The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Convolutional Social Pooling for Vehicle Trajectory Prediction
Open accessAbstract
Forecasting the motion of surrounding vehicles is a critical ability for an autonomous vehicle deployed in complex traffic. Motion of all vehicles in a scene is governed by the traffic context, i.e., the motion and relative spatial configuration of neighboring vehicles. In this paper we propose an LSTM encoder-decoder model that uses convolutional social pooling as an improvement to social pooling layers for robustly learning interdependencies in vehicle motion. Additionally, our model outputs a multi-modal predictive distribution over future trajectories based on maneuver classes. We evaluate our model using the publicly available NGSIM US-101 and I-80 datasets. Our results show improvement over the state of the art in terms of RMS values of prediction error and negative log-likelihoods of true future trajectories under the model's predictive distribution. We also present a qualitative analysis of the model's predicted distributions for various traffic scenarios.
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Cites
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Cited by
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Chang, M.-F., Lambert, J., Sangkloy, P., Singh, J., Bak, S., Hartnett, A., Wang, D., Carr, P., Lucey, S., Ramanan, D., et al. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00895 · Cited by 1,474
Multimodal Motion Prediction with Stacked Transformers
Liu, Y., Zhang, J., Fang, L., Jiang, Q., & Zhou, B. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr46437.2021.00749 · Cited by 474
Query-Centric Trajectory Prediction
Zhou, Z., Wang, J., Li, Y., & Huang, Y. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52729.2023.01713 · Cited by 333
Wu, X., Dong, J., Bao, W., Zou, B., Wang, L., & Wang, H. (2024) · IEEE Internet of Things Journal · doi:10.1109/jiot.2024.3417285 · Cited by 95
Spatially-Aware Graph Neural Networks for Relational Behavior Forecasting from Sensor Data
Casas, S., Gulino, C., Liao, R., & Urtasun, R. (2019) · arXiv · doi:10.48550/arxiv.1910.08233 · Cited by 44
Metadata
- Authors
- Deo, N., & Trivedi, M. M.
- Venue
- 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
- Publisher
- IEEE
- Published
- 2018-06
- Pages
- 1549-15498
- OpenAlex
- W2803332797
- Cited by
- 1,050
- References
- 19
- FWCI
- 72.78
- Type
- conference paper
- Language
- en
- Open access
- green
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