Probing crowd density through smartphones in city-scale mass gatherings

EPJ Data Science

Volumn 2, Issue 1, 2013, Pages 1-24

  Wirz, Martin ^a   Franke, Tobias ^b   Roggen, Daniel ^a   Mitleton Kelly, Eve ^c   Lukowicz, Paul ^b   Tröster, Gerhard ^a  

^a ETH ZURICH   (Switzerland)

^b GERMAN RESEARCH CENTER FOR ARTIFICIAL INTELLIGENCE DFKI   (Germany)

^c LONDON SCHOOL OF ECONOMICS   (United Kingdom)

Author keywords

Crowd density estimation; Crowd sensing; Participatory sensing; Pedestrian behavior; Smartphone

Indexed keywords

HUMAN COMPUTER INTERACTION; LOCATION; VIDEO CAMERAS;

CALIBRATION ERROR; CROWD DENSITY; CROWD SENSING; LOCATION INFORMATION; LOCATION-AWARE; PARTICIPATORY SENSING; PEDESTRIAN BEHAVIOR; WALKING SPEED;

SMARTPHONES;

EID: 84933517822     PISSN: None     EISSN: 21931127     Source Type: Journal    
DOI: 10.1140/epjds17     Document Type: Article

References (65)

1. BBC News (2011) Royal wedding: in numbers. http://www.bbc.co.uk/news/uk-13248642
2. Clarin.com (2010) Dos millones de personas, en un cierre inolvidable. http://edant.clarin.com/diario/2010/05/25/um/m-02199900.htm
3. RTVE (2010) Dos millones de personas recibieron a la Selección Española de Fútbol en Madrid.http://www.rtve.es/alacarta/videos/television/dos-millones-personas-recibieron-a-seleccion-espanola-futbolmadrid/828627/
4. Helbing D, Mukerji P (2012) Crowd disasters as systemic failures: analysis of the love parade disaster EPJ Data Sci 1:7. http://www.epjdatascience.com/content/1/1/7
5. Sime J (1995) Crowd psychology and engineering. Saf Sci 21:1-14
6. Tarlow P (2002) Event risk management and safety, vol 4. Wiley, New York
7. Getz D (2007) Event studies: theory, research and policy for planned events. Elsevier, Amsterdam
8. Johansson A, Batty M, Hayashi K, Al Bar O, Marcozzi D, Memish ZA (2012) Crowd and environmental management during mass gatherings. Lancet Infect Dis 12(2):150-156
9. Helbing D, Buzna L, Johansson A, Werner T (2005) Self-organized pedestrian crowd dynamics: experiments, simulations, and design solutions. Transp Sci 39:1-24
10. Hughes RL (2003) The flow of human crowds. Annu Rev Fluid Mech 35:169-182. http://www.annualreviews.org/doi/abs/10.1146/annurev.fluid.35.101101.161136.
11. Smelser NJ (1963) Theory of collective behavior
12. Nicholson C, Roebuck B (1995) The investigation of the Hillsborough disaster by the health and safety executive. Saf Sci 18(4):249-259
13. Au S, Great Britain H, Staff SE, Health GB, Executive S, Ltd RC (1993) Managing crowd safety in public venues: a study to generate guidance for venue owners and enforcing authority inspectors. HSE contract research report, HSE Books. http://books.google.ch/books?id=3osbPwAACAAJ
14. Wirz M, Franke T, Roggen D, Mitleton-Kelly E, Lukowicz P, Tröster G (2012) Inferring and visualizing crowd conditions by collecting GPS location traces from pedestrians’ mobile phones for real-time crowd monitoring during city-scale mass gatherings. In: Collaboration technologies and infrastructures (WETICE), 21st international conference on. IEEE Press, New York
15. Batty M, Desyllas J, Duxbury E (2003) The discrete dynamics of small-scale spatial events: agent-based models of mobility in carnivals and street parades. Int J Geogr Inf Sci 17(7):673-697
16. Lee R, Hughes R (2005) Exploring trampling and crushing in a crowd. J Transp Eng 131:575
17. Hsieh Y, Ngai K, Burkle F Jr, Hsu E (2009) Epidemiological characteristics of human stampedes. Disaster Med Public Health Prep 3(4):217
18. Burkle F, Hsu E (2011) Ram Janki temple: understanding human stampedes. Lancet 377(9760):106-107
19. Krausz B, Bauckhage C (2012) Loveparade 2010: automatic video analysis of a crowd disaster. Comput Vis Image Underst 116(3):307-319
20. Helbing D, Johansson A, Al-Abideen H (2007) Dynamics of crowd disasters: an empirical study. Phys Rev E 75(4):046109
