Methodical Approach to the Development of a Radar Sensor Model for the Detection of Urban Traffic Participants Using a Virtual Reality Engine  

作　　者：Rene Degen Harry Ott Fabian Overath Christian Schyr Mats Leijon Margot Ruschitzka Rene Degen;Harry Ott;Fabian Overath;Christian Schyr;Mats Leijon;Margot Ruschitzka(CAD CAM Center Cologne, Institute of Automotive Engineering Cologne (IFK), Faculty of Automotive Systems and Production, Cologne University of Applied Science, Cologne, Germany;Division of Electricity, Department of Electrical Engineering, Uppsala University, Uppsala, Sweden;Advanced Solution Lab, AVL Deutschland GmbH, Karlsruhe, Germany)

机构地区：[1]CAD CAM Center Cologne, Institute of Automotive Engineering Cologne (IFK), Faculty of Automotive Systems and Production, Cologne University of Applied Science, Cologne, Germany [2]Division of Electricity, Department of Electrical Engineering, Uppsala University, Uppsala, Sweden [3]Advanced Solution Lab, AVL Deutschland GmbH, Karlsruhe, Germany

出　　处：《Journal of Transportation Technologies》2021年第2期179-195,共17页交通科技期刊（英文）

摘　　要：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.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.

关 键 词：Advanced Driver Assistance Systems (ADAS) Autonomous Mobility Diffuse Scattering Microwave Propagation Radar Raw Data RAYTRACING Sensor Simulation 

分 类 号：TN9[电子电信—信息与通信工程]