u-blox has announced that Siemens has integrated the u‑blox ZED-F9K high precision dead reckoning module into its Toyota Prius V2X (vehicle-to-everything) test fleet. Siemens carried out live demonstrations of the technology at the ITS European Congress 2019 (https://2019.itsineurope.com/) in Eindhoven, the Netherlands.
As the only available source of absolute position, satellite-based positioning plays a crucial role in advanced driver automation systems and driverless vehicles. The same is true in V2X communication, in which vehicles continuously share their location and other information with other traffic participants – cars and pedestrians – as well as surrounding infrastructure, improving road safety and reducing traffic congestion.
V2X test vehicles typically determine their position using high-end, expensive GNSS (Global Navigation Satellite Systems) receivers. While these provide highly accurate position information, they fail to realistically represent the hardware that will be deployed in vehicles produced for the mass market. By opting to use the ZED-F9K turnkey solution for high precision dead reckoning, Siemens was able to align the performance of their test fleet with real world conditions while also reducing the cost and the engineering effort required to develop their vehicles.
“We’ve had a very positive experience with u-blox’s ZED-F9K high precision dead reckoning solution. The product delivered strongly from the initial design-in to the data and performance in our first tests,” says Igor Passchier, Engineering fellow, Connected and Automated Driving at Siemens PLM Software. “It underscores the reputation of u‑blox as a trusted innovator in GNSS technology.”
“Our collaboration with Siemens shows the extent to which the ZED-F9K turnkey solution saves OEMs time, cost, and engineering effort while providing decimeter-level positioning performance,” says Alex Ngi, Product Strategy for Dead Reckoning, Product Center Positioning, u-blox. “For us, it has also been a welcome opportunity to contribute to solving the challenges in the autonomous driving ecosystem.”
