The Department is delighted to announce that two of our esteemed colleagues, Prof Weisong Wen and Dr Li Qinbiao from the Department of Aeronautical and Aviation Engineering (AAE), have successfully secured funding from the 23rd batch of the Smart Traffic Fund (STF), as announced by the Transport Department on 22 January 2026.
This round of funding saw four innovative projects approved, with three led by PolyU researchers.
|
Institution |
Project Title |
Name of PI |
|
Hong Kong Smart City Limited and Hong Kong Metropolitan University |
Driving Performance Analysis Assistance System for Driving Tests |
Mr CHOW Hei Sen |
|
The Hong Kong Polytechnic University |
Application of End-to-End Intelligent Driving System in Logistics Industry |
Prof. Weisong WEN (AAE) |
|
The Hong Kong Polytechnic University |
Wearable Wristband-based Driver Attention Monitoring and Alerting System |
Dr LI Qinbiao (AAE) |
|
The Hong Kong Polytechnic University |
Bus Automatic Emergency Braking System Designed for Hong Kong Road and Traffic Conditions |
Prof. SZE Nang Ngai (CEE) |
Project Highlights
Prof Weisong Wen’s project, “Application of End-to-End Intelligent Driving System in Logistics Industry” is awarded over HK$ 7,000,000. The project will deliver Hong Kong’s first end-to-end autonomous delivery vehicle platform, integrating localization, perception, and control within a unified AI system. This innovative approach is designed to significantly enhance logistics efficiency and alleviate road congestion, offering exceptional adaptability to Hong Kong’s unique urban environment by removing conventional system boundaries.
Dr Li Qinbiao’s project, “Wearable Wristband-based Driver Attention Monitoring and Alerting System” is awarded over $4,500,000. It aims to improve road safety by developing a real-world-ready solution to mitigate driver attention-loss states. By analyzing data collected from wearable, commercialized health-tracking wristbands, the system continuously monitors multiple physiological signals—such as photoplethysmogram (PPG), heart rate variability (HRV), and blood oxygen saturation—to assess driver attentiveness. Advanced deep learning algorithms detect signs of drowsiness and distraction, generating a Unified Attention-Loss Index (UAI) and issuing graded alerts to both drivers and fleet managers, providing timely warnings to enhance road safety.
Congratulations to Prof Wen and Dr Li for their outstanding achievements and contributions to advancing smart mobility and road safety in Hong Kong!
Read the full Smart Traffic Fund approved projects list at https://stf.hkpc.org/list-of-approved-projects/.
