empirical investication on pedestrian crowd dynamics and grouping

Empirical Investigation on Pedestrian Crowd Dynamics and Grouping

Andrea Gorrini1, Stefania Bandini2, Giuseppe Vizzari2

1 Information Society Ph.D. Program, Department of Sociology and Social Research University of Milano-Bicocca, Italy

2 Complex Systems and Artificial Intelligence Research Center (CSAI)University of Milano-Bicocca, Italy

http://www.alias.disco.unimib.it/abstracts-phd-course.html

TGF 2013 - Jülich Supercomputing Centre - Sept. 25-27, 2013

Outline

• Why observing groups? Motivations and fundamental research question

• Available literature, data and observations on group influence on pedestrian behaviour

• An observation and analysis of group influence in Vittorio Emanuele II Gallery in Milano

• Towards an interdisciplinary research on pedestrian and crowd analysis and synthesis

• Conclusions and discussion



Crowds of pedestrians as complex systems

• Overall system behaviour depends on individuals’ decisions and actions…• … that are generally influenced

by a large number of factors• … intertwined in an often

unpredictable way• Mixed and conflicting mechanisms

• Competition for the shared space…

• … but also cooperation (non written social norms) to prevent stall situations

• Imitation...• ... but also natural tendency to

stay at a distance (proxemics)• Emergent phenomena • …


Impact of groups in pedestrian and crowd dynamics

• Current approaches to modeling and simulation generally consider every pedestrian as a individual with almost no relationships• Considering only his/her own

goals• Considering other pedestrians

as moving obstacles or movement opportunities

• Nonetheless, in several situations pedestrians are bound by relationships influencing their movement• Generally speaking, a crowd is

made up of groups of pedestrians...

• What do we miss by neglecting this aspect of pedestrian behaviour?


Groups in the literature - Observations

• At least two studies report observations about groups

• 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" Environment and Planning B: Planning and Design 31(6) 805 – 828

• Michael Schultz, Christian Schulz, and Hartmut Fricke. “Passenger Dynamics at Airport Terminal Environment”, Pedestrian and Evacuation Dynamics 2008, Springer-Verlag, 2010

• Observations carried out in low density conditions

• Groups of small size were most frequently observed

• Little data about dynamic group proxemic behaviour


Admission test University of Milano-Bicocca

• Admission test of the Faculty of Psychology at the University of Milano-Bicocca - September 1, 2011

• Counting activity supported by video footages of the event

• About two thousand students attended the test• About 34% individuals, 50%

couples, 13% triples and 3% groups of 4 members (!)

• Statistically validated relationship between group size and velocity• Additional quantitative analyses

about the arrival and entrance process, LOS

• Qualitative analysis of group shapes and related phenomena

• More details in PED and ACRI (C&CA) 2012 papers



Scenario Analysis The Vittorio Emanuele II gallery is a popular commercial-touristic walkway situated in the Milan city centre; it represents an optimal scenario for video recording pedestrian flows



Data CollectionThe survey was performed the 24th of November 2012 from 2:50 pm to 4:10 pm. Thanks to the official authorization of the Municipality of Milan, the video footages

were performed from the balcony of the gallery; the staff was composed of four

observers; the equipment consisted of two video-camera with tripods



Data Analysis The survey was aimed at collecting data about: level of density and walkway level of

service; presence of groups; group size and proxemics spatial patterns; trajectories;

walking speed; group proxemics dispersion



Data Reduction and Analysis A selected portion of the gallery was considered for the analyses (12.8m – 12.8m). A grid of square cells (designed by using Adobe Photoshop CS5) was used in order

to discretize the environment in cells and to perform data analyses



1. Results – Fruin’s LOS The bidirectional pedestrian flows were measured every minute; the total flow was composed of 7773 people; the level of density was low; the average walkway

level of service corresponded to the B level (7.78 ped/min/m) that correspond to an irregular flow in low density situations



2. Results – Presence of Groups The video was sampled considering one minute every five: a subset of 15 minutes

was extracted (1645 people - 21.16% of the total); the presence of groups (84.19%), their size and proxemics arrangements were detected

Patterns Couples Triples ≥ 4 Members

Lane 94.43% 31.91% 29.61%

River 5.57% 9.57% 3.12%

V-like - 58.51% 10.39%

Rhombus - - 7.79%

Two Dyads - - 32.47%

Triad + Single - - 10.39%

Single + Triad - - 6.23%



3. Results – Walking Path and Speed A sample of 30 singles, 15 couples, 10 triples and 8 groups of four member was

considered related to the B level of service. Data analysis was aimed at checking any differences in walking path and speed between singles and group members

Singles Couples Triples 4 Members

Walking Speed 1.22 m/sec (sd 0.16)

0.92 m/sec(sd 0.18)

0.73 m/sec(sd 0.10)

0.65 m/sec(sd 0.04)

Path 13.96 m(sd 1.11)

13.39 m(sd 0.38)

13.45 m(sd 0.27)

13.16 m(sd 0.43)



Identification of groups (and elderlies)


3.1 Results – Trajectories and Path Within B level of service the differences in walking path between singles-couples and

singles-triples were significant (t-test, p < 0.05); no significant difference in path

between couple-triples (p > 0.05). The path of singles is 4.48% longer the the average

path of group members

Singles Couples Triples 4 Members



3.2 Results – Walking Speed Within B level of service the differences in walking speed between singles-couples,

singles-triples, singles-4members, couples-triples and triples-4 members were

significant (t-test, p < 0.01). The average walking speed of group members is 37.21%

lower than the one of singles



4.1 Results – Proxemics Dispersion Within B level of service situations the differences in proxemics group dispersion

(distance from the centroid of the group) between couples-triples and couples-4

members was significant (t-test, p < 0.01). The average spatial dispersion of triples and

groups of 4 members is 40.97% higher than the one of couples

Couples Triples 4 Members

DistanceCentroid

0.58 m(sd 0,22)

0.76 m(sd 0,11)

0.67(sd 0.12)



4.2 Results – Proxemics Dispersion The normalized position of each pedestrian with respect to the centroid and the

movement direction show that couples tend to walk with a line-abreast layout and a

distance of 0.4 m; triples tend to walk with a line-abreast pattern of 0.6 m (from left to

right members); no particular pattern regarding groups of 4 members can be detected


Couples Triples

Groups of 4


Towards integrated analysis and synthesis?


Model and simulator

Target system

Simulation results

Empirical data

Simulation campaignexecution

Modellingand design of

a simulator

Analysis ofresults and

interpretation

Analysis of thedynamics of target

system

Synthesis

Analysis

(i) Formalisation ofphenomenologies

(ii) Metrics, indicators,techniques

(i) Motivations and goalsfor model innovation(ii) Data for calibration

and validation


Towards integrated analysis and synthesis?



Conclusions and discussion

• Groups are relevant and significant

• Models for the simulation of crowds of pedestrians focused on collective events should consider them

• More observations, experiments and simulations are necessary to improve our understanding of the phenomenon

• More tight collaboration between researchers working on synthesis and analysis of crowds is promising and possibly beneficial for both

Grazie dell’attenzione! Thanks for your attention! Giuseppe Vizzari

empirical investication on pedestrian crowd dynamics and grouping

Science