an agent-based approach to pedestrian and group dynamics: experimental and real world scenarios

An Agent-Based Approach to Pedestrian and Group Dynamics: Experimental and Real World Scenarios

Giuseppe Vizzari1,2,3 , Lorenza Manenti1,3, Kazumichi Ohtsuka4 and Kenichiro Shimura4

1Complex Systems and Artificial Intelligence Research Center (CSAI)University of Milano-Bicocca, Italy

2 JSPS Fellow - Research Center on Advanced Science and Technology, The University of Tokyo, Tokyo, Japan

3 Crystals Project, Center of Research Excellence in Hajj and Omrah (Hajjcore)Umm Al-Qura University, Makkah, Saudi Arabia

4 Research Center for Advanced Science & Technology, The University of Tokyo, Japan

Tuesday, August 28, 12

http://www.ia.urjc.es/att2012/papers/att2012_submission_1.pdf






ATT2012 @ AAMAS 2012 - Valencia (ES) - June 5, 2012

Outline

• Pedestrian and crowd simulation, a brief introduction

• Impact of groups in pedestrian and crowd dynamics

• According to the literature

• Observations at the Hajj

• A model considering the presence of groups

• The model in a simple counterflow scenario

• The model in a real-world scenario

• Conclusions and discussion



Motivations ofcrowd modeling and simulation

• Designer’s decision support• Normal and evacuation situations• Positioning of signs• Malls and shopping centers

• Support the study of pedestrian behaviour• Envisioning of different behavioural

models in realistic environments• Possibility to perform ‘in-machina’

experiments• Support crowd management by

means of the elaboration of what-if scenarios

• Decision makers might not be experts in crowds• Need of effective ways to visualize

simulations and analyses of results



Crowds of pedestrians ascomplex 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• …



Types of approaches to pedestrian and crowd modeling

• Particle based

• Social force model and derivatives

• Continuous space and time

• Cellular Automata

• Ad-hoc rules (e.g. Blue & Adler, intersections) or floor field approach (e.g. Nishinari, Schadschneider, ...)

• Discrete in time and space

• Multi-Agent Systems

• Several approaches from computer graphics (e.g. Thalmann, Terzopoulos, Donikian, Manocha), some approaches are extensions of CA, ...

• Behavioural models generally more complex that in CA approaches



Outline











Impact of groups in pedestrian and crowd dynamics

• Current approaches generally consider every pedestrian as a individual with no relationships• Considering only his/her own

goals• Considering other pedestrians as

moving obstacles • 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



Groups in the literature - Modeling and Simulation• Extensions to the social force model

• Moussaïd, Helbing, Theraulaz et al. 2010• Small groups (2,3,4), unstructured• Low to moderate densities• Validation based on actual observations

• Xu and Duh, 2010• Only couples (groups of 2 pedestrians)• Low to moderate densities• Shallow validation based on data from the

literature (Daamen, 2004)• CA models

• Sarmady, Haron, Zawawi Hj, 2009• Leaders and followers• Groups of 2 to 6 members experimented• Not validated

• Agent-based models• Qiu and Hu 2010

• Structured groups (intra and inter group matrices)

• Large groups experimented (60 pedestrians)• Not validated

• Group members tend to stay close to other group members (additional behavioural component)



The Hajj in Brief

• Annual pilgrimage to Makkah, Saudi Arabia

• Fifth pillar of Islam, a religious duty that must be carried out at least once in their lifetime by every able-bodied Muslim who can afford to do so

• Over 2,5 millions of people coming from over 150 countries

• A precise and articulated system of rituals implying the mass movement of pilgrims over several sites that in some cases are about 20 km distant



The Mashaer Line

• Five proposed rail lines connecting the holy sites with one another and with Makkah

• The southern rail includes 9 stations: 3 in Mina, 3 in Muzdalifah and 3 in Arafat, to replace 35,000 cars and buses and access the Haram and Makkah Central Area

