8 papers
PATH: Preference-Aware Traversability Estimation for Robotic Teleoperation in Off-Road Navigation
Xianghao Meng, Wenshuo Wang, Cheng Shao +4
Traversability estimation is critical for ground vehicle teleoperation, yet existing methods often neglect the human operator's preferences for speed and risk tolerance. To address…
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…
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…
An Evolutionary Game-Theoretic Merging Decision-Making Considering Social Acceptance for Autonomous Driving
Haolin Liu, Zijun Guo, Yanbo Chen +3
Highway on-ramp merging is of great challenge for autonomous vehicles (AVs), since they have to proactively interact with surrounding vehicles to enter the main road safely within…
Driving Style Recognition Like an Expert Using Semantic Privileged Information from Large Language Models
Zhaokun Chen, Chaopeng Zhang, Xiaohan Li +3
Existing driving style recognition systems largely depend on low-level sensor-derived features for training, neglecting the rich semantic reasoning capability inherent to human exp…
100 Drivers, 2200 km: A Natural Dataset of Driving Style toward Human-centered Intelligent Driving Systems
Chaopeng Zhang, Wenshuo Wang, Zhaokun Chen +1
Effective driving style analysis is critical to developing human-centered intelligent driving systems that consider drivers' preferences. However, the approaches and conclusions of…
Shareable Driving Style Learning and Analysis with a Hierarchical Latent Model
Chaopeng Zhang, Wenshuo Wang, Zhaokun Chen +3
Driving style is usually used to characterize driving behavior for a driver or a group of drivers. However, it remains unclear how one individual's driving style shares certain com…