SIMULATING PEDESTRIAN ROUTE SELECTION WITH IMPERFECT KNOWLEDGE

Kyle Feuz, Vicki Allan

Abstract

Heuristic evaluation of possible route choices allows pedestrians to make decisions in a timely and efficient manner. The heuristic function used to evaluate the route and the subsequent route selection has a large impact on the egress time of the pedestrian. We implement several common heuristic functions using the PLEASE simulation model and allow these heuristics to be combined using weighted factors. When the total distance of a route is unknown, using a greedy strategy of selecting the shortest-leg first route is shown to be a poor choice. When combined with other heuristic estimates however, including shortest-leg first costs can help to decrease egress times. We show that for a variety of building layouts using a heuristic function based upon width, distance, signage and congestion levels leads to better egress times.

References

  1. Büchner, S., Hölscher, C., and Strube, G. (2007). Path choice heuristics for navigation related to mental representations of a building. In Proceedings of the European Cognitive Science Conference, pages 504-509. Taylor & Francis.
  2. Dalton, R. (2003). The secret is to follow your nose. Environment and Behavior, 35(1):107.
  3. Feuz, K. (2011). Pedestrian leadership and egress assistance simulation environment. Master's thesis, Utah State University.
  4. Fridman, N. and Kaminka, G. (2007). Towards a cognitive model of crowd behavior based on social comparison theory. In Proceedings of the National Conference on Artificial Intelligence, volume 22, page 731. Menlo Park, CA; Cambridge, MA; London; AAAI Press; MIT Press; 1999.
  5. Golledge, R. (1995). Path selection and route preference in human navigation: A progress report. Spatial Information Theory A Theoretical Basis for GIS, pages 207-222.
  6. Gwynne, S., Galea, E., and Lawrence, P. (2006). The introduction of social adaptation within evacuation modelling. Fire and materials, 30(4):285-309.
  7. Gwynne, S., Galea, E. R., Lawrence, P. J., and Filippidis, L. (2001). Modelling occupant interaction with fire conditions using the buildingexodus evacuation model. Fire Safety Journal, 36(4):327-357.
  8. Helbing, D. and Johansson, A. (2009). Pedestrian, crowd and evacuation dynamics. In Encyclopedia of Complexity and Systems Science, pages 6476-6495. Springer.
  9. Hillier, B. (1996). Space is the Machine. Cambridge University Press, Cambridge.
  10. Hochmair, H. and Frank, A. (2000). Influence of estimation errors on wayfinding-decisions in unknown street networks-analyzing the least-angle strategy. Spatial Cognition and Computation, 2(4):283-313.
  11. Hoogendoorn, S. and Bovy, P. (2004). Pedestrian routechoice and activity scheduling theory and models. Transportation Research Part B: Methodological, 38(2):169-190.
  12. Koh, W. L., Lin, L., and Zhou, S. (2008). Modelling and simulation of pedestrian behaviours. In PADS 7808: Proceedings of the 22nd Workshop on Principles of Advanced and Distributed Simulation, pages 43-50, Washington, DC, USA. IEEE Computer Society.
  13. Kray, C., Kortuem, G., and Krüger, A. (2005). Adaptive navigation support with public displays. In Proceedings of the 10th international conference on Intelligent user interfaces, IUI 7805, pages 326-328, New York, NY, USA. ACM.
  14. Ozel, F. (2001). Time pressure and stress as a factor during emergency egress. Safety Science, 38(2):95-107.
  15. Pan, X. (2006). Computational Modeling of Human and Social Behaviors for Emergency Egress Analysis. PhD thesis, Stanford University, Stanford, California.
  16. Thompson, P. and Marchant, E. (1995). Testing and application of the computer model simulex. Fire Safety Journal, 24(2):149-166.
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Paper Citation


in Harvard Style

Feuz K. and Allan V. (2012). SIMULATING PEDESTRIAN ROUTE SELECTION WITH IMPERFECT KNOWLEDGE . In Proceedings of the 4th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-8425-96-6, pages 146-153. DOI: 10.5220/0003726201460153


in Bibtex Style

@conference{icaart12,
author={Kyle Feuz and Vicki Allan},
title={SIMULATING PEDESTRIAN ROUTE SELECTION WITH IMPERFECT KNOWLEDGE},
booktitle={Proceedings of the 4th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2012},
pages={146-153},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003726201460153},
isbn={978-989-8425-96-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - SIMULATING PEDESTRIAN ROUTE SELECTION WITH IMPERFECT KNOWLEDGE
SN - 978-989-8425-96-6
AU - Feuz K.
AU - Allan V.
PY - 2012
SP - 146
EP - 153
DO - 10.5220/0003726201460153