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：仿真是自动驾驶车辆开发过程中的重要组成部分，对于驾驶功能的训练、验证和确认具有显著优势。尽管仿真相比真实世界实验具有诸多好处，但虚拟测试仍面临诸多挑战，无法完全取代实车路试。本文围绕仿真的不同维度和类型，对这些挑战进行了全面概述，并总结了当前克服这些挑战的趋势。我们涵盖了感知真实性、行为真实性和内容真实性等相关方面，以及仿真领域的通用性难题。特别指出，我们观察到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。