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WMG to test new location system for intelligent vehicles

Intelligent vehicles and smart devices could gain more accurate location awareness by ‘fusing’ Global Navigation Satellite Systems (GNSS) and WiFi signals – and a test for this is the focus of an Innovate UK project led by Spirent Communications and involving WMG at the University of Warwick.

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The £694k ‘Enhanced Assured Location Simulator Leveraging WiFi and GNSS Sensor Fusion’ (ELWAG) project will seek to develop to test this pioneering hybrid WiFi and GNSS location system in a cost-effective, repeatable and safe environment – so that manufacturers can verify its performance.

Researchers at WMG, led by Dr Matthew Higgins, will play a significant role in the project. They will take physical layer measurements of both Wi-Fi and GNSS signals in Autonomous Vehicle scenarios, in and around the University of Warwick campus and the local urban road network.

These measurements will then assist in Spirent’s development of an RF propagation model that will overlay RF effects on their Wi-Fi Access Point simulator. WMG researchers will then perform RF validation and verification activities around the developed model, to provide a level of assurance on its performance.

Dr Matthew Higgins, Associate Professor in the Intelligent vehicles group at WMG, University of Warwick, commented: “The safety and functional assurance of future autonomous vehicles will be one of the many critical paths to large consumer adoption. Through this project, we will contribute towards providing innovative solutions to the challenges of using sensor fusion in this testing context.”

Dr Erik Kampert, Senior Research Fellow at WMG, added: “This is a highly technical project, which will require a holistic understanding of the signal propagation characteristics between Satellites, Infrastructure and Vehicles. The results will impact future autonomous testing methodologies.”

The ELWAG project will run for 18 months, and also involves Chronos Technology.

Many devices currently rely on a singular location technology (typically GPS), which is one type of the wider eco system of GNSS. These systems, whilst becoming more capable, still suffer at times from the user's environment - typically in urban areas where buildings and other cityscape features interfere with the signal.

The urban environment is, however, where most of us need to know our location to the highest level of accuracy, due to increasing population or device density. WiFi signals exist almost universally within dense urban areas, so there is a possibility of ‘fusing’ these signals with the GNSS signals to identify one's location very accurately.

Mark Holbrow, Director of Engineering and Product Development at Spirent’s Positioning Business Unit, said: “Currently Wi-Fi access point plus GNSS simulation can only be achieved in an ad hoc manner and does not allow for the testing of moving vehicles, multipath effects, insertion of data errors, spoofing and above all controlled, repeatable testing.

“In the autonomous vehicle sector location accuracy can vary by up to 5 metres, which is unacceptable from a safety perspective. Bringing that accuracy down to 30 centimetres through sensor fusion will have substantial implications for autonomous navigation.”

The need for smart devices to have a highly accurate self-awareness of their own location, and the location of other smart devices around is becoming increasingly important.

In applications such as autonomous vehicles and transport systems, accurate location awareness is an obvious operational requirement as to their safe operation in and around other vehicles, pedestrians of the infrastructure.

In the personal devices space, smart watches, phones, health monitoring and exercise aids are all striving to be able to make a judgement of the user’s state based upon location.

In the emergency and security services space, knowing the location of people and objects is also increasingly important as to target response capabilities effectively.

Tue 01 May 2018, 17:22 | Tags: Intelligent Vehicles