154 citations · 185 across the 15 of their papers we have counts for
15 papers
Token-Wise Latent Streaming from Slow Reasoners to Fast Planners for Dynamic Vision Language Navigation
Tianshuai Hu, Yangyi Zhong, Zeying Gong +7
Vision-Language Navigation in dynamic, human-centric environments exposes a fundamental tension: linguistic reasoning is slow and deliberative, whereas safe, socially compliant pla…
LVDrive: Latent Visual Representation Enhanced Vision-Language-Action Autonomous Driving Model
Xiaodong Mei, Diankun Zhang, Hongwei Xie +3
Vision-Language-Action (VLA) models have emerged as a promising framework for end-to-end autonomous driving. However, existing VLAs typically rely on sparse action supervision, whi…
NavThinker: Action-Conditioned World Models for Coupled Prediction and Planning in Social Navigation
Tianshuai Hu, Zeying Gong, Lingdong Kong +7
Social navigation requires robots to act safely in dynamic human environments. Effective behavior demands thinking ahead: reasoning about how the scene and pedestrians evolve under…
NetRoller: Interfacing General and Specialized Models for End-to-End Autonomous Driving
Ren Xin, Hongji Liu, Xiaodong Mei +4
Integrating General Models (GMs) such as Large Language Models (LLMs), with Specialized Models (SMs) in autonomous driving tasks presents a promising approach to mitigating challen…
HAMF: A Hybrid Attention-Mamba Framework for Joint Scene Context Understanding and Future Motion Representation Learning
Xiaodong Mei, Sheng Wang, Jie Cheng +2
Motion forecasting represents a critical challenge in autonomous driving systems, requiring accurate prediction of surrounding agents' future trajectories. While existing approache…
LHPF: Look back the History and Plan for the Future in Autonomous Driving
Sheng Wang, Yao Tian, Xiaodong Mei +5
Decision-making and planning in autonomous driving critically reflect the safety of the system, making effective planning imperative. Current imitation learning-based planning algo…
Enhancing Campus Mobility: Achievements and Challenges of Autonomous Shuttle "Snow Lion''
Yingbing Chen, Jie Cheng, Sheng Wang +15
The rapid evolution of autonomous vehicles (AVs) has significantly influenced global transportation systems. In this context, we present ``Snow Lion'', an autonomous shuttle meticu…
IR-STP: Enhancing Autonomous Driving with Interaction Reasoning in Spatio-Temporal Planning
Yingbing Chen, Jie Cheng, Lu Gan +4
Considerable research efforts have been devoted to the development of motion planning algorithms, which form a cornerstone of the autonomous driving system (ADS). Nonetheless, acqu…
Rethinking Imitation-based Planner for Autonomous Driving
Jie Cheng, Yingbing Chen, Xiaodong Mei +3
In recent years, imitation-based driving planners have reported considerable success. However, due to the absence of a standardized benchmark, the effectiveness of various designs…
Improving Autonomous Driving Safety with POP: A Framework for Accurate Partially Observed Trajectory Predictions
Sheng Wang, Yingbing Chen, Jie Cheng +4
Accurate trajectory prediction is crucial for safe and efficient autonomous driving, but handling partial observations presents significant challenges. To address this, we propose…
Forecast-MAE: Self-supervised Pre-training for Motion Forecasting with Masked Autoencoders
Jie Cheng, Xiaodong Mei, Ming Liu
This study explores the application of self-supervised learning (SSL) to the task of motion forecasting, an area that has not yet been extensively investigated despite the widespre…
Efficient Speed Planning for Autonomous Driving in Dynamic Environment with Interaction Point Model
Yingbing Chen, Ren Xin, Jie Cheng +4
Safely interacting with other traffic participants is one of the core requirements for autonomous driving, especially in intersections and occlusions. Most existing approaches are…
Autonomous Navigation through intersections with Graph ConvolutionalNetworks and Conditional Imitation Learning for Self-driving Cars
Xiaodong Mei, Yuxiang Sun, Yuying Chen +2
In autonomous driving, navigation through unsignaled intersections with many traffic participants moving around is a challenging task. To provide a solution to this problem, we pro…
HGCN-GJS: Hierarchical Graph Convolutional Network with Groupwise Joint Sampling for Trajectory Prediction
Yuying Chen, Congcong Liu, Xiaodong Mei +2
Accurate pedestrian trajectory prediction is of great importance for downstream tasks such as autonomous driving and mobile robot navigation. Fully investigating the social interac…
High-speed Autonomous Drifting with Deep Reinforcement Learning
Peide Cai, Xiaodong Mei, Lei Tai +2
Drifting is a complicated task for autonomous vehicle control. Most traditional methods in this area are based on motion equations derived by the understanding of vehicle dynamics,…