Abstract
Multi-agent simulations can provide useful insights into the movement of pedestrians in arbitrary environments for predictive planning and analysis. The fidelity of such agents is important for the validity of the associated analyses. Current methods tend to employ agent models that are largely homogeneous in both physical abilities and behaviours. However, actual pedestrians exhibit a wide range of locomotion abilities and behaviours. In this work, we take a first step towards identifying and modelling distracted behaviours, such as walking and texting on a cell phone. Our models relate reported changes to the locomotion patterns and sensory abilities of distracted pedestrians to the corresponding parameters of a commonly used crowd simulation steering approach. We demonstrate experimentally that accounting for even a few of these behaviours significantly alters the flow patterns of the simulated agents. This impact affects overall crowd behaviour and is reflected in several crowd statistics including flow rate, effort, and kinetic energy.
Similar content being viewed by others
References
Agostini, V., Fermo, F.L., Massazza, G., Knaflitz, M.: Does texting while walking really affect gait in young adults? J. Neuroeng. Rehabil. 12(1), 86 (2015)
Allbeck, J.M., Badler, N.I.: Creating crowd variation with the ocean personality model (2008)
Bailly, G., Raidt, S., Elisei, F.: Gaze, conversational agents and face-to-face communication. Speech Commun. 52(6), 598–612 (2010)
Cha, J., Kim, H., Park, J., Song, C.: Effects of mobile texting and gaming on gait with obstructions under different illumination levels. Phys. Ther. Rehabil. Sci. 4(1), 32–37 (2015)
Curtis, S., Guy, S.J., Zafar, B., Manocha, D.: Virtual tawaf: a case study in simulating the behavior of dense, heterogeneous crowds. In: IEEE International Conference on Computer Vision Workshops (ICCV Workshops), pp. 128–135. IEEE (2011)
Durupinar, F., Allbeck, J., Pelechano, N., Badler, N.: Creating crowd variation with the ocean personality model. In: Proceedings of the 7th International Joint Conference on Autonomous Agents and Multiagent Systems, vol. 3, pp. 1217–1220. International Foundation for Autonomous Agents and Multiagent Systems (2008)
Funge, J., Tu, X., Terzopoulos, D.: Cognitive modeling: knowledge, reasoning and planning for intelligent characters (1999)
Grillon, H., Thalmann, D.: Simulating gaze attention behaviors for crowds. Comput. Anim. Virtual Worlds 20(2–3), 111–119 (2009)
Guy, S.J., Chhugani, J., Curtis, S., Dubey, P., Lin, M., Manocha, D.: Pledestrians: a least-effort approach to crowd simulation. In: Proceedings of the 2010 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, pp. 119–128. Eurographics Association (2010)
Guy, S.J., Kim, S., Lin, M.C., Manocha, D.: Simulating heterogeneous crowd behaviors using personality trait theory
Haga, S., Sano, A., Sekine, Y., Sato, H., Yamaguchi, S., Masuda, K.: Effects of using a smart phone on pedestrians’ attention and walking. Procedia Manuf. 3, 2574–2580 (2015)
Haworth, B., Usman, M., Berseth, G., Kapadia, M., Faloutsos, P.: On density-flow relationships during crowd evacuation. Comput. Anim. Virtual Worlds 28(3–4), e1783 (2017). https://doi.org/10.1002/cav.1783
Haworth, M.B.: Biomechanical locomotion heterogeneity in synthetic crowds. Ph.D. thesis, York University, Toronto, Canada (2019)
Helbing, D., Molnar, P.: Social force model for pedestrian dynamics. Phys. Rev. E 51(5), 4282 (1995)
Hill, R.: Modeling perceptual attention in virtual humans. In: Proceedings of the 8th Conference on Computer Generated Forces and Behavioral Representation, pp. 563–573. Citeseer (1999)
Itti, L., Koch, C., Niebur, E.: A model of saliency-based visual attention for rapid scene analysis. IEEE Trans. Pattern Anal. Mach. Intell. 11, 1254–1259 (1998)
Jeon, S., Kim, C., Song, S., Lee, G.: Changes in gait pattern during multitask using smartphones. Work 53(2), 241–247 (2016)
Ju, E., Choi, M.G., Park, M., Lee, J., Lee, K.H., Takahashi, S.: Morphable crowds. In: ACM Transactions on Graphics (TOG), vol. 29, p. 140. ACM (2010)
Kapadia, M., Falk, J., Zünd, F., Marti, M., Sumner, R.W., Gross, M.: Computer-assisted authoring of interactive narratives. In: Proceedings of the 19th Symposium on Interactive 3D Graphics and Games, pp. 85–92 (2015)
Kapadia, M., Pelechano, N., Allbeck, J., Badler, N.: Virtual Crowds: Steps Toward Behavioral Realism. Morgan & Claypool Publishers, San Rafael (2015)
Karamouzas, I., Heil, P., Van Beek, P., Overmars, M.H.: A predictive collision avoidance model for pedestrian simulation. In: International Workshop on Motion in Games, pp. 41–52. Springer (2009)
Khullar, S.C., Badler, N.I.: Where to look? Automating attending behaviors of virtual human characters. Auton. Agents Multi Agent Syst. 4(1–2), 9–23 (2001)
Kokkinara, E., Oyekoya, O., Steed, A.: Modelling selective visual attention for autonomous virtual characters. Comput. Anim. Virtual Worlds 22(4), 361–369 (2011)
Kuffner, J.J., Latombe, J.C.: Fast synthetic vision, memory, and learning models for virtual humans. In: Proceedings Computer Animation, pp. 118–127. IEEE (1999)
