Modeling Pedestrian and Crowd Behaviour: the case of the Crystals Project

1. Modeling Pedestrian and Crowd Behaviour: the
case of the Crystals Project
Giuseppe Vizzari1,2
1Complex Systems and Artificial Intelligence Research Center
University of Milano-Bicocca
2Crystals Project, Center of Research Excellence in Hajj and Omrah (Hajjcore)
Umm Al-Qura University, Makkah, Saudi Arabia

2. Outline
• The context of application: the Hajj, the Mashaer line and the Arafat I
station
• Groups, as a crowd management concept and a natural, pervasive
presence in pedestrian population
• Groups in the relevant literature
• “In vitro”, “in vivo”, “in silico”: the Crystals Project approach
• Observations about groups (“in vitro” and “in vivo”)
• Modeling and simulation (“in silico”)
• Results in the Arafat I scenario
• Conclusions and future developments

3. Outline
• The context of application: the Hajj, the Mashaer line and the
Arafat I station
• Groups, as a crowd management concept and a natural, pervasive
presence in pedestrian population
• Groups in the relevant literature
• “In vitro”, “in vivo”, “in silico”: the Crystals Project approach
• Observations about groups (“in vitro” and “in vivo”)
• Modeling and simulation (“in silico”)
• Results in the Arafat I scenario
• Conclusions and future developments

4. 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

5. 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

6. Observations at the Hajj

7. Outline
• The context of application: the Hajj, the Mashaer line and the Arafat I
station
• Groups, as a crowd management concept and a natural,
pervasive presence in pedestrian population
• Groups in the relevant literature
• “In vitro”, “in vivo”, “in silico”: the Crystals Project approach
• Observations about groups (“in vitro” and “in vivo”)
• Modeling and simulation (“in silico”)
• Results in the Arafat I scenario
• Conclusions and future developments

8. 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

9. 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

10. 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

11. Outline
• The context of application: the Hajj, the Mashaer line and the Arafat I
station
• Groups, as a crowd management concept and a natural, pervasive
presence in pedestrian population
• Groups in the relevant literature
• “In vitro”, “in vivo”, “in silico”: the Crystals Project approach
• Observations about groups (“in vitro” and “in vivo”)
• Modeling and simulation (“in silico”)
• Results in the Arafat I scenario
• Conclusions and future developments

12. 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

13. Groups in the literature -
Modeling and
Simulation
• Extensions to the social force model
• Helbing, Theraulaz et al. 2009, 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 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)

14. Outline
• The context of application: the Hajj, the Mashaer line and the Arafat I
station
• Groups, as a crowd management concept and a natural, pervasive
presence in pedestrian population
• Groups in the relevant literature
• “In vitro”, “in vivo”, “in silico”: the Crystals Project approach
• Observations about groups (“in vitro” and “in vivo”)
• Modeling and simulation (“in silico”)
• Results in the Arafat I scenario
• Conclusions and future developments

15. The Crystals Project Approach
“In silico”
“In vitro” “In vivo”

16. Outline
• The context of application: the Hajj, the Mashaer line and the Arafat I
station
• Groups, as a crowd management concept and a natural, pervasive
presence in pedestrian population
• Groups in the relevant literature
• “In vitro”, “in vivo”, “in silico”: the Crystals Project approach
• Observations about groups (“in vitro” and “in vivo”)
• Modeling and simulation (“in silico”)
• Results in the Arafat I scenario
• Conclusions and future developments

17. Experiments in
Tokyo
• Experiments carried out by the
Research Center on Advanced
Science and Technology of The
University of Tokyo
• Aimed at evaluating the impact of the
presence of groups in experimental
situations
• Specifically their impact on the
formation of lanes and total
travel times in relatively high
density situations
• Results still not published...
• ... However, we can already say that
more experiments and observations
are needed to draw conclusions
• The influence of groups is not
trivial

18. 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

19. Vittorio Emanuele II
Gallery, Milan
• Popular commercial-touristic
walkway in Milan’s city centre
• Goals of the survey:
• level of density and walkway level
of service (A and B);
• presence of groups (over 84%);
• group size and proxemics spatial
patterns, trajectories and walking
speed (groups are slower but
their trajectories are shorter);
• group proxemics dispersion (they
preserve cohesion, even if
large ones occupy more space)
• still hard to evaluate spatial
arrangement of group members
Group
dispersion
Couples Triples 4 Members
Distance
Centroid
0.58 m
(sd 0,22)
0.76 m
(sd 0,11)
0.67
(sd 0.12)

20. Outline
• The context of application: the Hajj, the Mashaer line and the Arafat I
station
• Groups, as a crowd management concept and a natural, pervasive
presence in pedestrian population
• Groups in the relevant literature
• “In vitro”, “in vivo”, “in silico”: the Crystals Project approach
• Observations about groups (“in vitro” and “in vivo”)
• Modeling and simulation (“in silico”)
• Results in the Arafat I scenario
• Conclusions and future developments

21. A model considering
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)
• A notion of group has been introduced
• To generate a generalised effect of
cohesion among members of
groups
• ... able to overcome goal
orientation for certain types of
groups (e.g. families, close friends)
• Speed heterogeneity also introduced
(poster on Monday afternoon)

22. A few formal details
• Stochastic choice of destination cell; for each cell c, the probability of choosing
an action a leading to it is
• The “utility” value of the cell is defines as follows:
where
• Goal is associated to the static floor field and Obs to the wall potential
• Sep is associated to the proxemic repulsion
• D is an inertia factor
• Over regulates the possibility of having two pedestrians sharing the same cell in
case of high density
• Coh and Inter represent group cohesion factors respectively for small simple
groups and large potentially structured groups

