UPTP Vehicle Trajectory Prediction Based on User Preference Under Complexity Environment-Reference-Cited by-同舟云学术

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UPTP Vehicle Trajectory Prediction Based on User Preference Under Complexity Environment

Published:2017-09-18 Issue:3 Volume:97 Page:4651-4665
ISSN:0929-6212
Container-title:Wireless Personal Communications
language:en
Short-container-title:Wireless Pers Commun

Author:

Xia Zhuoqun,Hu Zhenzhen,Luo Junpeng

Funder

National Natural Science Foundation of China Grant

the Hunan Province Natural Science Foundation of China Grant

the Hunan Province Transportation Department Technological Progress and Innovation Fund of China Grant

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Computer Science Applications

Link

http://link.springer.com/article/10.1007/s11277-017-4743-9/fulltext.html

Reference29 articles.

1. Yoon, H., & Shahabi, C. (2008). Rubst time-referenced segmentation of moving object trajectories. In Eighth IEEE International Conference on Data Miniing (pp. 1121–1126). doi: 10.1109/ICDM.2008.133 .

2. Wang, Z.-C., Lu, M., & Yuan, X.-R. (2013). Visual traffic jam analysis based on trajectory data. IEEE Transaction on Visualization and Computer Graphics, 19(12), 2159–2168.

3. Andrienko, G., & Andrienko, N. (2008). Spatio-temporal aggregation for visual analysis of movements. In Proceedings of IEEE VAST (Vol. 1, pp. 51–58).

4. Deb, S., Jia, C., & Fong, S. (2013). On-road direction trajectory prediction by junction-based pattern mining from GPS data. International Conference on Machine Intelligent and Research Advancement (pp. 253–257). doi: 10.1109/ICMIRA.2013.54 .

5. Ying, J. J. C., Lee, W. C., Weng, T. C., & Tseng, V. S. (2011). Semantic trajectory mining for location prediction. ACM SIGSPATIAL GIS11 (pp. 34–43). November 1–4, 2011, Chicago, IL, USA. doi: 10.1145/2093973.2093980 .

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