10 citations · 52 across the 40 of their papers we have counts for
21 papers · 1 filter
Beyond Planning: Differentiable Control-in-the-loop End-to-End Autonomous Driving
Zhidong Wang, Zirui Li, Zitong Shan +6
End-to-end autonomous driving has achieved remarkable progress by planning trajectories directly from raw sensor data. Yet the step from planning to control still relies on hand-tu…
Ego-Dynamics-Augmented World Model for Autonomous Driving with Zero-Shot Cross-Embodiment Adaptation
Zhidong Wang, Jingsong Liang, Zirui Li +3
End-to-end autonomous driving requires generalization ability across platforms with dissimilar physical characteristics. The chassis defines the physical embodiment of each platfor…
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…
Driver-WM: A Driver-Centric Traffic-Conditioned Latent World Model for In-Cabin Dynamics Rollout
Haozhuang Chi, Daosheng Qiu, Hao Su +4
Safe L2/L3 driving automation requires anticipating human-in-the-loop reactions during shared-control transitions. While most driving world models forecast the external environment…
IntentNav: Learning Spatial-Visual Object Navigation from Human Demonstrations
Yuxin Cai, Zongtai Li, Maonan Wang +9
Object navigation requires a robot to search for an unobserved target in an unknown environment by deciding where to explore next under partial observability. Effective search rese…
InterHub: A Naturalistic Trajectory Dataset with Dense Interaction for Autonomous Driving
Xiyan Jiang, Xiaocong Zhao, Yiru Liu +4
The driving interaction-a critical yet complex aspect of daily driving-lies at the core of autonomous driving research. However, real-world driving scenarios sparsely capture rich…
Updating Robot Safety Representations Online from Natural Language Feedback
Leonardo Santos, Zirui Li, Lasse Peters +2
Robots must operate safely when deployed in novel and human-centered environments, like homes. Current safe control approaches typically assume that the safety constraints are know…
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…
Reachability-Based Confidence-Aware Probabilistic Collision Detection in Highway Driving
Xinwei Wang, Zirui Li, Javier Alonso-Mora +1
Risk assessment is a crucial component of collision warning and avoidance systems in intelligent vehicles. To accurately detect potential vehicle collisions, reachability-based for…
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…
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…
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…
Sequential Point Cloud Prediction in Interactive Scenarios: A Survey
Haowen Wang, Zirui Li, Jianwei Gong
Point cloud has been widely used in the field of autonomous driving since it can provide a more comprehensive three-dimensional representation of the environment than 2D images. Po…
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…
Decision-Making Technology for Autonomous Vehicles Learning-Based Methods, Applications and Future Outlook
Qi Liu, Xueyuan Li, Shihua Yuan +1
Autonomous vehicles have a great potential in the application of both civil and military fields, and have become the focus of research with the rapid development of science and eco…
Autonomous Formula Racecar: Overall System Design and Experimental Validation
Hanqing Tian, Jun Ni, Zirui Li +1
This paper develops and summarizes the work of building the autonomous integrated system including perception system and vehicle dynamic controller for a formula student autonomous…
From perception to control: an autonomous driving system for a formula student driverless car
Tairan Chen, Zirui Li, Yiting He +3
This paper introduces the autonomous system of the "Smart Shark II" which won the Formula Student Autonomous China (FSAC) Competition in 2018. In this competition, an autonomous ra…