Future vehicles: learnable wheeled robots

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 selfdriving 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.