Online federated learning method of traffic flow prediction model

The invention provides an online federated learning method for a traffic flow prediction model of a traffic control system, and the method comprises the steps: D1, carrying out the updating of a preset number of times of the traffic flow prediction model of each road side unit, each updating comprises the following steps: D11, acquiring a to-be-predicted traffic flow sequence of the current road side unit as a code input of the traffic flow prediction model so as to obtain a code hiding state of the current road side unit; d12, the server calculates the spatial relation between the current road side unit and other road side units and updates the code hiding state of the current road side unit, and the updated code hiding state serves as decoding input of the traffic flow prediction model of the current road side unit to obtain predicted traffic flow; d13, updating the parameters of the traffic flow prediction model of the current road side unit according to the loss between the actual traffic flow and the pre