23. Overlapping
• Overlapping is a transient
situation in which pedestrians
share the same cell
• ... it can sometimes be
observed in counterflow
situations in which there is not
enough space for avoidance
• It can only happen if local
density exceeds a given
threshold
• The choice is still penalised
(Over ≤ 0)
• No more than two pedestrians
can share a single cell
[Kretz et al., 2006]

24. Simple and
structured groups
• Simple groups are made up of family
members, friends, people that know each
other
• They often adapt their behaviour to
preserve the cohesion of the group
• Large groups can include perfect
strangers that share for some time a
common goal
• Members of this group have a tendency
to stay close to each other...
• ... but this tendency is not so strong to
prevent group fragmentation
• And generally they are actually
structured (they can include other -
often simple - groups), so we call them
structured

25. • Multipliers of the different components of movement “utility” are adjusted
according to the state of the group
• The dispersion of the group causes an increased impact of simple group
cohesion and a reduced effect of goal attraction (static floor field)
Adaptive group cohesion mechanism

26. Modelling groups - some qualitative results
Counterflow of two structured groups including simple groups of various size, in a 2.4 m wide corridor

27. Aggregate effects of groups
Counterflow of two structured groups including simple groups of various size, in a 2.4 m wide corridor;
shuffled sequential update - ongoing tests with parallel update strategy

28. Aggregate effects of
groups analysed
• 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)

29. Effectiveness of simple group cohesion
mechanism
Counterflow of two structured groups including simple groups of various size, in a 3.6 m wide corridor
(Dispersion measured in terms of area covered by the group)

30. Additional results in “experimental” scenarios: T
junction
Plot of experimentally observed data
[Zhang et al., 2012]
[Vizzari et al., 2013]

31. Outline
• The context of application: the Hajj, the Mashaer line and the Arafat I
station
• Groups, as a crowd management concept and a natural, pervasive
presence in pedestrian population
• Groups in the relevant literature
• “In vitro”, “in vivo”, “in silico”: the Crystals Project approach
• Observations about groups (“in vitro” and “in vivo”)
• Modeling and simulation (“in silico”)
• Results in the Arafat I scenario
• Conclusions and future developments

32. A sample simulation in the Arafat I station

33. Hajj case study: two vs. three groups

34. Hajj case study: normal vs. obstacle

35. Hybrid Agent Architecture
OPERATIONAL
LEVEL
WALKING
INTERACTION WITH
OTHER TRAFFIC
PERFORMING
ACTIVITY
BODY
STRATEGICAL
LEVEL
TACTICAL
LEVEL
CHOICE OF
ACTIVITIES
SCHEDULE OF
ACTIVITIES
CHOICE OF
ACTIVITY AREA
ROUTE CHOICE
MIND
REACTIVECOGNITIVE

36. Additional Annotation Tools

37. Cognitive Map

38. Knowledge: Body + Mind

39. AGENT LIFE-CYCLE
BODY
MIND
Perception
Perception &
Choose
movement
Self
Localization
Wayfinding
Change
Pathfield
intermediate
destination?
Next Plan's
Instruction
yes
yes
no
Plan
Translation
no
Move
(if possible)
next turn
got lost or don't know
how to reach the goal?
BODY
Perception
Choose
movement
Move
(if possible)
next turn
• Plan Building
• Plan Management
• Actuation

40. Sample simulation considering crowd
management procedures

41. Dynamically managing The tactical level:
Introduction to the paths tree
• Given an arbitrary environment, the agent should
be able to plan a path toward its target,
considering:
• The types of environment that will be crossed
 static elements
• The emergence of congestion or other
elements influencing the path conditions 
dynamic elements
• The choice among paths is performed according
to the expected traveling time, dynamically
changing.
• The decision tree contains the average traveling
time of each minimal path to a destination,
estimated by considering static elements and the
average speed of the agents.

42. An evacuation of a large population of
pedestrians
1000agentsat~10p/sec
1000agentsat~10p/sec
Step 50 Step 200
Step 350 Step 500

43. Quantitative results

44. Outline
• The context of application: the Hajj, the Mashaer line and the Arafat I
station
• Groups, as a crowd management concept and a natural, pervasive
presence in pedestrian population
• Groups in the relevant literature
• “In vitro”, “in vivo”, “in silico”: the Crystals Project approach
• Observations about groups (“in vitro” and “in vivo”)
• Modeling and simulation (“in silico”)
• Results in the Arafat I scenario
• Conclusions and future developments

45. Conclusions and
discussion
• Groups are relevant and significant
• Results of simulations are partly validated
• Fundamental diagram and spatial
utilisation in tune with results from the
literature… without groups
• Group cohesion mechanism generates
results about dispersion that are in tune
with Vittorio Emanuele Gallery’s
observation…
• … but we don’t have data about groups
in high density situations (and it’s hard to
obtain such data)
• More observations, experiments and
simulations are necessary to improve our
understanding of the phenomenon
• Closer collaboration between researchers
working on synthesis and analysis of
crowds is promising and possibly beneficial
for both

46. Future works
• Of course, improvements...
• of the model, of our understanding about the phenomena...
• Of course, additional applications to real world scenarios...
• for providing additional success stories and collecting additional issues,
limits, directions for improvements
• Strengthening the connections with automated analysis/computer vision
• Exploiting the model for supporting smart environment, smart city systems
• In the vein of what was discussed by Ulrich Wagoum for stadium
evacuation assistant, Georgios Sirakoulis work on anticipative
technologies and robotic evacuation assistant...

48. ありがとうございます。 Giuseppe Vizzari