Driving control method and system based on personalized federal contrast learning

The invention relates to an intelligent decision making technology, and discloses a driving control method based on personalized federal contrast learning, which comprises the following steps: a client obtains driving data, and performs feature extraction on the driving data by using a multi-modal processor to obtain multi-modal driving feature data; performing data processing on the multi-modal driving characteristic data to obtain multi-modal driving comparison characteristic data; the central server carries out training on the comparative learning driving prediction model to obtain a target driving prediction model, the central server carries out parameter aggregation on the global neuron parameters to obtain fusion parameters and distributes the fusion parameters to a plurality of clients, and the clients carry out personalized parameter optimization on the target driving prediction model by using the fusion parameters; and the client receives the real-time driving data of the user to carry out driving pr