As one of the important signs of the third wave of artificial intelligence, wheeled robots not only inherit knowledge but also learn independently, which brings about to learnable wheeled robots that use a driving brain to achieve data-driven control and learning. Presently, most existing technologies for self-driving vehicles can learn positively from the benchmark drivers to guarantee safe driving. However, in many unpredicted situations, such as rollover, human drivers often cause the behavior of irrational subconscious on account of human emotions like panic. In this paper, we propose a learnable wheeled robot using the driving brain by taking the rollover as an example, which is the most serious and dangerous situation in dynamic vehicle operations. Then, based on the analysis of rollover accidents, we utilize the driving brain reversely and conduct negative learning, materializing, and condensing the group intelligence of accident experts, to solve the problem of the lack of individual intelligence in emergencies and further promote real-time response to other dangerous conditions, such as puncture for self-driving vehicles.

作为第三次人工智能浪潮的重要标志之一，轮式机器人不仅继承知识，而且能够独立学习，这带来了可学习的轮式机器人，它们利用驱动大脑来实现数据驱动的控制和学习。目前，大多数用于自动驾驶车辆的现有技术可以向基准驾驶员积极学习，以确保安全驾驶。但是，在许多不可预测的情况下，例如翻车，人类驾驶员经常由于诸如恐慌之类的人类情绪而导致非理性的潜意识行为。本文以侧翻为例，提出了一种利用驾驶大脑的可学习轮式机器人，这是动态车辆操作中最严重，最危险的情况。然后，基于对翻车事故的分析，