Inferring driving trajectories based on probabilistic model from large scale taxi GPS data

Physica A: Statistical Mechanics and its Applications

Volumn 506, Issue , 2018, Pages 566-577

  Tang, Jinjun ^a   Liang, Jian ^a   Zhang, Shen ^b   Huang, Helai ^a   Liu, Fang ^c  

^a CENTRAL SOUTH UNIVERSITY   (China)

^b HARBIN INSTITUTE OF TECHNOLOGY   (China)

^c INNER MONGOLIA AGRICULTURAL UNIVERSITY   (China)

Author keywords

Global Positioning System; Hidden Markov model; Taxis trajectory; Trip prediction

Indexed keywords

FORECASTING; GLOBAL POSITIONING SYSTEM; HIDDEN MARKOV MODELS; LEARNING ALGORITHMS; TAXICABS; TRAFFIC CONGESTION; TRAJECTORIES;

DATA-DRIVEN APPROACH; MEASURE OF EFFECTIVENESS; PREDICTION PERFORMANCE; PREDICTIVE MODELING; PROBABILISTIC MODELING; STATUS INFORMATIONS; TEMPORAL AND SPATIAL; TRAFFIC INFORMATION;

PREDICTIVE ANALYTICS;

EID: 85046164305     PISSN: 03784371     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.physa.2018.04.073     Document Type: Article

References (45)

