PolyU research brings innovative solutions to promote new energy transportation and enhance driving safety

The Hong Kong Polytechnic University (PolyU) applies advanced technologies to drive the development of smart cities and smart mobility and bring innovative solutions to society. In the latest batch of Smart Traffic Fund approved projects, three PolyU projects have received total funding of approximately HK$8.42 million.

One of the recently-funded projects focuses on designing software for optimising the planning and scheduling of new energy buses to build a more environmentally friendly travel experience and promote the development of new energy public transport. The other two projects relate to the development of a network connected advanced driver assistance system that provides predictive warnings and driving advice for improved driver safety, and to a human-machine co-operative driving system that monitors driving conditions and enhances driving safety with the real-time estimation of driving risks.

Prof. Christopher CHAO, Vice President (Research and Innovation) of PolyU, said, “The Smart Traffic Fund has been instrumental in powering innovation in long-term transportation development. These funded projects help PolyU realise its mission of creating positive impact in society and showcases our committed efforts to addressing social needs through the application of advanced technologies. Moving forward, PolyU will continue to be at the forefront of innovative research in the transportation industry.”

Since the HKSAR Government launched the Smart Traffic Fund in November 2021, a total of 36 projects have been funded, of which 14 are PolyU led projects, involving approved funding of approximately HK$45.9 million. With continuous contributions, PolyU has been leading in funding achievements.

Previously-funded PolyU projects have employed various advanced technologies to predict and assist in the management of different traffic conditions, such as using artificial intelligence to predict vacant parking spaces, deep learning models to predict traffic data, 3D geo-spatial models for driving simulation safety assessment and using intelligent automation technology to assess driver behaviour and psychological status.

Details of the three recently-funded projects:

Principal Investigator	Project Title	Project Summary
Dr Weihua GU, Associate Professor, Department of Electrical Engineering	Development of Software for Optimising the Planning and Scheduling of New Energy Buses	The project aims to develop a software tool to optimise the planning and scheduling of new energy buses on different routes.
Dr Hailong HUANG, Assistant Professor, Department of Aeronautical and Aviation Engineering	Development of a Personalised and Connected Advanced Driver Assistance System	This project aims to develop a personalised and connected advanced driver assistance system, which targets both driving habits of individual drivers and motion prediction of surrounding vehicles so as to improve driving safety by providing predictive warnings and driving advice.
Dr Chao HUANG, Research Assistant Professor, Department of Industrial and Systems Engineering	Designing of an Intelligent Human-machine Cooperative Driving System	This project aims to develop a human-machine cooperative driving system to enhance driving safety. Monitoring of drivers’ driving status and real-time estimation of driving risks will be included in the system.

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