A Markov-chain Activity-based Model for Pedestrians in Office Buildings

Sanmay Shelat; Winnie Daamen; Bjorn Kaag; Dorine Duives; Serge Hoogendoorn

doi:10.17815/CD.2020.78

Authors

Sanmay Shelat Department of Transport and Planning, Delft University of Technology, Delft, The Netherlands
Winnie Daamen Department of Transport and Planning, Delft University of Technology, Delft, The Netherlands
Bjorn Kaag Argosonic, Heerlen, The Netherlands
Dorine Duives Department of Transport and Planning, Delft University of Technology, Delft, The Netherlands
Serge Hoogendoorn Department of Transport and Planning, Delft University of Technology, Delft, The Netherlands

DOI:

https://doi.org/10.17815/CD.2020.78

Keywords:

pedestrians, tactical behaviour level, offices, buildings, activity-based, markov-chain

Abstract

As the number of people working in office buildings increases, there is an urgent need to improve building services, such as lighting and temperature control, within these buildings to increase energy efficiency and well-being of occupants. A pedestrian behaviour model that simulates office occupants’ movements and locations can provide the high spatial and temporal resolution data required for the testing, evaluation, and optimization of these control systems. However, since most studies in pedestrian research focus on modelling specific actions at the operational level or target situations where movement schedules do not have to modelled, a pedestrian behaviour model that can simulate complex situations over long time periods is missing. Therefore, this paper proposes a tactical level model to generate occupant movement patterns in office buildings. The Markov-chain activity-based model proposed here is data parsimonious, flexible in accepting different levels of information, and can produce high resolution output. The mathematical properties of the methodology are analyzed to understand their impact on the final results. Finally, the tactical level pedestrian behaviour model is face validated using a case study of an imaginary office with a simple layout.

References

S. P. Hoogendoorn, "Normative Pedestrian Flow Behavior: Theory and Applications," Delft University of Technology2001.

A. Schadschneider, H. Klüpfel, T. Kretz, C. Rogsch, and A. Seyfried, "Fundamentals of pedestrian and evacuation dynamics," in Multi-Agent Systems for Traffic and Transportation Engineering: IGI Global, 2009, pp. 124-154.

V. Tabak, "User simulation of space utilisation," Eindhoven University Press9068146149, 2008, vol. PhD.

C. Liao, Y. Lin, and P. Barooah, "Agent-based and graphical modelling of building occupancy," Journal of Building Performance Simulation, vol. 5, pp. 5-25, 2011.

C. Wang, D. Yan, and Y. Jiang, "A novel approach for building occupancy simulation," Building Simulation, vol. 4, pp. 149-167, 2011.

A. Penn and A. Turner, "Space syntax based agent simulation," presented at the 1st International Conference on Pedestrian and Evacuation Dynamics, University of Duisburg, Germany, 2001.

E. Andresen, D. Haensel, M. Chraibi, and A. Seyfried, "Wayfinding and Cognitive Maps for Pedestrian Models," in Traffic and Granular Flow '15, Cham, 2016, pp. 249-256: Springer International Publishing.

X. Feng, D. Yan, and T. Hong, "Simulation of occupancy in buildings," Energy and Buildings, vol. 87, pp. 348-359, 2015.

Y. Chen, T. Hong, and X. Luo, "An agent-based stochastic Occupancy Simulator," Building Simulation, journal article pp. 1-13, 2017.

G. Zimmermann, "Modeling and Simulation of Individual User Behavior for Building Performance Predictions," presented at the Proceedings of the 2007 Summer Computer Simulation Conference, San Diego, California, 2007.

K. Sailer and I. McCulloh, "Social networks and spatial configuration—How office layouts drive social interaction," Social Networks, vol. 34, no. 1, pp. 47-58, 2012/01/01/ 2012.