Linking Cognitive and Computational Saliences in Route Information

  • Makoto Takemiya
  • Kai-Florian Richter
  • Toru Ishikawa
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7463)

Abstract

Finding a destination in a new spatial environment can be a daunting task. To aid navigation, many people take advantage of route directions, either provided by other people or by electronic navigation services. However, their effectiveness may be hampered if they are overly complex. While most people are generally good at focusing on important information, this is a challenge for navigation services. Thus, being able to automatically determine important points along a route that need to be included in route directions would provide a further step towards cognitively ergonomic navigation services. In the present study, methods for calculating the salience—or importance—of decision points are correlated with the frequency of decision points appearing in route directions. Results show that metrics based on the probability of a decision point being traversed and information-theoretic quantities of decision points correlate significantly with incidence in route directions, indicating that it is possible to identify crucial decision points in advance. This has implications for the design of navigation services that are able to adapt their assistance in real time.

Keywords

navigation route directions individual differences salience 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Allen, G.L.: Principles and practices for communicating route knowledge. Applied Cognitive Psychology 14(4), 333–359 (2000)CrossRefGoogle Scholar
  2. 2.
    Bryan, K., Leise, T.: The $25,000,000,000 eigenvector: The linear algebra behind Google. SIAM Rev. 48(3), 569–581 (2006)MathSciNetMATHCrossRefGoogle Scholar
  3. 3.
    Caduff, D., Timpf, S.: The landmark spider: Representing landmark knowledge for wayfinding tasks. In: Barkowsky, T., Freksa, C., Hegarty, M., Lowe, R. (eds.) Reasoning with Mental and External Diagrams: Computational Modeling and Spatial Assistance - Papers from the 2005 AAAI Spring Symposium, Menlo Park, CA, pp. 30–35 (2005)Google Scholar
  4. 4.
    Carlson, L.A., Hölscher, C., Shipley, T.F., Dalton, R.C.: Getting lost in buildings. Current Directions in Psychological Science 19(5), 284–289 (2010)CrossRefGoogle Scholar
  5. 5.
    Claramunt, C., Winter, S.: Structural salience of elements of the city. Environment and Planning B 34(6), 1030–1050 (2007)CrossRefGoogle Scholar
  6. 6.
    Couclelis, H., Golledge, R.G., Gale, N., Tobler, W.: Exploring the anchor-point hypothesis of spatial cognition. Journal of Environmental Psychology 7, 99–122 (1987)CrossRefGoogle Scholar
  7. 7.
    Dale, R., Geldof, S., Prost, J.P.: Using natural language generation in automatic route description. Journal of Research and Practice in Information Technology 37(1), 89–105 (2005)Google Scholar
  8. 8.
    Daniel, M.P., Denis, M.: Spatial descriptions as navigational aids: A cognitive analysis of route directions. Kognitionswissenschaft 7, 45–52 (1998)CrossRefGoogle Scholar
  9. 9.
    Denis, M.: The description of routes: A cognitive approach to the production of spatial discourse. Cahiers Psychologie Cognitive 16(4), 409–458 (1997)Google Scholar
  10. 10.
    Hansen, S., Richter, K.-F., Klippel, A.: Landmarks in OpenLS — A Data Structure for Cognitive Ergonomic Route Directions. In: Raubal, M., Miller, H.J., Frank, A.U., Goodchild, M.F. (eds.) GIScience 2006. LNCS, vol. 4197, pp. 128–144. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  11. 11.
    Hegarty, M., Montello, D., Richardson, A., Ishikawa, T., Lovelace, K.: Spatial abilities at different scales: Individual differences in aptitude-test performance and spatial-layout learning. Intelligence 34(2), 151–176 (2006)CrossRefGoogle Scholar
