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仿真器在自动驾驶汽车（Autonomous Vehicle,AV）系统的研究、开发和验证中发挥着举足轻重的作用。本文系统地探讨了AV仿真器的国内外现状，并重点分析了其能力、面临的挑战和未来发展趋势。首先，梳理了AV仿真器的发展历程，阐述了国内外相关研究现状。接着，依据技术性指标、功能性指标、性能指标和商业性指标，对各类仿真器进行了全面评估，同时讨论了它们在不同研究和开发任务中的适用性。此外，深入剖析了AV仿真器所面临的挑战和限制，结合深度学习、人工智能等先进技术的发展，提出了针对性的解决策略。对于如何克服AV仿真器在复杂环境和多元场景下的局限性，提出了一系列具有前瞻性的解决方案。在此基础上，着重强调了未来研究的机遇和新兴趋势，这些将为下一代仿真器的发展奠定基础。最后，本综述旨在为研究人员、开发者及行业利益相关者提供有益的参考，协助他们选择最符合需求的工具，并激发自动驾驶领域未来的创新潜力。综述的内容有助于推动AV仿真器在自动驾驶研究和实际应用中发挥更大的作用，从而为人类出行带来更为安全、便捷和高效的体验。
Abstract：Simulators play a crucial role in the research, development, and validation of autonomous vehicle(AV) systems. This review systematically explores the current status of AV simulators both domestically and internationally, focusing on their capabilities, challenges, and future development trends. First, the development history of AV simulators is reviewed and the current state of related research at home and abroad is elaborated. second, a comprehensive evaluation of various simulators is conducted based on technical, functional, performance, and commercial indicators, while discussing their applicability in different research and development tasks. In addition, this review delves into the challenges and constraints faced by AV simulators. Combining the development of advanced technologies such as deep learning and artificial intelligence, targeted solutions are proposed. A series of forward-looking solutions are presented to overcome the limitations of AV simulators in complex environments and diverse scenarios. Consequently, this review emphasizes the opportunities and emerging trends in future research, which will lay the foundation for the development of the next generation of simulators. Finally, this review aims to provide valuable guidance for researchers, developers,and industry stakeholders, helping them choose the tools that best suit their needs and stimulate the innovation potential of the autonomous driving field. The content of this review contributes to the promotion of AV simulators in autonomous driving research and practical applications, thereby providing a safer, more convenient, and efficient travel experience for humanity.
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基本信息:
DOI：10.19961/j.cnki.1672-4747.2023.04.007
中图分类号:U463.6
引用信息:
[1]张坤鹏,常成,王世璞等.自动驾驶汽车仿真器综述:能力、挑战和发展方向[J].交通运输工程与信息学报,2024,22(01):1-24.DOI:10.19961/j.cnki.1672-4747.2023.04.007.
基金信息:
国家重点研发计划课题:基于车-云-场协同的自动驾驶效能在线加速测评（2021YFB2501200）