21. Krausz B, Bauckhage C (2011) Analyzing pedestrian behavior in crowds for automatic detection of congestions. In: Computer vision workshops (ICCV workshops), 2011 IEEE international conference on. IEEE Press, New York, pp 144-149
22. Johansson A, Helbing D, Al-Abideen HZ, Al-Bosta S (2008) From crowd dynamics to crowd safety: a video-based analysis. ArXiv e-prints
23. Fruin J (1981) Crowd disasters - a systems evaluation of causes and countermeasures. Inc. US National Bureau of Standards, pub. NBSIR, 81-3261
24. Gong S, Loy CC, Xiang T (2011) Security and surveillance. In: Moeslund TB, Hilton A, Krüger V, Sigal L (eds) Visual analysis of humans. Springer, London
25. Jacques J Jr, Musse S, Jung C (2010) Crowd analysis using computer vision techniques. IEEE Signal Process Mag 27:66-77
26. Mehran R, Oyama A, Shah M (2009) Abnormal crowd behavior detection using social force model. In: Computer vision and pattern recognition. IEEE Press, New York
27. Helbing D, Molnar P (1995) Social force model for pedestrian dynamics. Phys Rev E 51:4282-4286
28. Steffen B, Seyfried A (2010) Methods for measuring pedestrian density, flow, speed and direction with minimal scatter. Phys A, Stat Mech Appl 389(9):1902-1910
29. Eagle N, Pentland A (2006) Reality mining: sensing complex social systems. Pers Ubiquitous Comput 10(4):255-268
30. LaMarca A, Chawathe Y et al (2005) Place lab: device positioning using radio beacons in the wild. In: Pervasive computing
31. Calabrese F, Colonna M, Lovisolo P, Parata D, Ratti C (2011) Real-time urban monitoring using cell phones: a case study in Rome. IEEE Trans Intell Transp Syst 12:141-151
32. Becker R, Caceres R, Hanson K, Loh J, Urbanek S, Varshavsky A, Volinsky C (2011) A tale of one city: using cellular network data for urban planning. IEEE Pervasive Comput 10(4):18-26
33. Couronne T, Olteanu Raimond A, Smoreda Z (2011) Looking at spatiotemporal city dynamics through mobile phone lenses. In: Network of the future, international conference on the. IEEE Press, New York
34. Calabrese F, Pereira F, Di Lorenzo G, Liu L, Ratti C (2010) The geography of taste: analyzing cell-phone mobility and social events. In: Pervasive computing. Lecture notes in computer science, vol 6030. Springer, Berlin, pp 22-37
35. Kim D, Kim Y, Estrin D, Srivastava M (2010) Sensloc: sensing everyday places and paths using less energy. In: Proc. of the 8th ACM conference on embedded networked sensor systems. ACM, New York
36. Van Diggelen F (2009) A-GPS: assisted GPS, GNSS, and SBAS. Artech House, Norwood
37. Azizyan M, Constandache I, Choudhury RR (2009) SurroundSense: mobile phone localization via ambience fingerprinting. In: Proceedings of the 15th annual international conference on mobile computing and networking, MobiCom ’09. ACM, New York, pp 261-272
38. Koshak N, Fouda A (2008) Analyzing pedestrian movement in mataf using gps and gis to support space redesign. In: The 9th international conference on design and decision support systems in architecture and urban planning
39. Versichele M, Neutens T, Delafontaine M, de Weghe NV (2012) The use of bluetooth for analysing spatiotemporal dynamics of human movement at mass events: a case study of the Ghent festivities. Appl Geogr 32(2):208-220
40. Bandini S, Federici ML, Manzoni S (2007) A qualitative evaluation of technologies and techniques for data collection on pedestrians and crowded situations. In: Proceedings of the 2007 summer computer simulation conference, SCSC. Society for Computer Simulation International, San Diego, pp 1057-1064
41. Marana A, Da Fontoura Costa L, Lotufo R, Velastin S (1999) Estimating crowd density with Minkowski fractal dimension. In: Acoustics, speech, and signal processing, IEEE international conference on, vol 6, pp 3521-3524
42. Ma R, Li L, Huang W, Tian Q (2004) On pixel count based crowd density estimation for visual surveillance. In: Cybernetics and intelligent systems, IEEE conference on, vol 1. IEEE Press, New York, pp 170-173
