Articles | Volume 16, issue 1
https://doi.org/10.5194/ms-16-87-2025
© Author(s) 2025. This work is distributed under the Creative Commons Attribution 4.0 License.
Research article
| 
06 Feb 2025
Research article |
| 06 Feb 2025
| 06 Feb 2025
Interactive trajectory prediction for autonomous driving based on Transformer
Related authors
Mech. Sci., 16, 877–886, 2025
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Cited articles
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Bhat, M., Francis, J., and Oh, J.: Trajformer: Trajectory Prediction with Local Self-Attentive Contexts for Autonomous Driving, arXiv [preprint], https://doi.org/10.48550/arXiv.2011.14910, 30 November 2020.
Chang, M. F., Lambert, J., Sangkloy, P., Singh, J., Bak, S., Hartnett, A., Wang, D., Carr, P., Lucey, S., and Ramanan, D.: Argoverse: 3D Tracking and Forecasting With Rich Maps, arXiv [preprint], https://doi.org/10.48550/arXiv.1911.02620, 6 November 2019.
Cui, Z., Henrickson, K., Ke, R., and Wang, Y.: Traffic graph convolutional recurrent neural network: A deep learning framework for network-scale traffic learning and forecasting, IEEE T. Intell. Transp., 21, 4883–4894, https://doi.org/10.1109/TITS.2019.2950416, 2020.
Dai, S., Li, L., and Li, Z.: Modeling vehicle interactions via modified LSTM models for trajectory prediction, IEEE Access, 7, 38287–38296, https://doi.org/10.1109/ACCESS.2019.2907000, 2019.
