论文标题
针对专业人类赛车司机的自动赛车的软件堆栈基准测试
Benchmarking of a software stack for autonomous racing against a professional human race driver
论文作者
论文摘要
完全自治的公共道路车辆的方式需要逐步替换人类驾驶员，其最终目标是完全更换驾驶员。最终，驾驶软件必须能够处理自己发生的所有情况，甚至是紧急情况。这些特殊情况需要在处理范围内极端的制动和转向动作，以避免事故或减少其后果。普通的人类驾驶员未经训练来应对这种极端且很少发生的情况，因此常常没有这样做。但是，专业的赛车驾驶员经过培训，可以使用最大数量的轮胎部队驾驶车辆。这些能力对于开发自主驾驶软件具有很高的兴趣。在这里，我们将专业的赛车手和我们的软件堆栈与在赛车运动中建立的数据分析技术开发的软件堆栈。这项研究的目的是提出迹象，以进一步改善我们的软件的性能，并确定它仍然无法达到人类竞赛驱动力的绩效水平的领域。我们的结果用于扩展软件的功能，并将我们的发现纳入公共道路自动驾驶汽车的研究和开发中。
The way to full autonomy of public road vehicles requires the step-by-step replacement of the human driver, with the ultimate goal of replacing the driver completely. Eventually, the driving software has to be able to handle all situations that occur on its own, even emergency situations. These particular situations require extreme combined braking and steering actions at the limits of handling to avoid an accident or to diminish its consequences. An average human driver is not trained to handle such extreme and rarely occurring situations and therefore often fails to do so. However, professional race drivers are trained to drive a vehicle utilizing the maximum amount of possible tire forces. These abilities are of high interest for the development of autonomous driving software. Here, we compare a professional race driver and our software stack developed for autonomous racing with data analysis techniques established in motorsports. The goal of this research is to derive indications for further improvement of the performance of our software and to identify areas where it still fails to meet the performance level of the human race driver. Our results are used to extend our software's capabilities and also to incorporate our findings into the research and development of public road autonomous vehicles.
