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：仿真是自动驾驶汽车开发过程中的关键环节，在驾驶功能的训练、验证和确认方面具有显著优势。尽管仿真相比真实世界实验具有一系列优点，但虚拟测试仍面临诸多挑战，无法完全替代物理实测。本研究从仿真的不同层面和类型出发，系统梳理了这些挑战，并总结了当前应对这些挑战的发展趋势。我们重点探讨了感知真实性、行为真实性和内容真实性，以及仿真领域的普遍难点。观察发现，数据驱动的生成式方法与高保真数据合成正逐步取代基于模型的仿真，成为主要发展趋势。