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Imprecise Navigation

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Abstract

Conventional models of navigation commonly assume a navigation agent’s location can be precisely determined. This paper examines the more general case, where an agent’s actual location cannot be precisely determined. This paper develops a formal model of navigation under imprecision using a graph. Two key strategies for dealing with imprecision are identified and defined: contingency and refinement. A contingency strategy aims to find an instruction sequence that maximizes an agent’s chances of reaching its destination. A refinement strategy aims to use knowledge gained as an agent moves through the network to disambiguate location. Examples of both strategies are empirically tested using a simulation with computerized navigation agents moving through a road network at different levels of locational imprecision. The results of the simulation indicate that both the strategies, contingency and refinement, applied individually can produce significant improvements in navigation performance under imprecision, at least at relatively fine granularities. Using both strategies in concert produced significant improvements in performance across all granularities.

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References

  1. M. Agrawala and C. Stolte. “A design and implementation for effective computer-generated route maps,” in AAAI Symposium on Smart Graphics, 61–65, 2000.

  2. G. Allen and K. Kirasic. “Effects of the cognitive organization of route knowledge on judgments of macrospatial distances,” Memory and Cognition, Vol. 3:218–227, 1985.

    Google Scholar 

  3. P. Bahl and V. Padmanabhan. “RADAR: An in-building RF-based user location and tracking system,” in Proceedings IEEE INFOCOM 2000, Vol. 2:775–784, 2000.

    Google Scholar 

  4. D. Busquets, R. López de Móntarez, C. Sierra, and T. Dietterich. “A multi-agent architecture integrating learning and fuzzy techniques for landmark-based robot navigation,” in M. Escrig, F. Toledo, and E. Golobardes (Eds.), Proceedings Fifth Catalonian Conference on AI CCIA 2002, 269–281, 2002.

  5. E. Chown. “Making predictions in an uncertain world: Environmental structure and cognitive maps,” Adaptive Behaviour, Vol. 7(1), 1999.

  6. T. Cormen, C. Leiserson, R. Rivest, and C. Stein. Introduction to Algorithms. Second edition, McGraw-Hill.

  7. J. Cuellar, J. Morris, and D. Mulligan. “Geopriv requirements,” Internet Engineering Task Force (IETF) Internet Draft. http://www.ietf.org/ids.by.wg/geopriv.html.

  8. M. Denis, F. Pazzaglia, C. Cornoldi, and L. Bertolo. “Spatial discourse and navigation: An analysis of route directions in the city of Venice,” Applied Cognitive Psychology, Vol. 13:145–174, 1999.

    Google Scholar 

  9. M. Duckham and M. Worboys. “Computational structure in three-valued nearness relations,” in D. Montello (Ed.), Spatial Information Theory: Foundations of Geographic Information Science (COSIT 2001), Berlin, 79–91, 2001.

  10. Federal Communications Commission (FCC). “Enhanced 911,” http://www.fcc.gov/911/enhanced. Updated: January 3, 2003.

  11. A.U. Frank. “Communication with maps: A formalized model,” in C. Freksa, W. Brauer, C. Habel, and K. F. Wender (Eds.), Spatial Cognition II (Int. Workshop on Maps and Diagrammatical Representations of the Environment, Hamburg), Vol. 1849 of Lecture Notes in Artificial Intelligence. Springer-Verlag: Berlin, 80–99, 2000.

    Google Scholar 

  12. A.U. Frank. “Pragmatic information content—how to measure the information in a route description,” in M. Duckham, M. F. Goodchild, and M. F. Worboys (Eds.), Foundations in Geographic Information Science, Taylor & Francis: London, 47–68, 2003.

    Google Scholar 

  13. S. Goldin and P. Thorndyke. “Simulating navigation for spatial knowledge acquisition,” Human Factors, Vol. 24(4):457–471, 1982.

    Google Scholar 

  14. R. Golledge. “Place recognition and wayfinding: Making sense of space,” Geoforum, Vol. 23(2):199–214, 1992.

    Google Scholar 

  15. A. Harrington. “GPS/GIS integration: Lessen atmospheric and multipath GPS errors,” Geo World, Vol. 13(12):26–27, 2000.

    Google Scholar 

  16. J. Hightower and G. Boriello. “Location systems for ubiquitous computing” IEEE Computer, Vol. 34(8):57–66, 2001.

    Google Scholar 

  17. H. Hochmair. “The wayfinding metaphor—comparing the semantics of wayfinding in the physical world and the WWW,” Ph.D. thesis, Institute for Geoinformation, Technical University Vienna, 2002.

