A method for predicting a road occupancy map of a target moving object, comprising: obtaining target status information of the target moving object at a current moment, wherein the target moving object is any one of at least one moving object around a vehicle, and the target status information comprises a lateral acceleration of the target moving object; performing discretization processing on the target status information to obtain a parameter sequence, wherein the parameter sequence comprises a plurality of discrete values; predicting, based on a target discrete value and the target status information, a target movement track corresponding to the target discrete value, wherein the target discrete value is any one of the plurality of discrete values comprised in the parameter sequence, and the target movement track comprises a plurality of target track points; determining, based on the target movement track, a road region in which the target moving object travels at a subsequent moment, wherein the subsequent moment is a next moment of the current moment; characterized in that the determining comprises: obtaining a target probability value corresponding to each target track point comprised in the target movement track, wherein the target probability value corresponding to the target track point is equal to the target probability value corresponding to the target discrete value; obtaining a target track point that satisfies a regression fitting condition, wherein the target track point that satisfies the regression fitting condition is a track point corresponding to a target probability value greater than or equal to a preset probability value; and performing regression fitting based on the target track point that satisfies the regression fitting condition, to obtain the road region in which the target moving object travels at the subsequent moment. obtaining target status information of the target moving object at a current moment, wherein the target moving object is any one of at least one moving object around a vehicle, and the target status information comprises a lateral acceleration of the target moving object; performing discretization processing on the target status information to obtain a parameter sequence, wherein the parameter sequence comprises a plurality of discrete values; predicting, based on a target discrete value and the target status information, a target movement track corresponding to the target discrete value, wherein the target discrete value is any one of the plurality of discrete values comprised in the parameter sequence, and the target movement track comprises a plurality of target track points; determining, based on the target movement track, a road region in which the target moving object travels at a subsequent moment, wherein the subsequent moment is a next moment of the current moment; characterized in that the determining comprises: obtaining a target probability value corresponding to each target track point comprised in the target movement track, wherein the target probability value corresponding to the target track point is equal to the target probability value corresponding to the target discrete value; obtaining a target track point that satisfies a regression fitting condition, wherein the target track point that satisfies the regression fitting condition is a track point corresponding to a target probability value greater than or equal to a preset probability value; and performing regression fitting based on the target track point that satisfies the regression fitting condition, to obtain the road region in which the target moving object travels at the subsequent moment. obtaining a target probability value corresponding to each target track point comprised in the target movement track, wherein the target probability value corresponding to the target track point is equal to the target probability value corresponding to the target discrete value; obtaining a target track point that satisfies a regression fitting condition, wherein the target track point that satisfies the regression fitting condition is a track point corresponding to a target probability value greater than or equal to a preset probability value; and performing regression fitting based on the target track point that satisfies the regression fitting condition, to obtain the road region in which the target moving object travels at the subsequent moment.