Research Interest: Human factors in driving behavior, Driving adaption and safety reaction, Driving assistant design
Education
B.Eng, Industry Design, Shandong University, 2016.09-2020.06
M.Eng, Industry Design Engineering, Shandong University, 2020.09-2023.06
Ph.D, Aviation Engineering, The Hong Kong Polytechnic University, 2025.01-present
International Visit
International Visit Student, Korea Advanced Institute of Science & Technology (KAIST), 2026.10-2026.12
Employment
CHINA NATIONAL HEAVY DUTY TRUCK GROUP CO.,LTD，2023.07-2024.11
Core Research
Research 1: Development of human-centric driver support systems and training recommendations for safer cross-border driving in GBA and beyond.
Motivated by the “Hong Kong Vehicles Going North” policy, this research develops an integrated framework for cross-regional driving adaptation and safety enhancement. We developed a real-world cross-border driving simulation and training system to reproduce unfamiliar traffic environments and improve drivers’ adaptation and safety responses, while collecting naturalistic driving data from more than 150 drivers to identify maladaptive driving behaviors and associated risks. Based on these findings, we further developed a context-aware driving assistance system that translates behavioral risk patterns into proactive safety interventions. The main contribution is to establish a complete pathway from driving adaptation training, maladaptation identification, intelligent safety assistance, providing a data-driven approach to improving safety in cross-regional driving.
Main contributions of Research 1:
1) Visual Mismatch and Blind-Spot Risk: Identified the effects of cross-regional visual mismatch on blind-spot risk and evaluated drivers’ visual adaptation and compensatory behaviors.
2) Dynamic Speed-Limit Optimization: Developed reasonable dynamic speed-limit sign ranges for cross-regional highways and evaluated their effectiveness using a duration model.
3) Naturalistic Driving Risk Identification: Analyzed and clustered naturalistic driving data from 150+ drivers to identify maladaptive driving patterns and develop a data-driven driver risk identification framework.
Key Publications
Journal Paper
[1] Visual Mismatch and Adaptation Behaviour Under Unfamiliar Driving Environment: A Comparative Eye-Tracking Study of Blind Spot In LHD and RHD. International Journal of Industrial Ergonomics. (Major revision)
Conference Paper
[1] A Driving Assistant HUD Design to Mitigate the Risk of Blind Spot in Cross-Border Driving (The 2026 International Conference on Human-Computer Interaction)
[2] Is Aggressive Behavior in Cross-Border Driving Predictable? An Empirical Study Based on the Binary Logit model (The 15th Asia-Pacific Conference on Transportation and the Environment)
[3] Risk qualification for cross-boundary driving in typical intersections caused by blind spot (The 29th International Conference of Hong Kong Society for Transportation Studies)
Awards
Best Student Paper Runner up, The 29th HKSTS conference.