Simulators have irreplaceable importance for the research and development of autonomous driving. Besides saving resources, labor, and time, simulation is the only feasible way to reproduce many severe accident scenarios. Despite their widespread adoption across academia and industry, there is an absence in the evolutionary trajectory of simulators and critical discourse on their limitations. To bridge the gap in research, this paper conducts an in-depth review of simulators for autonomous driving. It delineates the three-decade development into three stages: specialized development period, gap period, and comprehensive development, from which it detects a trend of implementing comprehensive functionalities and open-source accessibility. Then it classifies the simulators by functions, identifying five categories: traffic flow simulator, vehicle dynamics simulator, scenario editor, sensory data generator, and driving strategy validator. Simulators that amalgamate diverse features are defined as comprehensive simulators. By investigating commercial and open-source simulators, this paper reveals that the critical issues faced by simulators primarily revolve around fidelity and efficiency concerns. This paper justifies that enhancing the realism of adverse weather simulation, automated map reconstruction, and interactive traffic participants will bolster credibility. Concurrently, headless simulation and multiple-speed simulation techniques will exploit the theoretic advantages. Moreover, this paper delves into potential solutions for the identified issues. It explores qualitative and quantitative evaluation metrics to assess the simulator's performance. This paper guides users to find suitable simulators efficiently and provides instructive suggestions for developers to improve simulator efficacy purposefully.

翻译：仿真器在自动驾驶研发中具有不可替代的重要性。除节省资源、人力和时间外，仿真是复现众多严重事故场景的唯一可行途径。尽管仿真器已在学术界和工业界得到广泛应用，但其发展轨迹的演进规律及自身局限性的批判性讨论仍存在空白。为填补这一研究缺口，本文对自动驾驶仿真器进行了深度综述。将三十年发展历程划分为三个时期：专业发展期、间隙期和全面发展期，揭示了向功能综合化与开源化演进的总趋势。随后依据功能维度对仿真器进行分类，识别出五类：交通流仿真器、车辆动力学仿真器、场景编辑器、感知数据生成器与驾驶策略验证器。融合多种功能的仿真器被定义为综合仿真器。通过考察商业与开源仿真器，本文揭示仿真器面临的核心问题主要围绕保真度与效率。论证表明，提升恶劣天气仿真逼真度、自动化地图重建与交互式交通参与者功能将增强可信度；同时，无头仿真与多倍速仿真技术可充分发挥理论优势。此外，本文深入探讨了已识别问题的潜在解决方案，并从定性与定量两个维度探索了评估仿真器性能的指标。本研究为使用者高效筛选适配仿真器提供指引，为开发者针对性提升仿真器效能提供建设性建议。