… This requires using nondeterministic models for prediction. … prediction of traffic participants.
Instead of explicitly modeling dependencies between vehicles, we trim reachable occupancy …

… if the occupancy of the ego vehicle (ie the vehicle under consideration) intersects with the …
the prediction of the occupancy of each traffic participant. We guarantee that each occupancy …

… to predict the vehicles average occupancy on highways. For predictions, we have used
deep neural networks and have used fiveminutes interval vehicles average occupancy data as …

… occupancy area of a pedestrian for autonomous driving. To do this, a probabilistic prediction
… The occupancy prediction can be determined on the basis of this probability as a function of …

… prediction. To bridge this gap, we introduce the first method for collaborative 3D semantic
occupancy prediction. Particularly, it improves local 3D semantic occupancy predictions by …

… to predict road user occupancy through vehicle-specific probabilities of presence. Instead of
… another behavior prediction approach which tries to predict the most likely vehicle positions, …

… propose a new BEV fusion and occupancy prediction method via V2X communication. …
prediction results achieve high accuracy. 2) We compare the prediction method of single vehicle …

… vehicle trajectory prediction framework based on recurrent neural network. Basically, the
characteristic of the vehicle’s … by various latent factors including road structure, traffic rules, and …

… the 900 test scenarios and the experiments using real vehicles prove that the … predicting a
reliable estimate of the Predicted-Occupancy Grid. An application of the Predicted-Occupancy …

… Comparison of our occupancy model MO with two versions of our trajectory model MT
trained with and without Gaussian uncertainties on occupancy prediction for vehicles. While MO …