Joint Vehicle Trajectory and Cut-In Prediction on Highways using Output Constrained Neural Networks

Author:

Brosowsky Mathis1,Orschau Paul1,Dunkel Olaf2,Elspas Philip1,Slieter Daniel1,Zollner Marius3

Affiliation:

1. Dr. Ing. h.c. F. Porsche AG,Weissach,Germany,71287

2. KIT Karlsruhe Institute of Technology,Karlsruhe,Germany,76131

3. FZI Research Center for Information Technology,Karlsruhe,Germany,76131

Publisher

IEEE

Reference32 articles.

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3. Adam: A Method for Stochastic Optimization;kingma;Proceedings of the 3rd International Conference on Learning Representations,0

4. Multimodal Trajectory Predictions for Autonomous Driving using Deep Convolutional Networks

5. Deep Kinematic Models for Kinematically Feasible Vehicle Trajectory Predictions

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2. Predicut - A Machine Learning Model For Online Prediction of Cut-In Manoeuvre For Autonomous Vehicles;2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring);2023-06

3. Situation-aware communication topologies in heterogeneous platooning scenarios;Control Engineering Practice;2023-04

4. Cut-in maneuver detection with self-supervised contrastive video representation learning;Signal, Image and Video Processing;2023-03-01

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