Using PINN based MPC for motion planning for SDC and LSTM for pedestrain's trajectory prediction as dynamic obstacles
-
Updated
Dec 29, 2022 - Jupyter Notebook
Using PINN based MPC for motion planning for SDC and LSTM for pedestrain's trajectory prediction as dynamic obstacles
We have compared 4 models- Vanilla LSTM, Social LSTM, OLSTM, and GRU to show their comparison for predicting non linear trajectories of pedestrians in different scenes. We demonstrate their performance on publically available datasets. We show how it is important to take into account the surroundings of the pedestrians to have a better accuracy.
We have compared 4 models- Vanilla LSTM, Social LSTM, OLSTM, and GRU to show their comparison for predicting non linear trajectories of pedestrians in different scenes. We demonstrate their performance on publically available datasets. We show how it is important to take into account the surroundings of the pedestrians to have a better accuracy
Add a description, image, and links to the olstm topic page so that developers can more easily learn about it.
To associate your repository with the olstm topic, visit your repo's landing page and select "manage topics."