehicles often need to locate targets with high precision during work. In the unmanned material handling workshop, the unmanned vehicle needs to perform high-precision pos…
Driver Behavior Modelling at the Urban Intersection via Canonical Correlation Analysis
Zirui Li, Chao Lu, Cheng Gong +2
The urban intersection is a typically dynamic and complex scenario for intelligent vehicles, which exists a variety of driving behaviors and traffic participants. Accurately modell…