  18. J. Krumm, S. Harris, B. Meyers, B. Brumitt, M. Hale, and S. Shafer. “Multi-camera multi-person tracking for easyliving,” in Proceedings Third IEEE Workshop on Visual Surveillance VS2000, 3–10, 2000.

  19. B. Kuipers. “Representing Knowledge of Large-Scale Space,” Ph.D. thesis, Mathematics Department, Massachusetts Institute of Technology, Technical Report 418, M.I.T. Artificial Intelligence Laboratory, 1977.

  20. B. Kuipers. “Modelling spatial knowledge,” Cognitive Science, Vol. 2:129–153, 1978.

    Google Scholar 

  21. K. Lynch. The Image of the City. Harvard University Press: Cambridge, Massachusetts, 1960.

    Google Scholar 

  22. D. Mark. “Automated route selection for navigation,” IEEE Aerospace and Electronic Systems Magazine, Vol. 1(9):2–5, 1986.

    Google Scholar 

  23. M. Raubal and S. Winter. “Enriching wayfinding instructions with local landmarks,” in M. Egenhofer and D. Mark (Eds.), Geographic Information Science—Second International Conference GIScience 2002, Berlin, 2002.

  24. M. Raubal and M. Worboys. “A formal model of the process of wayfinding in built environments,” in C. Freksa and D. Mark (Eds.), Proceedings of the International Conference on Spatial Information Theory, Berlin, 381–401, 1999.

  25. S. Scott-Young and A. Kealy. “An intelligent navigation solution for land mobile location based services,” Journal of Navigation, Vol. 55:225–240, 2002.

    Google Scholar 

  26. A. Siegel and S. White. “The development of spatial representations of large-scale environments,” in H. Reese (Ed.), Advances in Child Development and Behavior, Vol. 10, Academic Press: New York, 9–55, 1975.

    Google Scholar 

  27. J. Stell. “Granulation for Graphs,” in C. Freksa and D. Mark (Eds.), Spatial Information Theory. Cognitive and Computational Foundations of Geographic Information Science, COSIT'99, Berlin 417–432, 1999.

  28. J. Stell and M. Worboys. “Generalizing graphs using amalgamation and selection,” in R. Guting, D. Papadial, and F. Lochovsky (Eds.), Advances in Spatial Databases: 6th International Symposium SSD'99, No. 1651 in Lecture Notes in Computer Science, Springer-Verlag: Berlin, 19–32, 1999.

    Google Scholar 

  29. L. Streeter and D. Vitello. “A profile of driver's map-reading abilities,” Human Factors, Vol. 28(2):223–239, 1986.

    Google Scholar 

  30. L. Streeter, D. Vitello, and S. Wonsiewicz. “How to tell people where to go: Comparing navigational aids,” International Journal of Man Machine Interaction, Vol. 22:549–562, 1985.

    Google Scholar 

  31. S. Timpf. “Ontologies of wayfinding: A traveler's perspective,” Networks and Spatial Economics, Vol. 2(1):9–33, 2002.

    Google Scholar 

  32. S. Timpf, G. Volta, D. Pollock, and M. Egenhofer. “A conceptual model of wayfinding using multiple levels of abstraction,” in A. Frank, I. Campari, and U. Formentini (Eds.), Theories and Methods of Spatio-Temporal Reasoning in Geographic Space, No. 639 in Lecture Notes in Computer Science. Springer-Verlag: Berlin, 348–367, 1992.

    Google Scholar 

  33. TruePosition. “TruePosition Web Site,” http://www.trueposition.com. Last accessed: January 23, 2003.

  34. R. Want, A. Hopper, V. Falcao, and J. Gibbons. “The Active Badge location system,” ACM Transactions on Information Systems, Vol. 10(1):91–102, 1992.

    Google Scholar 

  35. M. Worboys. “Nearness relations in environmental space,” International Journal of Geographical Information Science, Vol. 15(7):633–651, 2001.

    Google Scholar 

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Authors and Affiliations

  1. NCGIA, University of Maine, ME, 04469-5711, U.S.A

    Matt Duckham, Lars Kulik & Michael Worboys

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  1. Matt Duckham
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  2. Lars Kulik
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  3. Michael Worboys
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Duckham, M., Kulik, L. & Worboys, M. Imprecise Navigation. GeoInformatica 7, 79–94 (2003). https://doi.org/10.1023/A:1023426607262

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