2 citations · 3 across the 8 of their papers we have counts for
8 papers
EEG-Based Emergency Braking Intensity Prediction Using Blind Source Separation
Zikun Zhou, Wenshuo Wang, Wenzhuo Liu +5
Electroencephalography (EEG) signals have been promising for long-term braking intensity prediction but are prone to various artifacts that limit their reliability. Here, we propos…
UV-M3TL: A Unified and Versatile Multimodal Multi-Task Learning Framework for Assistive Driving Perception
Wenzhuo Liu, Qiannan Guo, Zhen Wang +9
Advanced Driver Assistance Systems (ADAS) need to understand human driver behavior while perceiving their navigation context, but jointly learning these heterogeneous tasks would c…
CrossRay3D: Geometry and Distribution Guidance for Efficient Multimodal 3D Detection
Huiming Yang, Wenzhuo Liu, Yicheng Qiao +8
The sparse cross-modality detector offers more advantages than its counterpart, the Bird's-Eye-View (BEV) detector, particularly in terms of adaptability for downstream tasks and c…
The Effects of Communication Delay on Human Performance and Neurocognitive Responses in Mobile Robot Teleoperation
Zhaokun Chen, Wenshuo Wang, Wenzhuo Liu +2
Communication delays in mobile robot teleoperation adversely affect human-machine collaboration. Understanding delay effects on human operational performance and neurocognition is…
TEM^3-Learning: Time-Efficient Multimodal Multi-Task Learning for Advanced Assistive Driving
Wenzhuo Liu, Yicheng Qiao, Zhen Wang +8
Multi-task learning (MTL) can advance assistive driving by exploring inter-task correlations through shared representations. However, existing methods face two critical limitations…
MMTL-UniAD: A Unified Framework for Multimodal and Multi-Task Learning in Assistive Driving Perception
Wenzhuo Liu, Wenshuo Wang, Yicheng Qiao +9
Advanced driver assistance systems require a comprehensive understanding of the driver's mental/physical state and traffic context but existing works often neglect the potential be…
MIPD: A Multi-sensory Interactive Perception Dataset for Embodied Intelligent Driving
Zhiwei Li, Tingzhen Zhang, Meihua Zhou +7
During the process of driving, humans usually rely on multiple senses to gather information and make decisions. Analogously, in order to achieve embodied intelligence in autonomous…
Path Planning for Air-Ground Robot Considering Modal Switching Point Optimization
Xiaoyu Wang, Kangyao Huang, Xinyu Zhang +5
An innovative sort of mobility platform that can both drive and fly is the air-ground robot. The need for an agile flight cannot be satisfied by traditional path planning technique…