43. Wu X, Liang G, Lee K, Xu Y (2006) Crowd density estimation using texture analysis and learning. In: Robotics and biomimetics, ROBIO’06, IEEE international conference on. IEEE Press, New York, pp 214-219
44. Jones M, Snow D (2008) Pedestrian detection using boosted features over many frames. In: Pattern recognition, ICPR 2008, 19th international conference on. IEEE Press, New York, pp 1-4
45. Brostow G, Cipolla R (2006) Unsupervised Bayesian detection of independent motion in crowds. In: Computer vision and pattern recognition, IEEE computer society conference on, vol 1. IEEE Press, New York, pp 594-601
46. Reades J, Calabrese F, Sevtsuk A, Ratti C (2007) Cellular census: explorations in urban data collection. IEEE Pervasive Comput 6(3):30-38
47. Morrison A, Bell M, Chalmers M (2009) Visualisation of spectator activity at stadium events. In: Information visualisation, 13th international conference. IEEE Press, New York, pp 219-226
48. Weidmann U (1992) Transporttechnik der Fussgänger: Transporttechnische Eigenschaften des Fussgängerverkehrs (Literaturauswertung). IVT, Zürich
49. Helbing D (2009) Derivation of a fundamental diagram for urban traffic flow. Eur Phys J B, Condens Matter Complex Syst 70(2):229-241
50. Jelić A, Appert-Rolland C, Lemercier S, Pettré J (2011) Properties of pedestrians walking in line-fundamental diagrams. Arxiv preprint arXiv:1111.5708
51. Daamen W, Hoogendoorn S (2003) Experimental research of pedestrian walking behavior. Transp Res Rec 1828:20-30
52. Zhang J, Klingsch W, Schadschneider A, Seyfried A (2012) Ordering in bidirectional pedestrian flows and its influence on the fundamental diagram. J Stat Mech Theory Exp 2012:P02002
53. Chattaraj U, Seyfried A, Chakroborty P (2009) Comparison of pedestrian fundamental diagram across cultures. ArXiv e-prints
54. Smith R (1995) Density, velocity and flow relationships for closely packed crowds. Saf Sci 18(4):321-327
55. Johansson A (2009) Constant-net-time headway as a key mechanism behind pedestrian flow dynamics. Phys Rev E 80(2):026120
56. Seyfried A, Steffen B, Lippert T (2006) Basics of modelling the pedestrian flow. Phys A, Stat Mech Appl 368:232-238
57. Fang Z, Lo S, Lu J (2003) On the relationship between crowd density and movement velocity. Fire Saf J 38(3):271-283
58. Seyfried A, Steffen B, Klingsch W, Boltes M (2005) The fundamental diagram of pedestrian movement revisited. J Stat Mech Theory Exp 2005:P10002
59. Schadschneider A, Klingsch W, Klüpfel H, Kretz T, Rogsch C, Seyfried A (2008) Evacuation dynamics: empirical results, modeling and applications. Arxiv preprint arXiv:0802.1620
60. Wiseman R (2008) Quirkology: the curious science of everyday lives. Pan, London
61. Wirz M, Roggen D, Tröster G (2010) User acceptance study of a mobile system for assistance during emergency situations at large-scale events. In: Human-centric computing (HumanCom), 3rd international conference on. IEEE Press, New York, pp 1-6
62. Warburton K, Lazarus J (1991) Tendency-distance models of social cohesion in animal groups. J Theor Biol 150(4):473-488
63. Moussaid M, Garnier S, Theraulaz G, Helbing D (2009) Collective information processing and pattern formation in swarms, flocks, and crowds. Top Cogn Sci 1(3):469-497
64. Willis A, Gjersoe N, Havard C, Kerridge J, Kukla R (2004) Human movement behaviour in urban spaces: implications for the design and modelling of effective pedestrian environments. Environ Plan B, Plan Des 31(6):805-828
65. Wirz M, Schläpfer P, Kjærgaard M, Roggen D, Feese S, Tröster G (2011) Towards an online detection of pedestrian flocks in urban canyons by smoothed spatio-temporal clustering of GPS trajectories. In: Proceedings of the 3rd ACM SIGSPATIAL international workshop on location-based social networks. ACM, New York