• Future lines to the Holy Haram• Extend the southern rail line to

Jeddah Airport, with an elevated alignment above the Jeddah Expressway over an 80 Km length


Observations at the Hajj - Groups as a crowd management organizational instrument

•Pilgrims are subdivided into groups of 250 persons following a leader in their movement from the nearby tents area to the platform

•The waiting boxes act as waiting areas hosting groups waiting to use ramps or elevators

•The platform can safely host even more than 3000 pilgrims (the capacity of a train), but the process is aimed at avoiding overcrowding of the platform



Observations at the Hajj - Considerations

• Groups are used as an organizational instrument to manage crowd

• Group arrival is planned, scheduled

• Leaders decide when and where to move, collaborating with station officers

• Their size is relatively large, their cohesion is not extreme...

• ... but inside them smaller sub-groups can be identified and they can be much more compact

• Groups have different intermediate movement targets, although the same final goal



Group influence in general - Considerations

• The presence of groups is pervasive in many events involving large crowds

• Groups are simply out there...

• ... it’s not a matter of deciding if they’re ‘good’ or ‘bad’ for the pedestrian flow

• ... it’s a matter of understanding their impact, in different relevant conditions

• The presence of groups should be carefully considered:

• Design choices might make it difficult for a group to preserve its cohesion, which is particularly significant in certain situations (e.g. kids, elderly, mobility impaired persons)...

• ... and this would cause stress in group members and congestions, delays in the whole system



Outline











A model considering the presence of groups

• Based on the floor-field CA approach, with significant difference on movement choice

• Employing traditional factors for movement destination choice• Goal orientation• Presence of obstacles• Presence of other pedestrians

(basic proxemics)• We added a simple notion of group

• A simple set of pedestrians• We added a factor to the movement

destination choice-making activity• The presence of a group member

nearby is considered positively• Notice that this factor alone does not

assure that a group does not split!

Considered factors:+ cell is closer to pedestrian's goal+ presence of group members nearby- presence of other pedestrians nearby- presence of obstacles nearby+ random factor

Movement blocking factors:- cell is occupied by another pedestrian- cell is occupied by an obstacle



Outline











The model in a simple counterflow scenario



The model in a simple counterflow scenario

• We can interpret the results making considering two phenomena

1. Wide groups offer a large profile to the counter flow, so they have a higher probability of facing conflicts

2. Once a group has formed a line, instead, the leader has the same conflict probability of an individual, but the follower has often an advantage

• In low density situations phenomenon (1) prevails, leading to a lower average combined flow for groups of pedestrians whose size is larger than 2• Pairs in fact can easily form a line,

turning phenomenon (1) to (2)• In high density situations the probability

of facing conflicts is very high also for individuals, so phenomenon (2) prevails, leading to higher average combined flow for even large groups (size 5)



Additional results - group cohesion

• The simple cohesion mechanism can generate different phenomenologies

• Experiments with an extension of the previous model (having a more complex perception model for pedestrians) can lead to different situations

• Groups remain compact

• Groups split but reunites

• Groups split and cannot reunite

• A metric of group dispersion was defined and employed to quantify this phenomenon



Outline











Preliminary results in the Hajj case study

• Compared three scenarios (columns), characterized by:• One group accessing the station

from one WB• Two groups simultaneously

accessing the station from two WBs

• Three groups simultaneously accessing the station from two WBs and from the tents area

• The diagrams respectively show different data for cells• Blocks, situations in which a

pedestrian wanted to move but couldn’t (1st row)

• Movements of a pedestrian from the cell (2nd row)

• Space utilization (sum of the above) (3rd row)



Outline











Conclusions and discussion

• Groups are relevant and significant• Models for the simulation of crowds

of pedestrians focused on collective events should consider them

• Results of first simulations, in tune with experiments carried out last year in Tokyo, suggest that the impact of groups is not so simple to evaluate

• 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 (e.g. computer vision) is promising and possibly beneficial for both


ありがとうございます。 Giuseppe Vizzari


an agent-based approach to pedestrian and group dynamics: experimental and real world scenarios

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