Lamberg, E.M., Muratori, L.M.: Cell phones change the way we walk. Gait Posture 35(4), 688–690 (2012)
Lee, K.H., Choi, M.G., Hong, Q., Lee, J.: Group behavior from video: a data-driven approach to crowd simulation. In: Proceedings of the 2007 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, pp. 109–118. Eurographics Association (2007)
Licence, S., Smith, R., McGuigan, M.P., Earnest, C.P.: Gait pattern alterations during walking, texting and walking and texting during cognitively distractive tasks while negotiating common pedestrian obstacles. PLoS ONE 10(7), e0133281 (2015)
Maples, W., DeRosier, W., Hoenes, R., Bendure, R., Moore, S.: The effects of cell phone use on peripheral vision. Optom. J. Am. Optom. Assoc. 79(1), 36–42 (2008)
Narang, S., Best, A., Randhavane, T., Shapiro, A., Manocha, D.: PedVR: simulating gaze-based interactions between a real user and virtual crowds. In: Proceedings of the 22nd ACM Conference on Virtual Reality Software and Technology, pp. 91–100. ACM (2016)
Niederer, D., Bumann, A., Mühlhauser, Y., Schmitt, M., Wess, K., Engeroff, T., Wilke, J., Vogt, L., Banzer, W.: Specific smartphone usage and cognitive performance affect gait characteristics during free-living and treadmill walking. Gait Posture 62, 415–421 (2018)
Patten, C.J., Kircher, A., Östlund, J., Nilsson, L.: Using mobile telephones: cognitive workload and attention resource allocation. Accid. Anal. Prev. 36(3), 341–350 (2004)
Pelechano, N., O’Brien, K., Silverman, B., Badler, N.: Crowd simulation incorporating agent psychological models, roles and communication. Technical report. Center for Human Modeling and Simulation, University of Pennsylvania, Philadelphia (2005)
Peters, C., O’Sullivan, C.: Synthetic vision and memory for autonomous virtual humans. In: Computer Graphics Forum, vol. 21, pp. 743–752. Wiley Online Library (2002)
Pizzamiglio, S., Naeem, U., Abdalla, H., Turner, D.L.: Neural correlates of single-and dual-task walking in the real world. Front. Hum. Neurosci. 11, 460 (2017)
Plummer, P., Apple, S., Dowd, C., Keith, E.: Texting and walking: effect of environmental setting and task prioritization on dual-task interference in healthy young adults. Gait Posture 41(1), 46–51 (2015)
Plummer-D’Amato, P., Brancato, B., Dantowitz, M., Birken, S., Bonke, C., Furey, E.: Effects of gait and cognitive task difficulty on cognitive-motor interference in aging. J. Aging Res. 2012 (2012)
Prupetkaew, P., Lugade, V., Kamnardsiri, T., Silsupadol, P.: Cognitive and visual demands, but not gross motor demand, of concurrent smartphone use affect laboratory and free-living gait among young and older adults. Gait Posture 68, 30–36 (2019)
Reynolds, C.W.: Flocks, herds and schools: a distributed behavioral model. SIGGRAPH Comput. Graph. 21(4), 25–34 (1987)
Schabrun, S.M., van den Hoorn, W., Moorcroft, A., Greenland, C., Hodges, P.W.: Texting and walking: strategies for postural control and implications for safety. PLoS ONE 9(1), e84312 (2014)
Tian, Y., Huang, Y., He, J., Wei, K.: What affects gait performance during walking while texting? A comparison of motor, visual and cognitive factors. Ergonomics 61(11), 1507–1518 (2018). https://doi.org/10.1080/00140139.2018.1493153
Xue, Z., Dong, Q., Fan, X., Jin, Q., Jian, H., Liu, J.: Fuzzy logic-based model that incorporates personality traits for heterogeneous pedestrians. Symmetry 9(10), 239 (2017)
Yoshiki, S., Tatsumi, H., Tsutsumi, K., Miyazaki, T., Fujiki, T.: Effects of smartphone use on behavior while walking. Urban Reg. Plan. Rev. 4, 138–150 (2017)
Yu, K.H., Shim, J.H., Choung, S.D., Jeon, H.S.: Effect of using a cell phone on gait parameters in healthy young adults: Texting and texting while listening to music. J. Korean Soc. Phys. Med. 10(4), 25–31 (2015)
Yu, Q., Terzopoulos, D.: A decision network framework for the behavioral animation of virtual humans. In: Proceedings of the 2007 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, pp. 119–128. Eurographics Association (2007)
Zhang, X., Schaumann, D., Haworth, B., Faloutsos, P., Kapadia, M.: Multi-constrained authoring of occupant behavior narratives in architectural design. In: Proceedings of SimAUD (2019)
Zheng, L., Qin, D., Cheng, Y., Wang, L., Li, L.: Simulating heterogeneous crowds from a physiological perspective. Neurocomputing 172, 180–188 (2016)
Funding
Funding was provided by Ontario Research Foundation (Grant No. RE08-054) and National Science Foundation (Grant Nos. IIS-1703883, S&AS-1723869).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Anonymity
Grants are not listed yet for anonymity reasons.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Supplementary material 8 (mp4 39697 KB)
Supplementary material 9 (mp4 24006 KB)
Rights and permissions
About this article
Cite this article
Kremer, M., Haworth, B., Kapadia, M. et al. Modelling distracted agents in crowd simulations. Vis Comput 37, 107–118 (2021). https://doi.org/10.1007/s00371-020-01969-4
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00371-020-01969-4