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20232026
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cs.RO2026

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…

cs.RO2025

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…

cs.RO2025

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…

cs.RO2025

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…

cs.RO2024

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…

cs.RO2023

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…