Optimizing Night Driving Simulations: A Comparative Study of Light Simulation Software

Abstract

Night driving simulations are essential tools for the development and validation of advanced automotive lighting systems. These simulations require not only photometrically accurate representations of light-material interactions but also real-time performance suitable for iterative design and driver-in-the-loop evaluations. This thesis presents a comparative study of three rendering platforms: Ansys AVxcelerate Headlamp, Synopsys LucidDrive, and Unity, to assess their capabilities in simulating nighttime driving environments with high visual fidelity.

The study benchmarks these tools across several dimensions, including rendering performance, photometric accuracy, and perceptual similarity, using standardized test scenes and real-world photometric profiles. A particular focus is placed on evaluating Unitys real-time ray tracing capabilities, enhanced by ReSTIR, against the more static and proprietary pipelines of AVxcelerate and LucidDrive. Experiments utilize standardized test scenes and automotive-grade models under controlled nighttime conditions, profiling performance via structural similarity of rendering results, GPU utilization, frame rate, and memory consumption.

The results underscore the limitations of commercial tools in handling dynamic lighting scenarios and complex BRDFs, while highlighting the flexibility and performance of open rendering frameworks. This work provides a reproducible benchmarking methodology and lays the foundation for future research on hybrid rendering strategies, perceptual validation models, and real-time simulation of intelligent headlight systems.