Multilevel road networks such as flyovers and overpasses are built in large cities to solve traffic congestion. Instant correct identification of the road level that a vehicle is driving in a multilevel road network is important to make driving more pleasant, safer, and smarter.
Vehicle drivers relying on GPS navigation who accidentally drive onto a flyover with intention only to proceed on the ground level will face this problem: the GPS navigation system does not realise the vehicle has entered a wrong level and continues to give instructions as if it were on the ground level. Only after quite a while will the system notice the wrong road level and begin to redirect to a new route.
Present vehicle navigation system that uses GPS with positioning error of 10-30 meters has a long existing problem in determining which road level a vehicle has entered, especially for flyovers parallel to the ground level. The problem often creates confusion and "motorway anxiety disorder" that makes people more prone to accidents in driving.
Professor Anthony Yeh Gar-On's research team at the Department of Urban Planning and Design of the University of Hong Kong (HKU) offers a novel solution to this long existing vehicle navigation problem since GPS was used over 20 years ago by instantly identifying whether a vehicle has entered a flyover or is still on the ground level.
The Angle Difference Method developed by the team compares the inclination angle of a vehicle and angles of different road levels stored in a Transport GIS to determine whether a vehicle has entered the ramp of a flyover or still on the ground level. It uses an ordinary smartphone that can be put anywhere at any angle in the vehicle with a plugged in or installed onboard diagnostic (OBD) device.
The system provides a simple and inexpensive solution to warn drivers INSTANTLY when he has accidentally entered a wrong road level. The accuracy for identification is 100%. Such timely information will reduce the stress and uncertainty in driving in a complex multilevel road system, making driving more pleasant, safer, and smarter.
The innovation won a gold medal award at the Geneva International Exhibition of Inventions in April 2018. It has received an US patent and an International PCT patent and generated several academic papers published in international academic journals including IEEE Transactions on Intelligent Transportation Systems.
The team is currently discussing with global GIS and vehicle navigation operators including major operators on the Mainland on potential application of the system to enable a major advancement in the current navigation system for vehicles, particularly in large cities with complicated flyover networks.
Professor Yeh said: "The invention provides an innovative, simple, and inexpensive method to overcome the long existing vehicle navigation problem that many people have tried to solve since GPS was used over 20 years ago by determining instantly whether a vehicle has entered a flyover or still on the ground level. The research team will further apply this "Angle Difference Method" to the navigation of automatic cars."
HKU research teams won eight awards at the Geneva International Exhibition of Inventions, including the Prize of Patent Office of the Cooperation Council for the Arab States of the Gulf - GCCPO and Gold Medal with Special Recognition by the International Jury of Experts, three gold medals and three silver medals. (Please click here for a list of the HKU award winning projects)
For videos to illustrate the innovation and show how vehicle GPS navigation works under the current system and the modified system utilising the innovation.
Angle Difference Method for Vehicle Navigation in Multilevel Road Networks
Geneva International Exhibition of Inventions Gold Medal Award
Professor Anthony YEH Gar-On and Dr ZHONG Teng
Department of Urban Planning and Design, HKUrbanLab, GIS Research Centre and Institute of Transport Studies of the University of Hong Kong
Professor YUE Yang (PhD graduate of Professor Yeh)
Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University