Next track point prediction using a flexible strategy of subgraph learning on road networks-Reference-Cited by-同舟云学术

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Next track point prediction using a flexible strategy of subgraph learning on road networks

Published:2024-05-27 Issue: Volume: Page:1-26
ISSN:1365-8816
Container-title:International Journal of Geographical Information Science
language:en
Short-container-title:International Journal of Geographical Information Science

Author:

Zhang Yifan¹^ORCID,Yu Wenhao¹²,Zhu Di³^ORCID

Affiliation:

1. School of Geography and Information Engineering, China University of Geosciences, Wuhan, China

2. National Engineering Research Center for Geographic Information System, China University of Geosciences, Wuhan, China

3. Department of Geography, Environment and Society, University of Minnesota, Twin Cities, MN, USA

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities, China University of Geosciences

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/13658816.2024.2358527

Reference77 articles.

1. Altch, F., and Fortelle, A., 2017. An lstm network for highway trajectory prediction. In: 2017 IEEE 20th international conference on intelligent transportation systems (ITSC). IEEE, 353–359.

2. Ba, J.L., Kiros, J.R., and Hinton, G.E., 2016. Layer normalization. arXiv preprint arXiv:1607.06450.

3. Bacciu, D., et al., 2023. Safety and robustness for deep neural networks: An automotive use case. In: J. Guiochet, S. Tonetta, E. Schoitsch, M. Roy and F. Bitsch, eds. Computer Safety, Reliability, and Security. SAFECOMP 2023 Workshops, Cham: Springer Nature Switzerland, 95–107.

4. An experience in using machine learning for short-term predictions in smart transportation systems;Bacciu D.;Journal of Logical and Algebraic Methods in Programming,2017

5. Chang, S.P., et al., 2016. Extracting driving behavior: Global metric localization from dashcam videos in the wild. In: G. Hua and H. J’egou, eds. Computer vision – ECCV 2016 workshops. Cham: Springer International Publishing, 136–148.

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