Quantitative comparison between crowd models for evacuation planning and evaluation
 Vaisagh Viswanathan,
 Chong Eu Lee,
 Michael Harold Lees,
 Siew Ann Cheong,
 Peter M. A. Sloot
 … show all 5 hide
Rent the article at a discount
Rent now* Final gross prices may vary according to local VAT.
Get AccessAbstract
Crowd simulation is rapidly becoming a standard tool for evacuation planning and evaluation. However, the many crowd models in the literature are structurally different, and few have been rigorously calibrated against realworld egress data, especially in emergency situations. In this paper we describe a procedure to quantitatively compare different crowd models or between models and realworld data. We simulated three models: (1) the lattice gas model, (2) the social force model, and (3) the RVO2 model, and obtained the distributions of six observables: (1) evacuation time, (2) zoned evacuation time, (3) passage density, (4) total distance traveled, (5) inconvenience, and (6) flow rate. We then used the DISTATIS procedure to compute the compromise matrix of statistical distances between the three models. Projecting the three models onto the first two principal components of the compromise matrix, we find the lattice gas and RVO2 models are similar in terms of the evacuation time, passage density, and flow rates, whereas the social force and RVO2 models are similar in terms of the total distance traveled. Most importantly, we find that the zoned evacuation times of the three models to be very different from each other. Thus we propose to use this variable, if it can be measured, as the key test between different models, and also between models and the real world. Finally, we compared the model flow rates against the flow rate of an emergency evacuation during the May 2008 Sichuan earthquake, and found the social force model agrees best with this real data.
 Title
 Quantitative comparison between crowd models for evacuation planning and evaluation
 Journal

The European Physical Journal B
87:27
 Online Date
 February 2014
 DOI
 10.1140/epjb/e201440699x
 Print ISSN
 14346028
 Online ISSN
 14346036
 Publisher
 Springer Berlin Heidelberg
 Additional Links
 Topics
 Keywords

 Statistical and Nonlinear Physics
 Industry Sectors
 Authors

 Vaisagh Viswanathan ^{(1)}
 Chong Eu Lee ^{(2)}
 Michael Harold Lees ^{(1)} ^{(3)} ^{(4)}
 Siew Ann Cheong ^{(2)} ^{(4)}
 Peter M. A. Sloot ^{(1)} ^{(3)} ^{(4)} ^{(5)}
 Author Affiliations

 1. School of Computer Engineering, Nanyang Technological University, Nanyang Avenue, 639798, Singapore, Republic of Singapore
 2. Division of Physics and Applied Physics, School of Physical and Mathematical Sciences, Nanyang Technological University, 21 Nanyang Link, 637371, Singapore, Republic of Singapore
 3. Computational Science, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, The Netherlands
 4. Complexity Program, Nanyang Technological University, 60 Nanyang View, 639673, Singapore, Republic of Singapore
 5. National Research Institute ITMO, 197101, St. Petersburg, Russia