TraPlan: An effective three-in-one trajectory-prediction model in transportation networks

IEEE Transactions on Intelligent Transportation Systems

Volumn 16, Issue 3, 2015, Pages 1188-1198

  Qiao, Shaojie ^a   Han, Nan ^a   Zhu, William ^b   Gutierrez, Louis Alberto ^c  

^a SOUTHWEST JIAOTONG UNIVERSITY   (China)

^b MINNAN NORMAL UNIVERSITY   (China)

^c Rensselaer Polytechnic Institute   (United States)

Author keywords

Index; moving objects; region of interests; trajectory prediction (TP); transportation networks

Indexed keywords

DECISION TREES; FORECASTING; IMAGE SEGMENTATION; INDEXING (OF INFORMATION); TRAJECTORIES; TRANSPORTATION;

INDEX; MOVING OBJECTS; REGION OF INTEREST; TRAJECTORY PREDICTION; TRANSPORTATION NETWORK;

TREES (MATHEMATICS);

EID: 85027952981     PISSN: 15249050     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITS.2014.2353302     Document Type: Article

References (25)

1. C. Zaniolo, "Event-oriented data models and temporal queries in transaction-time databases," in Proc. 16th Int. Symp. Temporal Represent. Reasoning, Washington, D.C., USA, 2009, pp. 47-53, IEEE Computer Society.
2. J. Zhang et al., "Data-driven intelligent transportation systems: A survey," IEEE Trans. Intell. Transp. Syst., vol. 12, no. 4, pp. 1624-1639, Dec. 2011.
3. Y. Zheng and X. Zhou, Computing With Spatial Trajectories. Berlin, Germany: Springer-Verlag,, 2011.
4. C. Song, Z. Qu, N. Blumm, and A.-L. Barabsi, "Limits of predictability in human mobility," Science, vol. 327, no. 5968, pp. 1018-1021, Feb. 2010.
5. F. Y. Wang, "Parallel control and management for intelligent transportation systems: Concepts, architectures, applications," IEEE Trans. Intell. Transp. Syst., vol. 11, no. 3, pp. 630-638, Sep. 2010.
6. J. Yang and M. Hu, "TrajPattern: Mining sequential patterns from imprecise trajectories of mobile objects," in Proc. 10th Int. Conf. Adv. Database Technol., Berlin, Germany, 2006, pp. 664-681, Springer.
7. M. Morzy, "Mining frequent trajectories of moving objects for location prediction," in Proc. 5th Int. Conf. Mach. Learn. Data Mining Pattern Recog., Berlin, Germany, 2007, pp. 667-680, Springer.
8. S. Qiao, T. Li, J. Peng, and J. Qiu, "Parallel sequential pattern mining of massive trajectory data," Int. J. Comput. Intell. Syst., vol. 3, no. 3, pp. 343-356, Sep. 2010.
9. J. C. Ying,W. C. Lee, T. C.Weng, and S. Tseng, "Semantic trajectory mining for location prediction," in Proc. 19th ACM SIGSPATIAL Int. Conf. Adv. Geographic Inf. Syst., New York, NY, USA, 2011, pp. 34-43, ACM.
10. A. Sadilek and J. Krumm, "Far out: Predicting long-term human mobility," in Proc. 26th AAAI Conf. Artif. Intell., Palo Alto, CA, USA, AAAI Press.
11. T. Hunter, P. Abbeel, and A. M. Bayen, "The path inference filter: Modelbased low-latency map matching of probe vehicle data," IEEE Trans. Intell. Transp. Syst., vol. 15, no. 2, pp. 507-529, Apr. 2014.
12. J. Zhou, K. H. Tung, W. Wu, and W. S. Ng, "A "semi-lazy" approach to probabilistic path prediction in dynamic environments," in Proc. 19th ACM SIGKDD Int. Conf. Knowl. Discovery Data Mining, NewYork, NY, USA, 2013, pp. 748-756, ACM.
13. T. L. Pan, A. Sumalee, R. X. Zhong, and N. Indra-payoong, "Short-term traffic state prediction based on temporalspatial correlation," IEEE Trans. Intell. Transp. Syst., vol. 14, no. 3, pp. 1-23, Sep. 2013.
14. L. Wang, K. Hu, T. Ku, and X. Yan, "Mining frequent trajectory pattern based on vague space partition," Knowl.-Based Syst., vol. 50, pp. 100-111, Sep. 2013.
15. S. Qiao, D. Shen, X. Wang, N. Han, and W. Zhu, "A self-adaptive parameter selection trajectory prediction approach via hidden Markov models," IEEE Trans. Intell. Transp. Syst., vol. 16, no. 1, pp. 284-296, Feb. 2015.
16. Y. Tao, D. Papadias, and J. Sun, "The TPR-tree: An optimized spatiotemporal access method for predictive queries," in Proc. 29th Int. Conf. Very Large Data Bases, 2003, pp. 790-801, ser. VLDB'03. VLDB Endowment.
17. J. Chen and X. Meng, "Update-efficient indexing of moving objects in road networks," Geoinformatica, vol. 13, no. 4, pp. 397-424, Dec. 2009.
18. E. Frentzos, "Indexing objects moving on fixed networks," in Proc. 8th Int. Symp. Spatial Temporal Databases, Berlin, Germany, 2003, pp. 289-305, Springer.
19. V. T. Almeida and R. H. Güting, "Indexing the trajectories of moving objects in networks," Geoinformatica, vol. 9, no. 1, pp. 33-60, Mar. 2005.
20. Z. Ding, X. Li, and B. Yu, "Indexing the historical, current, future locations of network-constrained moving objects," (in Chinese), J. Softw., vol. 20, no. 12, pp. 3193-3204, 2009.
21. J. Yuan, Y. Zheng, and X. Xie, "Discovering regions of different functions in a city using human mobility and POIs," in Proc. 18th ACM SIGKDD Int. Conf. Knowledge Discovery Data Mining, New York, NY, USA, 2012, pp. 186-194, ACM.
22. J. Sander, M. Ester, H. P. Kriegel, and X. Xu, "Density-based clustering in spatial databases: The algorithm DBSCAN and its applications," Data Mining Knowl. Discovery, vol. 2, no. 2, pp. 169-194, 1998.
23. J. Han, J. Pei, Y. Yin, and R. Mao, "Mining frequent patterns without candidate generation: A frequent-pattern tree approach," Data Mining Knowl. Discovery, vol. 8, no. 1, pp. 53-87, Jan. 2004.
24. T. Brinkhoff, "A framework for generating network-based moving objects," Geoinformatica, vol. 6, no. 2, pp. 153-180, Jun. 2002.
25. S. Qiao et al., "PutMode: Prediction of uncertain trajectories in moving objects databases," Appl. Intell., vol. 33, no. 3, pp. 370-386, 2010.