Simulation is an integral part in the process of developing autonomous vehicles and advantageous for training, validation, and verification of driving functions. Even though simulations come with a series of benefits compared to real-world experiments, various challenges still prevent virtual testing from entirely replacing physical test-drives. Our work provides an overview of these challenges with regard to different aspects and types of simulation and subsumes current trends to overcome them. We cover aspects around perception-, behavior- and content-realism as well as general hurdles in the domain of simulation. Among others, we observe a trend of data-driven, generative approaches and high-fidelity data synthesis to increasingly replace model-based simulation.

翻译：仿真在自动驾驶车辆的开发过程中是不可或缺的组成部分，对于驾驶功能的训练、验证与确认具有显著优势。尽管仿真相比真实世界实验具有诸多好处，但仍有多种挑战阻碍虚拟测试完全取代物理路试。本研究针对仿真不同层面与类型的挑战进行全面梳理，并总结了当前克服这些挑战的发展趋势。我们涵盖了感知真实性、行为真实性与内容真实性等多个维度，以及仿真领域的普遍性难题。研究发现，数据驱动的生成式方法与高保真数据合成正逐步取代传统基于模型的仿真，成为显著的发展趋势。