A Hierarchical LiDAR Simulation Framework Incorporating Physical Attenuation Response in Autonomous Driving Scenarios

作者：Tengchao Huang, Shuang Song, Huosheng Hu, Yunlong Gao, Guifang Shao, Qingyuan Zhu · 发表于：IEEE Transactions on Intelligent Transportation Systems · 年份：2024 · DOI：10.1109/tits.2023.3340676 · 被引用次数：6 · 研究领域：Remote Sensing and LiDAR Applications、Advanced Optical Sensing Technologies、Computer Graphics and Visualization Techniques

This paper presents a hierarchical LiDAR simulation framework to address the challenges of accurately simulating LiDAR data in autonomous driving scenarios. The framework utilizes a homology mapping approach to integrate LiDAR responses hierarchically at three levels: the instantaneous power response, environmental optical channel response, and target reflection response of LiDAR. This allows for the dynamic coupling of LiDAR geometric and physical models with varying environmental parameters. By integrating an array of interactions intrinsic to the LiDAR system and its external environment, the proposed model can provide high-fidelity LiDAR point cloud simulations. The effectiveness of the simulated point clouds has been validated through extensive experiments using actual LiDAR data and detection algorithms trained on existing datasets. The experimental results show that the proposed method has the potential to improve the realism of LiDAR simulations and the accumulation of challenging perception data.