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http://dx.doi.org/10.12815/kits.2021.20.6.331

A Study on Sensor Modeling for Virtual Testing of ADS Based on MIL Simulation  

Shin, Seong-Geun (ICT Convergence R&D Center, Korea Automotive Technology Institute)
Baek, Yun-Seok (ICT Convergence R&D Center, Korea Automotive Technology Institute)
Park, Jong-Ki (ICT Convergence R&D Center, Korea Automotive Technology Institute)
Lee, Hyuck-Kee (ICT Convergence R&D Center, Korea Automotive Technology Institute)
Publication Information
The Journal of The Korea Institute of Intelligent Transport Systems / v.20, no.6, 2021 , pp. 331-345 More about this Journal
Abstract
Virtual testing is considered a major requirement for the safety verification of autonomous driving functions. For virtual testing, both the autonomous vehicle and the driving environment should be modeled appropriately. In particular, a realistic modeling of the perception sensor system such as the one having a camera and radar is important. However, research on modeling to consistently generate realistic perception results is lacking. Therefore, this paper presents a sensor modeling method to provide realistic object detection results in a MILS (Model in the Loop Simulation) environment. First, the key parameters for modeling are defined, and the object detection characteristics of actual cameras and radar sensors are analyzed. Then, the detection characteristics of a sensor modeled in a simulation environment, based on the analysis results, are validated through a correlation coefficient analysis that considers an actual sensor.
Keywords
Sensor modeling; Virtual testing; MILS; Automated driving system testing;
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