A computer-implemented method for generating synthetic sensor data having superimposed distance and intensity information (11, 12) from an environment detection sensor, in particular a LiDAR sensor, of a vehicle, comprising the steps: providing a hierarchical variational autoencoder (HVAE), which has a first hierarchy level, a second hierarchy level and a third hierarchy level or is configured to communicate with the third hierarchy level of an external variational autoencoder; receiving a first data set, having distance information, of sensor data, in particular synthetically generated and/or actually detected sensor data (SSD, RSD), of the environment detection sensor of the vehicle by a variational autoencoder of the first hierarchical level, which associates global features of the first data set of sensor data with a first codebook vector, where the global features represent objects contained in the sensor data that are recognized as such; receiving (S 3) the first data set (DS 1) sensor data of the environment detection sensor of the vehicle by a variational autoencoder (VAE 2) of the second hierarchical level (E 2) which associates local features of the first data set (DS 1) of sensor data with a second codebook vector (CBV 2), where the local features represent fine features of the objects contained in the sensor data; conditioning a first feature vector encoded by the variational autoencoder of the first hierarchical level and a second feature vector encoded by the variational autoencoder of the second hierarchical level with a second dataset comprising distance and intensity information (I1, 12) of sensor data of the environment detection sensor of the vehicle; merging the conditioned first feature vector and the conditioned second feature vector into a resulting third feature vector; and Decoding (S 6) the resulting third feature vector (MV 3) to generate a third data set (DS 3) of synthetic sensor data of the environment detection sensor of the vehicle having superimposed distance and intensity information (11, I 2). providing a hierarchical variational autoencoder (HVAE), which has a first hierarchy level, a second hierarchy level and a third hierarchy level or is configured to communicate with the third hierarchy level of an external variational autoencoder; receiving a first data set, having distance information, of sensor data, in particular synthetically generated and/or actually detected sensor data (SSD, RSD), of the environment detection sensor of the vehicle by a variational autoencoder of the first hierarchical level, which associates global features of the first data set of sensor data with a first codebook vector, where the global features represent objects contained in the sensor data that are recognized as such; receiving (S 3) the first data set (DS 1) sensor data of the environment detection sensor of the vehicle by a variational autoencoder (VAE 2) of the second hierarchical level (E 2) which associates local features of the first data set (DS 1) of sensor data with a second codebook vector (CBV 2), where the local features represent fine features of the objects contained in the sensor data; conditioning a first feature vector encoded by the variational autoencoder of the first hierarchical level and a second feature vector encoded by the variational autoencoder of the second hierarchical level with a second dataset comprising distance and intensity information (I1, 12) of sensor data of the environment detection sensor of the vehicle; merging the conditioned first feature vector and the conditioned second feature vector into a resulting third feature vector; and Decoding (S 6) the resulting third feature vector (MV 3) to generate a third data set (DS 3) of synthetic sensor data of the environment detection sensor of the vehicle having superimposed distance and intensity information (11, I 2).