  12. 12.
    Hillier, B.: Space is the Machine: A Configurational Theory of Architecture. Cambridge University Press, Cambridge (1996)Google Scholar
  13. 13.
    Hirtle, S.C., Jonides, J.: Evidence of hierarchies in cognitive maps. Memory & Cognition 13(3), 208–217 (1985)CrossRefGoogle Scholar
  14. 14.
    Hirtle, S.C., Richter, K.F., Srivinas, S., Firth, R.: This is the tricky part: When directions become difficult. Journal of Spatial Information Science (1), 53–73 (2010)Google Scholar
  15. 15.
    Hölscher, C., Tenbrink, T., Wiener, J.: Would you follow your own route description? cognitive strategies in urban route planning. Cognition 121(2), 228–247 (2011)CrossRefGoogle Scholar
  16. 16.
    Ishikawa, T., Fujiwara, H., Imai, O., Okabe, A.: Wayfinding with a GPS-based mobile navigation system: A comparison with maps and direct experience. Journal of Environmental Psychology 28(1), 74–82 (2008)CrossRefGoogle Scholar
  17. 17.
    Ishikawa, T., Montello, D.: Spatial knowledge acquisition from direct experience in the environment: Individual differences in the development of metric knowledge and the integration of separately learned places. Cognitive Psychology 52(2), 93–129 (2006)CrossRefGoogle Scholar
  18. 18.
    Janzen, G., van Turennout, M.: Selective neural representation of objects relevant for navigation. Nature Neuroscience 7(6), 673–677 (2004)CrossRefGoogle Scholar
  19. 19.
    Jiang, B.: Ranking spaces for predicting human movement in an urban environment. International Journal of Geographical Information Science 23(7), 823–837 (2009)CrossRefGoogle Scholar
  20. 20.
    Klippel, A., Hansen, S., Richter, K.F., Winter, S.: Urban granularities - a data structure for cognitively ergonomic route directions. GeoInformatica 13(2), 223–247 (2009)CrossRefGoogle Scholar
  21. 21.
    Klippel, A., Richter, K.F., Hansen, S.: Cognitively ergonomic route directions. In: Karimi, H. (ed.) Handbook of Research on Geoinformatics, ch. XXIX, pp. 230–237. IGI: Information Science Reference, Hershey (2009)CrossRefGoogle Scholar
  22. 22.
    Klippel, A., Tappe, H., Habel, C.: Pictorial Representations of Routes: Chunking Route Segments during Comprehension. In: Freksa, C., Brauer, W., Habel, C., Wender, K.F. (eds.) Spatial Cognition III. LNCS (LNAI), vol. 2685, pp. 11–33. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  23. 23.
    Klippel, A., Tappe, H., Kulik, L., Lee, P.U.: Wayfinding choremes — a language for modeling conceptual route knowledge. Journal of Visual Languages and Computing 16(4), 311–329 (2005)CrossRefGoogle Scholar
  24. 24.
    Klippel, A., Winter, S.: Structural Salience of Landmarks for Route Directions. In: Cohn, A.G., Mark, D.M. (eds.) COSIT 2005. LNCS, vol. 3693, pp. 347–362. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  25. 25.
    Lovelace, K.L., Hegarty, M., Montello, D.R.: Elements of Good Route Directions in Familiar and Unfamiliar Environments. In: Freksa, C., Mark, D.M. (eds.) COSIT 1999. LNCS, vol. 1661, pp. 65–82. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  26. 26.
    Maaß, W.: How Spatial Information Connects Visual Perception and Natural Language Generation in Dynamic Environments: Towards a Computational Model. In: Kuhn, W., Frank, A.U. (eds.) COSIT 1995. LNCS, vol. 988, pp. 223–240. Springer, Heidelberg (1995)Google Scholar
  27. 27.
    Matthews, B.W.: Comparison of the predicted and observed secondary structure of T4 phage lysozyme. Biochimica et Biophysica Acta (BBA) - Protein Structure 405(2), 442–451 (1975)CrossRefGoogle Scholar
  28. 28.
    Michon, P.-E., Denis, M.: When and Why Are Visual Landmarks Used in Giving Directions? In: Montello, D.R. (ed.) COSIT 2001. LNCS, vol. 2205, pp. 292–305. Springer, Heidelberg (2001)Google Scholar
  29. 29.
