Update: 16th October 2026
(†: equal contribution, ~: corresponding author)
Preprints
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TriDrive: Joint Driver, Vehicle, and Road Modeling for Forecasting and Driver Monitoring
Yuhang Wang, Jingxin Yang, Chuheng Wei, Yuechen Guo, Jinghan Xu, Zhao Han, Hao Zhou
arXiv 2609.33000, September 2026. Under review. [arXiv] [Model] -
DriveDNA: A Large-Scale Multimodal Naturalistic Driving Dataset and Benchmark for Driving Style Identification
Yuhang Wang, Lingyao Li, Hao Zhou
arXiv 2607.23822, July 2026. [arXiv] [Data] -
BATON: A Multimodal Benchmark for Bidirectional Automation Transition Observation in Naturalistic Driving
Yuhang Wang, Yiyao Xu, Chaoyun Yang, Lingyao Li, Jingran Sun, Hao Zhou
arXiv 2604.07263 (v2, July 2026). [arXiv] [Data]
Conference Paper
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DriveMotion: A Large-Scale Multi-Source Benchmark for Driver Motion Sequence Modeling and Forecasting
Yuhang Wang, Chuheng Wei, Jingxin Yang, Xishun Liao, Hao Zhou
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2027)
Lake Buena Vista, Florida, United States. January, 2027. [arXiv] [Data] -
Observe Before You Alert: Adaptive Driver Alerting with Vision–Language Models
Yuhang Wang, Lingyao Li, Hao Zhou
Conference on Robot Learning (CoRL 2026). CoRL 2026 Travel Award. [PDF] [arXiv] -
ADAS-TO: A Large-Scale Multimodal Naturalistic Dataset and Empirical Characterization of Human Takeovers during ADAS Engagement
Yuhang Wang, Yiyao Xu, Jingran Sun, Hao Zhou
IEEE Intelligent Transportation Systems Conference (ITSC 2026) -
OpenLKA: An Open Dataset of Lane Keeping Assist from Production Vehicles Under Real-World Driving Conditions
Yuhang Wang, Abdulaziz Alhuraish, Shengming Yuan, Hao Zhou
IEEE Intelligent Transportation Systems Conference (ITSC 2025)
Gold Coast, Australia. November, 2025. Journal extension under review at Accident Analysis & Prevention. [Data access] -
Empirical Characterization of Electric Vehicle Acceleration: Implications for Lane Changes and Traffic Bottleneck Capacity
Ruqing (Kara) Huang, Yuhang Wang, Lee D. Han, Hao Zhou
TRB Annual Meeting 2026
Washington, D.C., United States. January, 2026. -
Computational design of custom-fit PAP masks
Yukun Lu, Yuhang Wang, Peng Song, Hang Siang Wong, Yingjuan Mok and Ligang Liu
Shape Modeling International (SMI 2024)
Wayne State University, United States. July, 2024.