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Researchers develop new location system for intelligent vehicles

-- Success Story --

Researchers develop new location system for intelligent vehicles

One of the challenges holding back further developments in vehicle autonomy is the reliability and accuracy of the signals and systems used to pinpoint a vehicle's location, as well as its ability to communicate its position to other vehicles and infrastructure.

WMG's Connectivity and Communications Technology research team are actively researching projects to improve our understanding of how these signals work and develop testing methodologies to accelerate the adoption of intelligent vehicle technologies.

Challenge

Most smart devices rely on Global Navigation Satellite Systems (GNSS) like GPS for location tracking, but in urban environments, high-rise buildings can obscure the signal making it less reliable. In indoor environments, these signals are even further impaired, if not unavailable altogether. On the other hand, in these dense urban environments, WiFi signals are often ubiquitous.

Researchers identified the potential to ‘fuse’ WiFi and GNSS signals together in order to pinpoint a device’s location with great accuracy both indoors and outdoors, something which had never been done before.

The Enhanced Assured Location Simulation Leveraging WiFi and GNSS for Sensor Fusion (ELWAG) project was funded by Innovate UK and led by Spirent Communications in collaboration with WMG and Chronos Technology. The aim of the study was to develop a simulator to test the hybrid WiFi-GNSS system in a robust and repeatable way, demonstrating its viability in the real world for intelligent vehicle applications and more.

Solution

Our research team generated real world data both from a laboratory environment, and on real roads around the University of Warwick campus, using the buildings and foliage to see how the signal strength and reliability was affected when something was in the way.

This data was then used by Spirent to develop a pioneering prototype WiFi-GNSS simulator. Finally, combined with Chronos Technology’s test measurement expertise, WMG researchers worked together to verify and validate the prototype, by simulating moving vehicles, obscuration of signals, spoofing (a form of interference where GNSS signals are manipulated), and data errors.

The ELWAG project was able not only to achieve the successful fusion of WiFi and GNSS signals for the first time, they also were able to demonstrate a controlled repeatable testing environment that is representative of the real world.

Dr Matthew Higgins, Reader at WMG, believes “the success of ELWAG has been possible in part through the availability of the 3xD simulator. The facility has proven to be versatile, and to take on board a cutting edge project though adaptation of the technical capabilities, and as such, delivering an impact to the project partners”.

Impact

This is the first time it has been possible to accurately simulate and test the hybrid WiFi-GNSS in both a laboratory and real-world environment. The ELWAG project has opened up a number of areas of further research, but early commercial opportunities include indoor wayfinding, such as in a large shopping complex, and even valet parking.

“Previously, WiFi access point plus GNSS simulation could only be achieved in an ad hoc manner and did not allow for the testing of moving vehicles, multipath effects, insertion of data errors, spoofing, and above all controlled, repeatable testing,” said Mark Holbrow, Spirent Positioning’s Senior Director of Engineering and Product Development. “This project has successfully demonstrated how it’s possible to reach the evolving PNT test requirements for a realistic, lab based, synchronous, multi-sensor test solution.”

Real-world use of this technology in autonomous vehicles is on the horizon, Spirent and WMG have since collaborated on the £1.2m Zenzic PNT Cyber project, which aimed to further develop the ELWAG technology by developing a PNT vulnerability test bed capable of replicating satellite/data errors as well as spoofed GNSS signals.

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