The rising popularity of self-driving cars has led to the emergence of a new research field in the recent years: Autonomous racing. Researchers are developing software and hardware for high performance race vehicles which aim to operate autonomously on the edge of the vehicles limits: High speeds, high accelerations, low reaction times, highly uncertain, dynamic and adversarial environments. This paper represents the first holistic survey that covers the research in the field of autonomous racing. We focus on the field of autonomous racecars only and display the algorithms, methods and approaches that are used in the fields of perception, planning and control as well as end-to-end learning. Further, with an increasing number of autonomous racing competitions, researchers now have access to a range of high performance platforms to test and evaluate their autonomy algorithms. This survey presents a comprehensive overview of the current autonomous racing platforms emphasizing both the software-hardware co-evolution to the current stage. Finally, based on additional discussion with leading researchers in the field we conclude with a summary of open research challenges that will guide future researchers in this field.
翻译:自驾车越来越受欢迎,导致近年来出现了一个新的研究领域:自动赛车。研究人员正在为高性能种族车辆开发软件和硬件,目的是在车辆极限边缘自主运行:高速、高加速度、低反应时间、高度不确定、动态和对抗性环境。本文是第一次涵盖自主赛领域研究的全面调查。我们只关注自主赛车领域,并展示在视觉、规划和控制以及端到端学习等领域使用的算法、方法和办法。此外,随着自动赛跑比赛日益增多,研究人员现在可以使用一系列高性能平台测试和评价其自主算法。本调查全面概述了当前自主赛车平台,强调软件硬件的共同演进到当前阶段。最后,根据与该领域主要研究人员进行的额外讨论,我们最后总结了将指导该领域未来研究人员的公开研究挑战。