TITLE:
Methodical Approach to the Development of a Radar Sensor Model for the Detection of Urban Traffic Participants Using a Virtual Reality Engine
AUTHORS:
Rene Degen, Harry Ott, Fabian Overath, Christian Schyr, Mats Leijon, Margot Ruschitzka
KEYWORDS:
Advanced Driver Assistance Systems (ADAS), Autonomous Mobility, Diffuse Scattering, Microwave Propagation, Radar Raw Data, Raytracing, Sensor Simulation
JOURNAL NAME:
Journal of Transportation Technologies,
Vol.11 No.2,
March
31,
2021
ABSTRACT: New
approaches for testing of autonomous driving functions are using Virtual
Reality (VR) to analyze the behavior of automated vehicles in various
scenarios. The real time simulation of the environment sensors is still a
challenge. In this paper, the conception, development and validation of an
automotive radar raw data sensor model is shown. For the implementation, the
Unreal VR engine developed by Epic Games is used. The model consists of a
sending antenna, a propagation and a receiving antenna model. The microwave
field propagation is simulated by a raytracing approach. It uses the method of
shooting and bouncing rays to cover the field. A diffused scattering model is
implemented to simulate the influence of rough structures on the reflection of
rays. To parameterize the model, simple reflectors are used. The validation is
done by a comparison of the measured radar patterns of pedestrians and cyclists
with simulated values. The outcome is that the developed model shows valid
results, even if it still has deficits in the context of performance. It shows
that the bouncing of diffuse scattered field can only be done once. This
produces inadequacies in some scenarios. In summary, the paper shows a high
potential for real time simulation of radar sensors by using ray tracing in a
virtual reality.