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Driver Destination Models

  • John Krumm
  • Eric Horvitz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4511)

Abstract

Predictive models of destinations represent an opportunity in the context of the increasing availability and sophistication of in-car driving aids. We present analyses of drivers’ destinations based on GPS data recorded from 180 volunteer subjects. We focus on the probability of observing drivers visit previously unobserved destinations given time of day and day of week, and the rate of decline of observing such new destinations with time. For the latter, we discover a statistically significant difference based on gender.

Keywords

driving mobility destinations cars automobiles navigation 

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References

  1. 1.
    Krumm, J., Horvitz, E.: Predestination: Inferring Destinations from Partial Trajectories. In: Eighth International Conference on Ubiquitous Computing UbiComp, 2006. Orange County, CA ( 2006)Google Scholar
  2. 2.
    Kostov, V., et al.: Travel Destination Prediction Using Frequent Crossing Pattern from Driving History. In: 8th International IEEE Conference on Intelligent Transportation Systems, Vienna, Austria ( 2005)Google Scholar
  3. 3.
    Marmasse, N., Schmandt, C.: A User-Centered Location Model. Personal and Ubiquitous Computing (6), 318–321 (2002)CrossRefGoogle Scholar
  4. 4.
    Ashbrook, D., Starner, T.: Using GPS To Learn Significant Locations and Predict Movement Across Multiple Users. Personal and Ubiquitous Computing 7(5), 275–286 (2003)CrossRefGoogle Scholar
  5. 5.
    Hariharan, R., Toyama, K.: Project Lachesis: Parsing and Modeling Location Histories. In: GIScience 2004, Springer, Heidelberg (2004)Google Scholar
  6. 6.
    Liao, L., Fox, D., Kautz, H.: Learning and Inferring Transportation Routines. In Proceedings of the 19th National Conference on Artificial Intelligence (AAAI 2004). San Jose, CA, USA (2004)Google Scholar
  7. 7.
    Gogate, V., et al.: Modeling Transportation Routines using Hybrid Dynamic Mixed Networks. In: Uncertainty in Artificial Intelligence (UAI 2005) (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • John Krumm
    • 1
  • Eric Horvitz
    • 1
  1. 1.Microsoft Research, Microsoft Corporation, One Microsoft Way, Redmond, WA 98052U.S.A.

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