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A Seed Based Method for Dictionary Translation.

, , and . ISMIS, volume 8502 of Lecture Notes in Computer Science, page 415-424. Springer, (2014)

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The inD Dataset: A Drone Dataset of Naturalistic Road User Trajectories at German Intersections., , , , , and . IV, page 1929-1934. IEEE, (2020)The rounD Dataset: A Drone Dataset of Road User Trajectories at Roundabouts in Germany., , , , and . ITSC, page 1-6. IEEE, (2020)BézierVAE: Improved Trajectory Modeling using Variational Autoencoders for the Safety Validation of Highly Automated Vehicles., , , and . ITSC, page 3788-3795. IEEE, (2019)A Seed Based Method for Dictionary Translation., , and . ISMIS, volume 8502 of Lecture Notes in Computer Science, page 415-424. Springer, (2014)Decoupled cooperative trajectory optimization for connected highly automated vehicles at urban intersections., , and . Intelligent Vehicles Symposium, page 741-746. IEEE, (2016)Data-Driven Maneuver Modeling using Generative Adversarial Networks and Variational Autoencoders for Safety Validation of Highly Automated Vehicles., , , and . ITSC, page 2383-2390. IEEE, (2018)Discrete dynamic optimization in automated driving systems to improve energy efficiency in cooperative networks., , and . Intelligent Vehicles Symposium, page 370-375. IEEE, (2014)Comparison of Camera-Equipped Drones and Infrastructure Sensors for Creating Trajectory Datasets of Road Users., , and . VEHITS, page 161-170. SCITEPRESS, (2021)The exiD Dataset: A Real-World Trajectory Dataset of Highly Interactive Highway Scenarios in Germany., , , , , and . IV, page 958-964. IEEE, (2022)The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems., , , and . ITSC, page 2118-2125. IEEE, (2018)