Data about the precise location and speed are supplied by Global Navigation Satellite Systems (GNSS). With the help of additional correction methods, the position in three-dimensional space can be determined with an accuracy of a few decimetres. In addition, a variety of different sensors, including optical sensors such as lidar and radar, are used to detect obstacles and road markings. GNSS positioning and movement data can be exchanged with other vehicles (Car2Car) via wireless data connections or sent to a higher-level infrastructure (Car2X). In this way, potential accidents can be prevented early on, drastic braking manoeuvres are no longer necessary, and traffic jams are also becoming increasingly rare. With the aid of fleet control technology, it is even possible to identify vehicles that are not visible to the driver, for example because they are covered in curves by buildings or plants. The further development of ADAS systems and increasingly autonomous vehicles leads to greater safety and efficiency in road traffic.
To ensure the safety of ADAS and autonomous driving, millions of test kilometers must be driven on different roads in different environments. GNSS reception is not of constant quality. Especially in city centres and mountain areas, the reception of navigation data can be disturbed by the coverage of signals by buildings, bridges, vegetation or mountains. In addition, GNSS signals are reflected on flat and curved surfaces (multipath). In addition, there are additional sources of interference that can potentially block, interfere with or falsify GPS/GNSS receivers. Testing is therefore time-consuming and costly when all the required kilometres actually have to be driven.