    Page, L., Brin, S., Motwani, R., Winograd, T.: The PageRank citation ranking: Bringing order to the web. Technical Report 1999-66, Stanford InfoLab (November 1999)Google Scholar
  30. 30.
    Parush, A., Ahuvia, S., Erev, I.: Degradation in Spatial Knowledge Acquisition When Using Automatic Navigation Systems. In: Winter, S., Duckham, M., Kulik, L., Kuipers, B. (eds.) COSIT 2007. LNCS, vol. 4736, pp. 238–254. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  31. 31.
    Raubal, M., Winter, S.: Enriching Wayfinding Instructions with Local Landmarks. In: Egenhofer, M., Mark, D.M. (eds.) GIScience 2002. LNCS, vol. 2478, pp. 243–259. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  32. 32.
    Richter, K.F.: From turn-by-turn directions to overview information on the way to take. In: Gartner, G., Cartwright, W., Peterson, M.P. (eds.) Location Based Services and TeleCartography. Lecture Notes in Geoinformation and Cartography, pp. 205–216. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  33. 33.
    Richter, K.F.: Context-Specific Route Directions - Generation of Cognitively Motivated Wayfinding Instructions, DisKI, vol. 314. IOS Press, Amsterdam (2008) also published as SFB/TR 8 Monographs vol. 3Google Scholar
  34. 34.
    Richter, K.F., Dara-Abrams, D., Raubal, M.: Navigating and learning with location based services: A user-centric design. In: Gartner, G., Li, Y. (eds.) Proceedings of the 7th International Symposium on LBS and Telecartography, pp. 261–276 (2010)Google Scholar
  35. 35.
    Richter, K.-F., Klippel, A.: A Model for Context-Specific Route Directions. In: Freksa, C., Knauff, M., Krieg-Brückner, B., Nebel, B., Barkowsky, T. (eds.) Spatial Cognition IV. LNCS (LNAI), vol. 3343, pp. 58–78. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  36. 36.
    Shannon, C.: A mathematical theory of communication. Bell Syst. Tech. J. 27, 379–423 (1948)MathSciNetMATHGoogle Scholar
  37. 37.
    Sorrows, M.E., Hirtle, S.C.: The Nature of Landmarks for Real and Electronic Spaces. In: Freksa, C., Mark, D.M. (eds.) COSIT 1999. LNCS, vol. 1661, pp. 37–50. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  38. 38.
    Takemiya, M., Ishikawa, T.: Determining decision-point salience for real-time wayfinding support. Journal of Spatial Information Science (in press, 2012)Google Scholar
  39. 39.
    Takemiya, M., Ishikawa, T.: I Can Tell by the Way You Use Your Walk: Real-Time Classification of Wayfinding Performance. In: Egenhofer, M., Giudice, N., Moratz, R., Worboys, M. (eds.) COSIT 2011. LNCS, vol. 6899, pp. 90–109. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  40. 40.
    Tenbrink, T., Winter, S.: Variable granularity in route directions. Spatial Cognition & Computation: An Interdisciplinary Journal 9(1), 64–93 (2009)CrossRefGoogle Scholar
  41. 41.
    Timpf, S., Volta, G.S., Pollock, D.W., Frank, A.U., Egenhofer, M.J.: A Conceptual Model of Wayfinding using Multiple Levels of Abstraction. In: Frank, A.U., Formentini, U., Campari, I. (eds.) GIS 1992. LNCS, vol. 639, pp. 348–367. Springer, Heidelberg (1992)CrossRefGoogle Scholar
  42. 42.
    Tomko, M., Winter, S., Claramunt, C.: Experiential hierarchies of streets. Computers, Environment and Urban Systems 32(1), 41–52 (2008)CrossRefGoogle Scholar
  43. 43.
    Tversky, B., Lee, P.U.: Pictorial and Verbal Tools for Conveying Routes. In: Freksa, C., Mark, D.M. (eds.) COSIT 1999. LNCS, vol. 1661, pp. 51–64. Springer, Heidelberg (1999)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Makoto Takemiya
    • 1
  • Kai-Florian Richter
    • 2
  • Toru Ishikawa
    • 3
  1. 1.Graduate School of Interdisciplinary Information StudiesThe University of TokyoJapan
  2. 2.Department of Infrastructure EngineeringThe University of MelbourneAustralia
  3. 3.Center for Spatial Information ScienceThe University of TokyoJapan

Personalised recommendations