Man-machine sharing control regionalization decision-making method based on Gaussian hidden Markov model

The invention discloses a man-machine sharing control regionalization decision-making method based on a Gaussian hidden Markov model. The method comprises the following steps: step 1, information acquisition; step 2, information processing; step 3, grade judgment; step 4, preliminary distribution; step 5, final distribution; step 6, updating in real time; in the first step, real-time driving information of a driver and real-time driving information of an auxiliary driving system are collected from a control panel, sensing equipment and an auxiliary driving system module through an information collection module; according to the method, different coping capacities and sensitivities of the driver to environmental risks from different directions are comprehensively considered, and a double-chain structure of the hidden Markov model is fully utilized, so that the specificity, the relative driving ability, the vehicle environmental risk degree, the area where the vehicle is located and the like of the driver are c