RISK ESTIMATION FOR PERCEPTION FAILURES IN AUTOMATED DRIVING
Sammanfattning
The failure of sensors to perceive the environment correctly is one of the primary
sources of risk that needs to be quantified in the development of active safety
features for autonomous vehicles. By extracting training data from the CARLA
simulator, an object detector was trained to simulate a perception system of
an autonomous vehicle. Using the detection model and gathering data for incorrect
detections, various extreme value models were created and compared
to investigate if extreme value theory is a viable option for estimating the risk
of sensor failures of the perception system. An analysis of the extreme value's
dependency on the velocity of the vehicle is performed and a risk measure is
presented.
Examinationsnivå
Student essay