Abstract
This paper reports progress in the development of a multi-agent model which simulates pedestrian destination, route choice and scheduling behavior. In this model, the simulation of movement is embedded in a more comprehensive model of activity scheduling and choice behavior. We assume that pedestrians will be activated to visit a store if the store is suited to conduct any of the activities that are still scheduled, and that they are aware of this store. When pedestrians are aware of a store and the store is included in their consideration set, they will be activated and gradually move to a store. We assume that activation level is a stochastic variable. To estimate the activation function, survey data were collected. Visitors were interviewed about various aspects of their behavior such as familiarity with stores, motivation, and expectations about store aspects like assortment, sphere, quality and service. In this paper, we will discuss some of the findings of this data collection.
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Ali, W., & Moulin, B. (2006). How articificial intelligent agents do shopping in a virtual mall: A ‘beleivable’and úsable’multiagent-based simulation of customers’ shopping behavior in a mall. In L. Lamontagne & M. Marchand (Eds.), Canadian AI, LNAI 4013 (pp. 73–85). Berlin: Springer.
Blue, V.J., & Adler, J.L. (1999). Bi-directional emergent fundamental pedestrian flows from cellular automata microsimulation. In A. Ceder (ed.), Transportation and Traffic Theory: Proceedings of the International Symposium on Traffic Theory. Pergamon, London.
Borgers, A., & Timmermans, H. J. P. (1986a). A model of pedestrian route choice and demand for retail facilities within inner-city shopping areas. Geographical Analysis, 18(2), 115–128.
Borgers, A., & Timmermans, H. J. P. (1986b). City centre entry points, store location patterns and pedestrian route choice behaviour: a micro-level simulation model. Socio-Economic Planning Sciences, 20, 25–30.
Borgers, A., & Timmermans, H.J.P. (2004). Simulating pedestrian route choice behaviour in urban & retail environments. Proceedings Walk21. Copenhagen, June 2004. (cd-rom)
Borgers, A., & Timmermans, H.J.P. (2005). Modeling pedestrian behaviour in downtown shopping areas. 9 th Computers in Urban Planning & Urban Management Conference CUPUM ‘05. London, June 2005.
Daamen, W. (2004). Modelling passenger flows in public transport facilities. Trail thesis series. Delft University Press, Delft.
Daamen, W., & Hoogendoorn, S. P. (2003). Controlled experiments to derive walking behaviour. European Journal of Transport and Infrastructure Research, 3(1), 39–59.
Dijkstra, J., Jessurun, A.J., & Timmermans, H.J.P. (2002). Simulating pedestrian activity scheduling behaviour and movement patters using a multi-agent cellular automata model, Proceedings of the Transportation Research Board Conference. Washington, January 2002.
Dijkstra, J., Timmermans, H.J.P., & de Vries, B. (2005). Modelling behavioural aspects of agents in simulating pedestrian movement 9 th Computers in Urban Planning & Urban Management Conference CUPUM’05. London, June 2005.
Dijkstra, J., Timmermans, H.J.P., & de Vries, B. (2007). Empirical estimation of agent shopping patterns for simulating pedestrian movement. 10 th Computers in Urban Planning & Urban Management Conference CUPUM’07. Iguassu, Brazil, July 2007.
Dijkstra, J., Jessurun, A. J., Timmermans, H. J. P., & de Vries, B. (2011). A framework for processing agent-based pedestrian activity simulations in shopping environments. Cybernetics and Systems, 42(7), 526–545.
Helbing, D., Farkas, I. J., & Viscek, T. (2000). Simulating dynamical features of escapic panic. Nature, 407, 487–489.
Hoogendoorn, S.P., & Daamen, W. (2002). Extracting microscopic pedestrian characteristics from video data. Proceedings of the Transportation Research Board Conference. Washington, January 2002.
Hoogendoorn, S. P., Bovy, P. H. L., & Daamen, W. (2001). Microscopic pedestrian wayfinding and dynamics modelling. In M. S. Chreckenberg & S. D. Sharma (Eds.), Pedestrian and evacuation dynamics. Berlin: Springer.
Kitazawa, K., & Batty, M. (2004). Pedestrian behaviour modelling—An application to retail movements using genetic algorithms. In J. P. van Leeuwen & H. J. P. Timmermans (Eds.), Developments in Design & Decision Support Systems in Architeccture and Urban Planning. Eindhoven: Eindhoven University of Technology.
Kukla, R., Kerridge, J., Willis, A., & Hine, J. (2001). PEDflow: development of an autonomous agent model of pedestrian flow. Proceedings of the Transportation Research Board Conference. Washington, January 1999.
Masuda, H., & Arai, T. (2005). An agent-based model of evacuation in a subway station. 9 th Computers in Urban Planning & Urban Management Conference CUPUM’05. London, June 2005.
Meyer-König, T., Klüpfel, H., & Schreckenberg, M. (2001). Assessment and analysis of evacuation processes on passenger ships by microscopic simulation. In M. Schreckenberg & S. D. Sharma (Eds.), Pedestrian and evacuation dynamics. Berlin: Springer.
Schelhorn, T., O’Sullivan, D., Hacklay, M., & Thurstain-Goodwin, M. (1999). STREETS: An agent-based pedestrian model. Venice: Computers in Urban Planning and Urban Management.
Shao, W. & Terzopoulos, D. (2005). Autonomous pedestrians. In K. Anjyo and P. Faloutsos (eds.), Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation. ACM, New York.
Teknomo, K. (2002). Microscopic pedestrian flow characteristics: Developement of an image processing data collection and simulation model. PhD thesis. Graduate School of Information Sciences, Tohoku.
Yoshida, T., & Kandea, T. (2007). An architecture and development framework for pedestrians’shop-around behavior model inside commercial district using agent-based approach. 10 th Computers in Urban Planning & Urban Management Conference CUPUM’07. Iguassu, Brazil, July 2007.
Zacharadis, V. (2005). Modelling pedestrian movement and choices from micro to urban scale: iussues, patterns and emergence. 9 th Computers in Urban Planning & Urban Management Conference CUPUM’05. London, June 2005.
Zhu, W., & Timmermans, H. J. P. (2010). Modeling pedestrian shopping behavior using principles of bounded rationality: Model comparison and validation. Journal of Geographical Systems, 13(2), 101–126.
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Dijkstra, J., Timmermans, H.J.P. & de Vries, B. Activation of Shopping Pedestrian Agents—Empirical Estimation Results. Appl. Spatial Analysis 6, 255–266 (2013). https://doi.org/10.1007/s12061-012-9082-3
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DOI: https://doi.org/10.1007/s12061-012-9082-3