Advanced Driver Assistance Systems (ADAS) and Autonomous Driving (AD) vehicles rely heavily on sensors for achieving their goal of protecting the driver and passengers from potentially dangerous situations. Optical sensors are used to measure locations and velocities of objects at distances of up to 150 meters. Optical sensors could be cameras (for visible light or IR) used to detect either objects or road features (like e.g. road edges and markings). They are a common choice for high-end ADAS and are found in sensor sets of most AD vehicles.
To ensure reliable performance of object detection, extensive testing of optical sensors is required. In vehicle testing performed at test tracks like AstaZero, 3D soft car targets are used for safety reasons. However, due to non-perfect shape and materials, the optical characteristics of 3D soft car targets may differ considerably from that of real vehicles in traffic, resulting in different detection performance, and hence different activation of the functions. Moreover, during tests the quality of the 3D soft car targets deteriorates due to repeated impacts and reassembly of the targets, which implies that there is a need of methods for securing the quality of the 3D soft car targets over time.
By addressing these challenges, the goal of the project has been to contribute to improved testing methods of optical and geometrical characteristics of 3D soft car targets by:
The results include test of different measurement methods, different 3D soft car targets as well as real vehicles and also an accelerated ageing test of a 3D soft car target from DRi.