Method and Applications of Lidar Modeling for Virtual Testing of Intelligent Vehicles

Zhao Jian; Li Yaxin; Zhu Bing; Deng Weiwen;etc

作者单位:Jilin Univ, State Key Lab Automot Simulat & Control;Beihang Univ, Beijing Adv Innovat Ctr Big Data & Brain Comp

发表期刊IEEE Transactions on Intelligent Transportation Systems,Vol. 22, No.5. MAY 2021

摘要:With the common use of lidar sensors on intelligent vehicles, the simulation of lidar in autonomous driving is necessary. This study proposes an innovative lidar modeling method, and introduces solutions for the simulation of the lidar detection function and its physical mechanism. The model consists of geometric and physical models, and can simulate both point clouds and targets. The geometric model addresses the spatial relationship between lidar and the environment. The physical model describes how the lidar detection mechanism may influence detection results. Signal attenuation and unwanted raw data caused by raindrops are the main consideration in the physical model. Characteristics of lidar signal attenuation in different weather conditions are modeled, and a simplified lidar equation is derived for use by lidar users, as opposed to designers. Unwanted raw data are simulated in a stochastic model employing the Monte Carlo method, where raindrop size and distance are sampled. The model is calibrated and validated with real lidar data. The application of the proposed lidar model for an autonomous emergency braking system is introduced.

关键词:Intelligent vehicles, lidar modeling, signal attenuation, simulation test, unwanted raw data