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Found 3 papers, 3 papers with code
A Novel Deep Neural Network for Trajectory Prediction in Automated Vehicles Using Velocity Vector Field
Anticipating the motion of other road users is crucial for automated driving systems (ADS), as it enables safe and informed downstream decision-making and motion planning.
Trajectory Prediction with Observations of Variable-Length for Motion Planning in Highway Merging scenarios
In addition, we study the impact of the proposed prediction approach on motion planning and control tasks using extensive merging scenarios from the exiD dataset.
Multimodal Manoeuvre and Trajectory Prediction for Automated Driving on Highways Using Transformer Networks
Due to the uncertain future behaviour of vehicles, multiple future behaviour modes are often plausible for a vehicle in a given driving scene.
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