强光环境智能汽车相机功能仿真测试

doi:10.19562/j.chinasae.qcgc.2025.12.010

Abstract

Abstract:

The strong light environment generated by vehicle high beams， sunlight， and other light sources can significantly affect the camera functions of intelligent vehicle. Establishing accurate and controllable testing methods for such strong light environment is crucial for improving the environmental adaptability of intelligent vehicles. However， real-world testing on roads or closed fields under strong light conditions faces challenges such as high testing cost， long cycles， and the difficulty of precisely replicating controlled scenarios. In this paper a simulation test method for intelligent vehicle camera function under strong light environment is proposed. It uses a geometric-physical fusion simulation model to simulate image responses in strong light environment， and employs strong light simulation images to test camera functions. Firstly， a geometric model of strong light environment imaging is constructed to determine the area affected by strong light. Secondly， the camera imaging physical model and the physical characteristics of strong light sources are used to determine the pixel intensity corresponding to the strong light effect. Based on the strong light impact region and pixel values， images collected from real vehicles under normal light conditions are combined to generate strong light simulation images. Finally， real-world test results under strong light environment are taken as ground truth， and the testing results for the same camera functions in strong light environment are compared with traditional simulation software， large model methods， and the method proposed in this paper. The experimental results show that the proposed method can improve the performance of strong light environment simulation testing. Compared to traditional simulation software and large model methods， it achieves more effective and accurate camera function testing under strong light conditions. Additionally， it offers the advantages of lower testing cost， higher efficiency， and precise controllability of simulation parameters， as compared to physical scene testing.

Key words: intelligent vehicle, camera function testing, strong light environment, geometric-physical fusion simulation model

Yinzi Huang,Bing Zhu,Jian Zhao,Peixing Zhang,Zhitong Gao,Jiayi Han,Xinwei Fan. Simulation Test Method of Intelligent Vehicle Camera Function in Strong Light Environment[J].Automotive Engineering, 2025, 47(12): 2378-2386.

Figures/Tables 20

物理特性参数	车辆远光灯	日光
$d Φ$	40 W	1 000 W/m³ $× d A$
$θ$ /（°）	10	45
$d w$ / $s r$	$5.48 × 10 - 4$	$9 × 10 - 3$
$d A$ / $m 2$	$1.26 × 10 - 5$	$1.26 × 10 - 5$
$L /$ （ $W ? m - 2 ? s r - 1$ ）	$5.9 × 109$	$1.6 × 106$

相机物理参数	数值
$D c$	4 mm
$f$	6.0 mm
$T$	20 ms
$g'$	1
$U$	0 V
$η$	12.89 mV
$S a t$	16 383
$B l a$	0
$g a i n R$	2.433 594
$g a i n B$	1.347 656

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Simulation Test Method of Intelligent Vehicle Camera Function in Strong Light Environment

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