A Two-Layer Model for Taxi Customer Searching Behaviors Using GPS Trajectory Data

IEEE Transactions on Intelligent Transportation Systems

Volumn 17, Issue 11, 2016, Pages 3318-3324

  Tang, Jinjun ^a   Jiang, Han ^b   Li, Zhibin ^c   Li, Meng ^b   Liu, Fang ^d   Wang, Yinhai ^c  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

^b TSINGHUA UNIVERSITY   (China)

^c University of Washington   (United States)

^d INNER MONGOLIA AGRICULTURAL UNIVERSITY   (China)

Author keywords

Customer search behavior; Huff model; path overlapping; path size logit model; taxi GPS traces

Indexed keywords

GLOBAL POSITIONING SYSTEM; LOCATION; PICKUPS; SALES; TRAVEL TIME;

DECISION FRAMEWORK; GPS TRAJECTORIES; INTERSECTION DELAYS; MULTINOMIAL LOGIT; PATH TRAVEL TIME; ROUTE CHOICE BEHAVIOR; SEARCHING BEHAVIOR; VALIDATION RESULTS;

TAXICABS;

EID: 84964507746     PISSN: 15249050     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITS.2016.2544140     Document Type: Article

References (21)

1. D. H. Lee, H. Wang, R. L. Cheu, and S. H. Teo, "Taxi dispatch system based on current demands and real-time traffic conditions," Transp. Res. Rec., vol. 1882, pp. 193-200, 2004.
2. W. C. Lee and B. W. Cheng, "Incorporating e-technology to advantage in a greener taxi industry and its impact on driving performance and safety," Transp. Plan. Technol., vol. 31, no. 5, pp. 569-588, 2008.
3. J. Tang, F. Liu, Y. Wang, and H. Wang, "Uncovering urban human mobility from large scale taxi GPS data," Phys. A, Statist. Mech. Appl., vol. 438, no. 15, pp. 140-153, Nov. 2015.
4. H. W. Chang, Y. C. Tai, and Y. J. Hsu, "Context-aware taxi demand hotspots prediction," Int. J. Bus. Intell. Data Mining, vol. 5, no. 1, pp. 3-18, Dec. 2010.
5. R. Arnott, "Taxi travel should be subsidized," J. Urban Econ., vol. 40, no. 3, pp. 316-333, Nov. 1996.
6. R. D. Cairns and C. Liston-Heyes, "Competition and regulation in the taxi industry," J. Public Econ., vol. 59, no. 1, pp. 1-15, Jan. 1996.
7. R. C. P. Wong, W. Y. Szeto, and S. C. Wong, "A cell-based logitopportunity taxi customer-search model," Transp. Res. C, Emerging Technol., vol. 48, pp. 84-96, Nov. 2014.
8. H. Yang, S. C. Wong, and K. I. Wong, "Demand-supply equilibrium of taxi services in a network under competition and regulation," Transp. Res. B, Methodol., vol. 36, no. 9, pp. 799-819, Nov. 2002.
9. B. D. Ziebart, A. L. Maas, A. K. Dey, and J. A. Bagnell, "Navigate like a cabbie: Probabilistic reasoning from observed context-aware behavior," in Proc. 10th Int. Conf. Ubiquitous Comput., Seoul, South Korea, 2008, pp. 1-10.
10. R. M. N. T. Sirisoma et al., "Empirical evidence for taxi customer-search model in Hong Kong," Proc. Inst. Civil Eng., Transp., vol. 163, no. 4, pp. 203-210, Dec. 2010.
11. W. Y. Szeto, R. C. P.Wong, S. C. Wong, and H. Yang, "A time-dependent logit-based taxi customer-search model," Int. J. Urban Sci., vol. 17, pp. 184-198, 2013.
12. R. Tan, M. Adnan, and D. H. Lee, "A new path size formulation in path size logit for route choice modeling in public transport networks," presented at the Proceedings 94th Transportation Research Board Annual Meeting, Washington, DC, USA, 2015.
13. M. Ben-Akiva and S. Ramming, "Lecture notes: Discrete choice models of traveler behavior in networks," presented at the Advanced Methods Planning Management Transportation Networks, Capri, Italy, 1998.
14. M. Ester, H. Kriegel, J. Sander, and X. Xu, "A density-based algorithm for sparse representations," in Proc. 2nd Int. Conf. Knowl. Discov. Data Mining, 1996, pp. 226-231.
15. D. L. Huff, "A probabilistic analysis of shopping center trade areas," Land Econ., vol. 39, no. 1, pp. 81-90, 1963.
16. M. E. O'Kelly, "Trade-area models and choice-based samples: Methods," Environ. Plan. A, vol. 31, no. 4, pp. 613-627, 1999.
17. J. Nocedal and S. J. Wright, Numerical Optimization. NewYork,NY, USA: Springer-Verlag, 2006, pp. 258-264.
18. E. Frejinger and M. Bierlaire, "Capturing correlation with subnetworks in route choice models," Transp. Res. B, Methodol., vol. 41, no. 3, pp. 363-378, Mar. 2007.
19. P. H. Bovy, S. Bekhor, and C. G. Prato, "The factor of revisited path size: Alternative derivation," Transp. Res. Rec., vol. 24, no. 1, pp. 132-140, 2008.
20. M. Rahmani and H. N. Koutsopoulos, "Path inference from sparse floating car data for urban networks," Transp. Res. C, Emerging Technol., vol. 30, pp. 41-54, May 2013.
21. X. Ma, H. Yu, Y.Wang, and Y.Wang, "Large-scale transportation network congestion evolution prediction using deep learning theory," PloS one, vol. 10, no. 3, 2015, Art. no. e0119044.