The invention relates to the technical field of automatic driving, and discloses an end-to-end automatic driving
system based on electroencephalogram intention modeling and
machine mental reasoning, and the
system comprises an electroencephalogram
signal collection module which is used for collecting an electroencephalogram
signal of a driver in real time and carrying out the preprocessing of the electroencephalogram
signal; the electroencephalogram intention decoding module is used for extracting driving intention features and outputting structured intention vectors; the
machine mental reasoning module is used for fusing the intention vector, the vehicle state and the environment
perception information, deducing the
mental state of the driver and outputting a
mental state vector; and the end-to-end automatic driving control module is used for performing multi-
modal fusion on the intention vector, the
mental state vector, the environment
perception characteristics and the vehicle dynamic state to generate a continuous
vehicle control instruction. According to the method, the
neurocognitive activity of the driver can be converted into decision-making elements which can be understood and utilized by a
machine in real time, so that man-machine cognitive alignment and closed-loop cooperative control are realized.