Where Is the Next Path? A Deep Learning Approach to Path Prediction Without Prior Road Networks-Reference-Cited by-同舟云学术

Where Is the Next Path? A Deep Learning Approach to Path Prediction Without Prior Road Networks

Published:2021 Issue: Volume: Page:219-235
ISSN:1867-8211
Container-title:Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
language:
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Author:

Wang Guiling^ORCID,Zhang Mengmeng,Gao Jing,Han Yanbo

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-67540-0_13

Reference21 articles.

1. Altche, F., de La Fortelle, A.: An LSTM network for highway trajectory prediction. In: 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC), pp. 353–359 (2017). https://doi.org/10.1109/ITSC.2017.8317913

2. Dalsnes, B.R., Hexeberg, S., Flåten, A.L., Eriksen, B.O.H., Brekke, E.F.: The neighbor course distribution method with Gaussian mixture models for AIS-based vessel trajectory prediction, pp. 580–5877 (2018)

3. Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence);Y Endo,2017

4. Georgiou, H.V., et al.: Moving objects analytics: Survey on future location & trajectory prediction methods. CoRR abs/1807.04639 (2018). http://arxiv.org/abs/1807.04639

5. Guo, L., Ding, Z., Hu, Z., Chen, C.: Uncertain path prediction of moving objects on road networks. J. Comput. Res. Dev. 47, 104–112 (2010). (in Chinese)

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