Development of High-Fidelity Automotive LiDAR Sensor Model with Standardized Interfaces

Abstract

This work introduces a process to develop a tool-independent, high-fidelity, ray tracing-based light detection and ranging (LiDAR) model. This virtual LiDAR sensor includes accurate modeling of the scan pattern and a complete signal processing toolchain of a LiDAR sensor. It is developed as a functional mock-up unit (FMU) by using the standardized open simulation interface (OSI) 3.0.2, and functional mock-up interface (FMI) 2.0. Subsequently, it was integrated into two commercial software virtual environment frameworks to demonstrate its exchangeability. Furthermore, the accuracy of the LiDAR sensor model is validated by comparing the simulation and real measurement data on the time domain and on the point cloud level. The validation results show that the mean absolute percentage error (MAPE) of simulated and measured time domain signal amplitude is 1.7%. In addition, the MAPE of the number of points Npoints and mean intensity Imean values received from the virtual and real targets are 8.5% and 9.3%, respectively. To the author’s knowledge, these are the smallest errors reported for the number of received points Npoints and mean intensity Imean values up until now. Moreover, the distance error derror is below the range accuracy of the actual LiDAR sensor, which is 2 cm for this use case. In addition, the proving ground measurement results are compared with the state-of-the-art LiDAR model provided by commercial software and the proposed LiDAR model to measure the presented model fidelity. The results show that the complete signal processing steps and imperfections of real LiDAR sensors need to be considered in the virtual LiDAR to obtain simulation results close to the actual sensor. Such considerable imperfections are optical losses, inherent detector effects, effects generated by the electrical amplification, and noise produced by the sunlight.

Performance Evaluation of MEMS-Based Automotive LiDAR Sensor and Its Simulation Model as per ASTM E3125-17 Standard

“…This section will provide an overview of the toolchain and signal processing steps of the LiDAR FMU model. A detailed description of the LiDAR FMU modeling methodology can be found in [ 23 ]. The toolchain and signal processing steps of the LiDAR FMU model are shown in Figure 4 .…”

“…Therefore, in this paper, we have evaluated the 3D imaging and point-to-point distance measurement performance of the Blickfeld micro-electro-mechanical systems (MEMS)-based automotive LiDAR sensor and its simulation model (LiDAR FMU) according to the ASTM E3125-17 tests method. It should be noted that same authors have developed the LiDAR FMU model in their previous work [ 23 ] for the simulation-based testing of ADAS, and the presented paper is the continuity of it. The authors want to bring the scientific community’s attention, focusing on developing and validating automotive real and virtual LiDAR sensors to the ASTM E3125-17 standard.…”

“…The LiDAR sensor model is developed as a functional mock-up unit (FMU) by using the standardized open simulation interface (OSI) and functional mock-up interface (FMI) [ 23 ]. The model is packaged as an OSI sensor model packaging (OSMP) FMU [ 25 ].…”

“…Therefore, it was integrated successfully into the co-simulation environment of CarMaker from IPG Automotive. The virtual LiDAR sensor considers the accurate modeling of scan pattern and complete signal processing toolchain of the Cube 1 LiDAR sensor, as described in [ 23 ].…”

“…It measures the round trip delay time (RTDT) that laser light takes to hit an object and return to the detector. With the RTDT , the range R can be calculated as [ 23 ]: where the range is denoted by R , c is the speed of light, and is the RTDT, also known as the time of flight (ToF).…”