Real-Time LiDAR Sensor Modeling: Intensity Modeling and Evaluation for Autonomous Vehicle Simulation

Abstract

Realistic LiDAR simulation is important for the development and validation of autonomous driving systems, but accurately reproducing LiDAR intensity remains challenging. Unlike point geometry, intensity depends on range, incidence angle, surface reflectivity, sensor-specific processing, and environmental effects. In addition, evaluating simulated intensity against real-world data is difficult because exact pointwise alignment between real and simulated point clouds is rarely achievable in a digital twin environment. This thesis investigates LiDAR intensity simulation in a CARLA-based digital twin of the AstaZero proving ground, developed in connection with Volvo Autonomous Solutions. Real-world LiDAR reference data are reconstructed from MCAP recordings and used to evaluate the simulated intensity output. A physically motivated intensity model is introduced for the simulated LiDAR, incorporating the main factors that affect return strength, including range, incidence angle, and material reflectivity. However, because the target LiDAR sensor outputs a vendor-specific value affected by an inaccessible, proprietary internal processing pipeline, a direct analytical sensor model is unattainable. Hence, the framework complements this physical formulation to a final calibrated reflectivity simulation model through empirical distribution mapping. The resulting model serves as a practical, real-time approximation of calibrated reflectivity behavior rather than a complete reproduction of the internal sensor-processing pipeline. To evaluate simulated LiDAR intensity, this thesis combines conventional histogrambased metrics with a novel geometry tolerant evaluation method proposed in this work. Wasserstein distance and Jensen–Shannon distance are used as baseline measures of global intensity distribution agreement. The proposed spherical harmonic based method represents each LiDAR frame as an angular intensity function on the sphere and compares frames using a weighted distance between their degree-wise spherical harmonic energy descriptors. This method captures coarse angular intensity structure in a rotation invariant manner without requiring exact pointwise correspondence. The results show that the proposed intensity model improves the similarity between simulated and real-world reference intensity distributions. The proposed evaluation method also provides a more informative comparison than traditional distributionbased metrics by preserving directional intensity structure when local geometric mismatch is present.