1. J. Froehlich, J. Krumm, Route prediction from trip observations, in: Proceedings of Society of Automotive Engineers World Congress, Detroit, USA, 2008, paper 2008-01-0201.
2. R. Simmons, B. Browning, Y. Zhang, V. Sadekar, Learning to predict driver route and destination intent, in: Proceedings of IEEE Intelligent Transportation Systems Conference, Toronto, Canada, 2006, pp. 127-132.
3. J. Krumm, A Markov model for driver turn prediction, in: Proceedings of Society of Automotive Engineers World Congress, Detroit, USA, paper 2008-01-0195, 2008.
4. A. Karbassi, M. Barth, Vehicle route prediction and time of arrival estimation techniques for improved transportation system management, in: Proceedings of Intelligent Vehicles Symposium, 2003, pp. 511–516.
5. Ashbrook, D., Starner, T., Using GPS to learn significant locations and predict movement across multiple users. Pers. Ubiquitous Comput. 7 (2003), 275–286.
6. Marmasse, N., Schmandt, C., A user-centered location model. Pers Ubiquitous Comput. 6 (2002), 318–321.
7. R. Hariharan, K. Toyama, Project lachesis: Parsing and modeling location histories, GIScience, LNCS 3234, 2004, pp. 106–124.
8. L. Liao, D. Fox, H. Kautz, Location-based activity recognition using relational Markov networks, in: Proceedings of the International Joint Conference on Artificial Intelligence, 2005.
9. J. Krumm, Real time destination prediction based on efficient routes. in: Proceedings of Society of Automotive Engineers World Congress, Detroit, USA, paper 2006-01-0811, 2006.
10. J. Krumm, E. Horvitz, Predestination: Inferring destinations from partial trajectories, in: Proceedings of Eighth International Conference on Ubiquitous Computing, Orange County, California, USA, 2006, pp. 241–260.
11. V. Gogate, R. Dechter, B. Bidyuk, C. Rindt, J. Marca, Modeling transportation routines using hybrid dynamic mixed networks, in: Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2005.
12. K. Torkkola, K. Zhang, H. Li, H. Zhang, C. Schreiner, M. Gardner, Traffic advisories based on route prediction, in: Proceedings of Workshop on Mobile Interaction with the Real World, Singapore, 2007.
13. Jeung, H., Yiu, M., Zhou, X., Jensen, C.S., Path prediction and predictive range querying in road network databases. Int. J. Very Large Data Bases 19 (2010), 585–602.
14. D. Patterson, L. Liao, D. Fox, H. Kautz, Inferring high-level behavior from low-level sensors, in: Proceedings of Ubiquitous Computing, Seattle, Washington, USA, 2003, pp. 73–89.
15. Y. Zheng, L. Zhang, X. Xie, W. Ma, Mining interesting locations and travel sequences from GPS trajectories, in: Proceedings of the International Conference on World Wide Web, 2009, pp. 791–800.
16. Liao, L., Patterson, D., Fox, D., Kautz, H., Learning and inferring transportation routines. Artif. Intell. 171 (2007), 311–331.
17. Chang, H., Tai, Y., Hsu, J.Y., Context-aware taxi demand hotspots prediction. Int. J. Bus. Intell. Data Mining 5 (2010), 3–18.
18. G. Qi, X. Li, S. Li, G. Pan, Z. Wang, Measuring social functions of city regions from large-scale taxi behaviors, in: Proceedings of IEEE International Conference on Pervasive Computing and Communications Workshops, Seattle, USA, 2011, pp. 384–388.
19. Tang, J., Liu, F., Zhang, W., Ke, R., Zou, Y., Lane-changes prediction based on adaptive fuzzy neural network. Expert Syst. Appl. 91 (2018), 452–463.
20. Sił anowicka, K., Vandrol, J., Oshan, T., Long, J., Demšar, U., Fotheringham, A., Analysis of human mobility patterns from gps trajectories and contextual information. Int. J. Geogr. Inf. Sci. 30 (2016), 881–906.
21. S. Phithakkitnukoon, M. Veloso, A. Biderman, C. Bento, C. Ratti, Taxi-aware map: Identifying and predicting vacant taxis in the city, in: Proceedings of the International Conference on Ambient Intelligence, 2010, pp. 86–95.
22. Zhang, S., Tang, J., Wang, H., Wang, Y., An, S., Revealing intra-urban travel patterns and service ranges from taxi trajectories. J. Transp. Geograph. 61 (2017), 72–86.
23. W. Liu, Y. Zheng, S. Chawla, J. Yuan, X. Xie, Discovering spatio-temporal causal interactions in traffic data streams, in: Proceedings of the 17th ACM SIGKDD conference on Knowledge Discovery and Data Mining, New York, USA, 2011, pp. 1010–1018.
24. Tang, J., Zhang, S., Liu, F., Zhang, W., Wang, Y., Statistical properties of urban mobility from location-based travel networks. Physica A 461 (2016), 694–707.
25. Tang, J., Liu, F., Wang, Y., Wang, H., Uncovering urban human mobility from large scale taxi GPS data. Physica A 438 (2015), 140–153.
26. Pan, G., Qi, G., Wu, Z., Zhang, D., Li, S., Land-use classification using taxi GPS traces. IEEE Trans. Intell. Transp. Syst. 14 (2013), 113–123.
27. D. Zhang, N. Li, Z. Zhou, C. Chen, L. Sun, S. Li, iBAT: Detecting anomalous taxi trajectories from GPS traces, in: Proceeding of the 13th International Conference on Ubiquitous Computing, New York, USA, 2011, pp. 99–108.
28. Chen, P., Yu, G., Wu, X., Ren, Y., Li, Y., Estimation of red-light running frequency using high resolution traffic and signal data. Acc. Anal. Prevent. 102 (2017), 235–247.
29. Tang, J., Zhang, Shen, Zou, Yajie, Liu, Fang, An adaptive map-matching algorithm based on hierarchical fuzzy system from vehicular GPS data. PLOS ONE, 12, 2017, e0188796.
30. Chen, P., Zeng, W., Yu, G., Wang, Y., Surrogate safety analysis of pedestrian-vehicle conflict at intersections using unmanned aerial vehicle videos. J. Adv. Transp. 2017 (2017), 1–12 5202150.
31. Rahmani, M., Koutsopoulos, H.N., Path inference from sparse floating car data for urban networks. Transp. Res. C Emerg. Technol. 30 (2013), 41–54.
32. Tang, J., Liu, F., Zou, Y., Zhang, W., Wang, Y., An improved fuzzy neural network for traffic speed prediction considering periodic characteristic. IEEE Trans. Intell. Transp. Syst. 18 (2017), 2340–2350.
33. Dong, H., Wu, M., Ding, X., Chu, L., Jia, L., Qin, Y., Zhou, X., Traffic zone division based on big data from mobile phone base stations. Transp. Res. C: Emerg. Technol. 58 (2015), 278–291.
34. J. Lee, I. Shin, G.L. Park, Analysis of the passenger pick-up pattern for taxi location recommendation, in: Proceedings of the 4th International Conference on Networked Computing and Advanced Information Management, Gyeongju, 2008, pp. 199–204.
35. B. Li, D. Zhang, L. Sun, C. Chen, S. Li, G. Qi, Q. Yang, Hunting or waiting? Discovering passenger-finding strategies from a large-scale real-world taxi dataset, in: Proceedings of IEEE International Conference on Pervasive Computing and Communications Workshops, Seattle, USA, 2011, pp. 63–68.
36. Tang, J., Jiang, H., Li, Z., Li, M., Liu, F., Wang, Y., A two-layer model for taxi customer searching behaviors using GPS trajectory data. IEEE Trans. Intell. Transp. Syst. 17 (2016), 3318–3324.
37. Wong, R.C.P., Szeto, W.Y., Wong, S.C., A cell-based logit-opportunity taxi customer-search model. Transp. Res. C: Emerg. Technol. 48 (2014), 84–96.
38. Jung, J., Chow, J.Y.J., Jayakrishnan, R., Park, J.Y., Stochastic dynamic itinerary interception refueling location problem with queue delay for electric taxi charging stations. Transp. Res. C: Emerg. Technol. 40 (2014), 123–142.
39. J. Yuan, Y. Zheng, L. Zhang, X. Xie, G. Sun, Where to find my next passenger? in: Proceedings of the 13th ACM International Conference on Ubiquitous Computing, Beijing, China, 2011, pp. 109–118.
40. Tang, J., Zhang, S., Chen, X., Liu, F., Zou, Y., Taxi trips distribution modeling based on entropy-maximizing theory: A case study in Harbin city - China. Physica A 493 (2018), 430–443.
41. J. Yuan, Y. Zheng, X. Xie, G. Sun, Driving with knowledge from the physical world, in: Proceedings of the 17th ACM SIGKDD conference on Knowledge Discovery and Data Mining, New York, USA, 2011, pp. 316–324.
42. Rabiner, L., Juang, B., Fundamentals of Speech Recognition. 1993, Prentice Hall.
43. Liu, X., Karimi, H.A., Location awareness through trajectory prediction. Comput. Environ. Urban Syst. 30 (2006), 741–756.
44. C.S. Jensen, D. Lin, B.C. Ooi, Query and update efficient B+-tree based indexing of moving objects, in: Proceeding of the 30th International Conference on Very Large Data Bases, 2004, pp. 768–779.
45. J.M. Patel, Y. Chen, V.P. Chakka, STRIPES: an efficient index for predicted trajectories, in: Proceeding of the ACM SIGMOD International Conference On Management of Data, New York, USA, 2004 pp. 635–646.