A Video-Based Observation and Analysis Method to Assess Human Movement and Behaviour in Crowded Areas
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A Video-Based Observation and Analysis Method to Assess Human Movement and Behaviour in Crowded Areas

Authors: Shahrol Mohamaddan, Keith Case, Ana Sakura Zainal Abidin

Abstract:

Human movement in the real world provides important information for developing human behaviour models and simulations. However, it is difficult to assess ‘real’ human behaviour since there is no established method available. As part of the AUNTSUE (Accessibility and User Needs in Transport – Sustainable Urban Environments) project, this research aimed to propose a method to assess human movement and behaviour in crowded areas. The method is based on the three major steps of video recording, conceptual behavior modelling and video analysis. The focus is on individual human movement and behaviour in normal situations (panic situations are not considered) and the interactions between individuals in localized areas. Emphasis is placed on gaining knowledge of characteristics of human movement and behaviour in the real world that can be modelled in the virtual environment.

Keywords: Video observation, Human movement, Behaviour, Crowds, Ergonomics, AUNT-SUE

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1096976

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References:


[1] G.K. Still, “Crowd Dynamics,” Doctoral Thesis, University of Warwick, 2000
[2] R. Marshall, S. Summerskill, J.M. Porter, K. Case, R.E. Sims, D.E. Gyi, and P. Davis, “Multivariate Design Inclusion Using HADRIAN,” in Proc. of the SAE 2008 Digital Human Modelling for Design and Engineering Conference and Exhibition, Pittsburgh, Pennsylvania, USA 2008
[3] R. Marshall, J.M. Porter, R.E. Sims, D.E. Gyi and K. Case, “HADRIAN Meets AUNT-SUE,” in Proc. of the International Conference on Inclusive Design, INCLUDE 2005, Royal College of Art, London, UK, 2005
[4] I. Pehkonen, R. Ketola, R. Ranta and E.P. Takala, “A Video-Based Observation Method to Assess Musculoskeletal Load in Kitchen Work,” International Journal of Occupational Safety and Ergonomics, Vol. 15, No. 1, pp. 75-88, 2009
[5] P.G. Dempsey, R.W. McGorry and W.S. Maynard, “A Survey of Tools and Methods used by Certificate Professional Ergonomists,” Applied Ergonomics, Vol. 36, No. 4, pp. 489-503, 2005
[6] S.A. Pascual and S. Naqvi, “An Investigation of Ergonomics Analysis Tools Used in Industry in the Identification of Work-Related Musculoskeletal Disorders,” International Journal of Occupational Safety and Ergonomics, Vol. 14, No. 2, pp. 237-245, 2008
[7] T.Y. Yen and R.G. Radwin, “A Comparison Between Analysis Time and Inter-Analyst Reliability Using Spectral Analysis of Kinematic Data and Posture Classification,” Applied Ergonomics, Vol. 33, pp. 85-93, 2002
[8] L.P. Noldus, R.J. Trienes, A.H. Hendriksen, H. Jansen and R.G. Jansen, “The Observer Video-Pro: New Software for the Collection, Management and Presentation of Time-Structured Data from Videotapes and Digital Media Files,” Behavior Research Methods, Instruments and Computers, Vol. 32, No. 1, pp. 197-206, 2000
[9] L. McAtamney and E.N. Corlett, “RULA: A Survey Method for the Investigation of Work-Related Upper Limb Disorders,” Applied Ergonomics, Vol. 24, No. 2, pp. 91-99, 1993
[10] S. Hignett and L. McAtamney, “Rapid Entire Body Assessment (REBA),” Applied Ergonomics, Vol. 31, No. 2, pp. 201-205, 2000
[11] G. David, V. Woods, G. Li and P. Buckle, “The Development of the Quick Exposure Check (QEC) for Assessing Exposure to Risk Factors for Work-Related Musculoskeletal Disorders,” Applied Ergonomics, Vol. 39, No. 1, pp. 57-69, 2008
[12] S. Mohamaddan, “Human Movement and Behaviour Simulation Using Gaming Software,” Doctoral Thesis, Loughborough University, 2013
[13] W. Daamen, P.H.L. Bovy and S.P. Hoogendoorn, S.P., “Modeling Pedestrians in Transfer Stations,” Pedestrians and Evacuation Dynamics, pp. 59-73, 2002
[14] S.P. Hoogendoorn, W. Daamen and P.H.L. Bovy, “Extracting Microscopic Pedestrian Characteristics from Video Data,” Transportation Research Board Annual Meeting, 2003
[15] T. Kretz, A. Grunebohm and M. Schreckenberg, “Experimental Study of Pedestrian Flow Through a Bottleneck,” Journal of Statistical Mechanics: Theory and Experiment, No. 10, 2006
[16] A. Seyried, T. Rupprecht, O. Passon, B. Steffen, W. Klingsch and M. Boltes, “New Insight Into Pedestrian Flow Through Bottlenecks,” Transportation Science, Vol. 43, No. 3, pp. 395-406, 2009
[17] S.J. Rymill and N.A. Dodgson, “A Psychologically-Based Simulation of Human Behaviour,” Theory and Practice of Computer Graphics, 2005
[18] F. Cherif and R. Chighoub, “Crowd Simulation Influenced by Agent’s Socio-Psychological State,” Journal of Computing, Vol. 2, No. 4, 2010
[19] X. Pan, C.S. Han, K. Dauber and K.H. Law, “Human and Social Behavior in Computational Modeling and Analysis of Egress,” Automation in Construction, Vol. 15, No. 4, pp. 448-461, 2006
[20] N. Pelechano, K. O’Brien, B. Silverman and N. Badler, “Crowd Simulation Incorporating Agent Psychological Models, Roles and Communication,” International Workshop on Crowd Simulation, 2005
[21] L.Z. Yang, D.L. Zhao, J. Li and T.Y. Fang, “Simulation of the Kin Behavior in Building Occupant Evacuation Based on Cellular Automaton,” Building and Environment, Vol. 40, No. 3, pp. 411-415, 2005
[22] S. Mohamaddan and K. Case, “Agent-Based Modelling and Simulation through Video Observation Analysis,” in Proc. of International FLINS Conference on Uncertainty Modelling in Knowledge Engineering and Decision Making, Vol. 7, pp. 412-417, 2012
[23] S. Mohamaddan and K. Case, “Towards Understanding of Human Behaviour in Crowded Spaces Using Video Observation Analysis,” in Proc. of International Conference on Manufacturing Research, Vol.2, pp. 637-642, 2012
[24] J.F. Suri and M. Marsh, “Scenario Building as an Ergonomics Method in Consumer Product Design,” Applied Ergonomics, Vol. 31, No. 2, pp. 151-157, 2000