Function monitoring increases safety. Consequentially, vehicle monitoring systems will be indispensable in automated vehicles in the future. In this research direction we develop measurement systems and methodologies for condition monitoring, with the aim of assessing the sensor condition over lifetime, detecting defective functions and investigating recalibration approaches to cope with degradation effects.  A central area is the life cycle prognosis of relevant automotive, safety critical systems such as ADAS camera, LiDAR and Radar.

Keywords: lidar sensor technology; passive and active VRU protection, ADAS Radar and Infrared Camera Technology, Sensor data fusion; ADAS LiDAR, physical sensor modeling, Sensor technology, Digital signal processing, Sensor simulation, Raw data processing, Camera sensor technology. Lifetime prediction and reliability analysis. Data-driven approaches, artificial intelligence, data science, machine learning, parameter estimation and calibration, optimization, reliability analysis and lifetime prediction

Projects: SMART-ADAS, KI-LiDAR, CommonSense, Aurora, GAIA-X4KI

 

Test rigs for reliability tests of LiDAR sensors under accelerated thermal ageing (left) and weather influences (right).

 

 

Open positions

If you are interested in vacancies for student work within the research group, please send an email with CV to assistenz-iimo-elger@thi.de.