A method for predicting a vehicle trajectory, comprising: obtaining vectorized features of a plurality of target vehicles based on perceived information of an autonomous vehicle; and obtaining a trajectory prediction result based on vectorized features of each of the target vehicles, to obtain a plurality of trajectory prediction results of the plurality of target vehicles; wherein the plurality of target vehicles comprise the autonomous vehicle and a plurality of first surrounding vehicles, wherein the plurality of first surrounding vehicles being vehicles in a surrounding environment of the autonomous vehicle that are selected according to a preset first rule; and the perceived information is obtained based on data acquired by a sensor of the autonomous vehicle; the obtaining vectorized features of a plurality of target vehicles further comprises: based on the perceived information of the autonomous vehicle, obtaining self-vehicle trajectory vectorized features, surrounding trajectory vectorized features, and road network vectorized features of each of the target vehicles; wherein the surrounding trajectory vectorized features are trajectory vectorized features of a plurality of second surrounding vehicles of the target vehicle, the plurality of second surrounding vehicles being vehicles in a surrounding environment of the target vehicle that are selected according to a preset second rule; the obtaining a trajectory prediction result based on vectorized features of each of the target vehicles further comprises: for each of the target vehicles, obtaining encoded features of the target vehicle based on the self-vehicle trajectory vectorized features, the surrounding trajectory vectorized features, and the road network vectorized features of the target vehicle; and obtaining the trajectory prediction result of the target vehicle based on the encoded features of the target vehicle. obtaining vectorized features of a plurality of target vehicles based on perceived information of an autonomous vehicle; and obtaining a trajectory prediction result based on vectorized features of each of the target vehicles, to obtain a plurality of trajectory prediction results of the plurality of target vehicles; wherein the plurality of target vehicles comprise the autonomous vehicle and a plurality of first surrounding vehicles, wherein the plurality of first surrounding vehicles being vehicles in a surrounding environment of the autonomous vehicle that are selected according to a preset first rule; and the perceived information is obtained based on data acquired by a sensor of the autonomous vehicle; the obtaining vectorized features of a plurality of target vehicles further comprises: based on the perceived information of the autonomous vehicle, obtaining self-vehicle trajectory vectorized features, surrounding trajectory vectorized features, and road network vectorized features of each of the target vehicles; wherein the surrounding trajectory vectorized features are trajectory vectorized features of a plurality of second surrounding vehicles of the target vehicle, the plurality of second surrounding vehicles being vehicles in a surrounding environment of the target vehicle that are selected according to a preset second rule; the obtaining a trajectory prediction result based on vectorized features of each of the target vehicles further comprises: for each of the target vehicles, obtaining encoded features of the target vehicle based on the self-vehicle trajectory vectorized features, the surrounding trajectory vectorized features, and the road network vectorized features of the target vehicle; and obtaining the trajectory prediction result of the target vehicle based on the encoded features of the target vehicle. based on the perceived information of the autonomous vehicle, obtaining self-vehicle trajectory vectorized features, surrounding trajectory vectorized features, and road network vectorized features of each of the target vehicles; wherein the surrounding trajectory vectorized features are trajectory vectorized features of a plurality of second surrounding vehicles of the target vehicle, the plurality of second surrounding vehicles being vehicles in a surrounding environment of the target vehicle that are selected according to a preset second rule; the obtaining a trajectory prediction result based on vectorized features of each of the target vehicles further comprises: for each of the target vehicles, obtaining encoded features of the target vehicle based on the self-vehicle trajectory vectorized features, the surrounding trajectory vectorized features, and the road network vectorized features of the target vehicle; and obtaining the trajectory prediction result of the target vehicle based on the encoded features of the target vehicle. for each of the target vehicles, obtaining encoded features of the target vehicle based on the self-vehicle trajectory vectorized features, the surrounding trajectory vectorized features, and the road network vectorized features of the target vehicle; and obtaining the trajectory prediction result of the target vehicle based on the encoded features of the target vehicle.