基于模型规划与控制的计时赛超越人类赛车手
Outracing Human Racers with Model-based Planning and Control for Time-trial Racing
AI总结：
本研究利用高保真模拟器GTS，通过改进基于模型的离线轨迹规划与MPC在线跟踪控制框架，使自动驾驶赛车圈速达到人类专家前0.95%水平，并通过消融实验验证了各模块的必要性。
摘要：
近年来，自动驾驶赛车已成为自动驾驶领域的一个热门子课题。自动驾驶赛车研究的目标是开发软件，使车辆在操控极限下运行，并达到人类水平的赛车表现。在本研究中，我们探讨如何利用高保真赛车模拟器Gran Turismo Sport (GTS)，通过基于模型的规划与控制方法来接近人类专家级的赛车表现。GTS为自动驾驶赛车研究提供了独特的机会，因为许多高水平人类玩家的赛车记录可以作为专家示范。通过将自动驾驶赛车软件的表现与人类专家进行对比，我们更好地理解了现有软件的性能差距，并以有原则的方式探索了新方法。具体而言，我们重点关注常用的基于模型的赛车框架，该框架由离线轨迹规划器和基于模型预测控制(MPC)的在线跟踪控制器组成。我们从车辆模型、规划算法和控制器设计三个视角深入研究了设计挑战，并提出了新颖的解决方案，以改进基线方法，使其达到人类专家级的表现。我们表明，所提出的控制框架在GTS的人类专家玩家中能够实现前0.95%的圈速。此外，我们进行了全面的消融研究，以验证所提出模块的必要性，并指出了达到人类最佳表现水平的潜在未来方向。
英文摘要：
Autonomous racing has become a popular sub-topic of autonomous driving in recent years. The goal of autonomous racing research is to develop software to control the vehicle at its limit of handling and achieve human-level racing performance. In this work, we investigate how to approach human expert-level racing performance with model-based planning and control methods using the high-fidelity racing simulator Gran Turismo Sport (GTS). GTS enables a unique opportunity for autonomous racing research, as many recordings of racing from highly skilled human players can served as expert emonstrations. By comparing the performance of the autonomous racing software with human experts, we better understand the performance gap of existing software and explore new methodologies in a principled manner. In particular, we focus on the commonly adopted model-based racing framework, consisting of an offline trajectory planner and an online Model Predictive Control-based (MPC) tracking controller. We thoroughly investigate the design challenges from three perspective, namely vehicle model, planning algorithm, and controller design, and propose novel solutions to improve the baseline approach toward human expert-level performance. We showed that the proposed control framework can achieve top 0.95% lap time among human-expert players in GTS. Furthermore, we conducted comprehensive ablation studies to validate the necessity of proposed modules, and pointed out potential future directions to reach human-best performance.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
