Calculating Meeting Points for Multi User Pedestrian Navigation Systems

  • Bjoern Zenker
  • Alexander Muench
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7006)


Most pedestrian navigation systems are intended for single users only. But pedesterians often prefere going out with other people, meeting friends and covering distances together. Thus we built a navigation system which allows calculating routes for multiple people who want to meet departing at different locations. In this paper we present, how satisfying meeting points can be found. We discuss two approaches, one based on the Steiner Tree Problem in Networks and one based on the Euclidian Steiner Problem which neglects the street network. Both approaches are evaluated and a user study demonstrates the applicability of our solution.


Street Network Steiner Point Meeting Point Steiner Tree Problem Goal Position 
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  1. 1.
    Moussaïd, M., Perozo, N., Garnier, S., Helbing, D., Theraulaz, G.: The walking behaviour of pedestrian social groups and its impact on crowd dynamics. PLoS ONE 5(4), e10047 (2010)Google Scholar
  2. 2.
    James, J.: A preliminary study of the size determinant in small group interaction. American Sociological Review 16(4), 474–477 (1951)CrossRefGoogle Scholar
  3. 3.
    Tumas, G., Ricci, F.: Personalized mobile city transport advisory system. In: ENTER Conference 2009 (2009)Google Scholar
  4. 4.
    Maruyama, A., Shibata, N., Murata, Y., Yasumoto, K.: P-tour: A personal navigation system for tourism. In: Proc. of 11th World Congress on ITS, pp. 18–21 (2004)Google Scholar
  5. 5.
    Voelkel, T., Weber, G.: Routecheckr: personalized multicriteria routing for mobility impaired pedestrians. In: Proceedings of the 10th International ACM SIGACCESS Conference on Computers and Accessibility, pp. 185–192 (2008)Google Scholar
  6. 6.
    van Setten, M., Pokraev, S., Koolwaaij, J.: Context-aware recommendations in the mobile tourist application compass. In: De Bra, P.M.E., Nejdl, W. (eds.) AH 2004. LNCS, vol. 3137, pp. 235–244. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  7. 7.
    Huang, R.: A schedule-based pathfinding algorithm for transit networks using pattern first search. Geoinformatica 11, 269–285 (2007)CrossRefGoogle Scholar
  8. 8.
    Ding, D., Yu, J.X., Qin, L.: Finding time-dependent shortest paths over large graphs. In: EDBT Proceedings, pp. 697–706 (2008)Google Scholar
  9. 9.
    Zenker, B., Ludwig, B.: Rose - an intelligent mobile assistant - discovering preferred events and finding comfortable transportation links. In: ICAART, vol. (1), pp. 365–370 (2010)Google Scholar
  10. 10.
    Winter, P.: Steiner problem in networks: a survey. Networks 17(2), 129–167 (1987)MathSciNetCrossRefzbMATHGoogle Scholar
  11. 11.
    Karp, R.: Reducibility Among Combinatorial Problems. In: Complexity of Computer Computations: Proceedings, pp. 85 (1972)Google Scholar
  12. 12.
    Proemel, H., Steger, A.: The Steiner tree problem: a tour through graphs, algorithms, and complexity. Friedrick Vieweg & Son (2002)Google Scholar
  13. 13.
    Melzak, Z.: On the problem of Steiner. Canad. Math. Bull 4(2), 143–148 (1961)MathSciNetCrossRefzbMATHGoogle Scholar
  14. 14.
    Smith, J., Lee, D., Liebman, J.: An O (n log n) heuristic for Steiner minimal tree problems on the Euclidean metric. Networks 11(1), 23–39 (1981)MathSciNetCrossRefzbMATHGoogle Scholar
  15. 15.
    Chang, S.: The generation of minimal trees with a Steiner topology. Journal of the ACM (JACM) 19(4), 699–711 (1972)MathSciNetCrossRefzbMATHGoogle Scholar
  16. 16.
    Warme, D., Winter, P., Zachariasen, M.: Exact algorithms for plane Steiner tree problems: A computational study. Advances in Steiner Trees, 81–116 (2000)Google Scholar
  17. 17.
    Winter, P.: An algorithm for the Steiner problem in the Euclidean plane. Networks 15(3), 323–345 (1985)MathSciNetCrossRefzbMATHGoogle Scholar
  18. 18.
    Becker, G.: The economic approach to human behavior. University of Chicago Press, Chicago (1976)Google Scholar
  19. 19.
    Wuersch, M., Caduff, D.: Refined route instructions using topological stages of closeness. In: Li, K.-J., Vangenot, C. (eds.) W2GIS 2005. LNCS, vol. 3833, pp. 31–41. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  20. 20.
    Helbing, D., Molnar, P., Farkas, I., Bolay, K.: Self-organizing pedestrian movement. Environment and Planning B 28(3), 361–384 (2001)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Bjoern Zenker
    • 1
  • Alexander Muench
    • 1
  1. 1.University of Erlangen-NuernbergErlangenGermany

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