面向自动驾驶仿真的虚拟LiDAR传感器建模

在自动驾驶仿真领域，虚拟传感器输出数据的精准度是仿真结果可靠性的重要保障。激光雷达（LiDAR）作为车辆环境感知的关键传感器，其采集的点云数据的准确性是实现车辆对三维环境理解的关键。但在虚拟环境中，通过3D渲染技术模拟的点云数据难以真实反映传感器在复杂工况下的变化规律。本文提出一种用于自动驾驶仿真的虚拟LiDAR传感器建模方法。该方法首先基于Unity 3D引擎构建LiDAR的几何测量模型。其次，结合真实传感器的衰变特性推导简化的LiDAR物理模型。最后，基于蒙特卡罗方法在随机模型上对仿真数据进行噪声模拟，从而实现高保真的LiDAR数据输出。所提出的方法可结合精细化的虚拟场景进行数据验证，实验结果表明：该方法能够有效地在虚拟环境下模拟LiDAR数据，从而应用于自动驾驶仿真算法验证过程。

Modeling of virtual LiDAR sensor for autonomous driving simulation

The accuracy of virtual sensor output data is crucial for ensuring the reliability of simulation results in the field of autonomous driving simulation. As a key sensor for vehicle environment perception, the accuracy of point cloud data collected by LiDAR is critical for achieving a comprehensive understanding of the three-dimensional environment. However, in the virtual environment, the simulated point cloud data generated using 3D rendering techniques often fail to accurately reflect the variations of the sensor under complex conditions. In this study, we propose a modeling method for virtual LiDAR sensor in autonomous driving simulation. Firstly, a geometric measurement model for LiDAR is constructed based on the Unity 3D engine. Subsequently, a simplified LiDAR physical model is derived by incorporating the decay characteristics of real sensors. Finally, a Monte Carlo-based noise simulation is performed on the stochastic model to achieve high-fidelity LiDAR data output. The proposed method is validated by combining it with finely detailed virtual scenarios. Experimental results demonstrate the effectiveness of the method in accurately simulating LiDAR data in virtual environments, thus facilitating the verification of autonomous driving simulation algorithms