An Agent Based Model to model pedestrians interactions with the environment. Poster

1. Using Agent Based Modeling to model PModel bey : Alirdeza Kardeuni , Fsinal Protjectr for “iComaplexitny Based MoWdels” Classa , Profeyssor : Mfioira Zenlner ding
ABM
Agent Based Modeling is used to
simulate acons and interacons of
autonomous agents in complex
systems.
Complex Systems?
Ÿ It’s difficult or impossible to predict
complex systems.
Ÿ Complex systems could be organized
or disorganized.
Ÿ Properes of these systems emerge
from interacons between their
elements.
Ÿ C o m p l ex sy ste m s c o u l d h ave
different behaviors to different
situaons.
Ÿ
Why ABM?
Ÿ By using ABM we could understand
some of the behaviors in these
complex systems.
Ÿ Understanding how a complex
system such as a transportaon
network works can help us to create
robust plans and policies that address
the complexity of these systems
Pedestrians constantly
use informaon to
navigate the urban
space and find their
desnaon.
The Process of Wayfinding
Ÿ The answers to these quesons are
found from :
Ÿ Other People, The environment, Maps,
Signage and ...
Number of blocks in
the X and Y direction
Density of
Destinations
Percentage
of Important
(Major) Destinations
Number of people
in the streets
Percentage of
Residents
(pedestrians with
knowledge)
make the rest
pedestrians
(Tourists)
percentage of
residents’ knowledge
of destinations.
The radius in which
the pedestrians look
for destinations and
other people
Add or remove
signs by clicking on an
intersection
Set up signage at a
defined percentage
of intersections
Set up streets and
Bocks
Set up destinations
at random locations
Randomly define
major destinations
Place pedestrians
and residents at
random locations
on the streets
Set two random
destinations as
a pedestrians trip plan
put a percentage of
destinations in residents
knowledge list
Should pedestrians? have
perfect information ?
Set pedestrians initial
knowledge list empty
Let each pedestrian
know all the destinations
Should pedestrians
have perfect
information ?
No Yes
Setup Stage
Setup Environment Setup People Setup Signage
Go
Is your destination
on your knowledge list?
Walk Randomly
NNoo
YYeess
Move forward
one ( distance
unit )
NNoo YYeess
Is any resident
in your search
radius?
Ask Questions
Does the resident/or
signage have
your destination in his
knowledge list ?
NNoo YYeess
Move to your
destination
Move forward
one ( distance
unit )
Put it in your
knowledge list
Stop
Everyone are at
their destination?
NNoo YYeess
Stop the Model
Calculate travel statistics for
every pedestrian
Do nothing
Ÿ The wayfinding process is simplified
as a series of quesons pedestrians
asks about how to get to their
desnaon(s).
The Model
Agents and Environment
Do you know Where
Destination 33 is?
Tourist Residents
Tourist
Let’s see
if I can find
destination 45
on this sign!
Do you know Where
Destination 33 is?
46
43
47
66
Before After
Results
Model Process (pseudo Code)
25% Residents with 30% knowledge,no signage
25% Residents with 10% knowledge with
signage on 50 percent of intersections.
Try with different situations yourself!
Examine how different sign policies
effect travel time of pedestrians!