The 2nd International Conference on Informatics, Engineering, Sciences and Technology, 18 July 2019, Bandung, Indonesia

1. 18 July 2019
Bandung, Indonesia
The 2nd International Conference on
Informatics, Engineering, Sciences and
Technology
1
Gravity-driven agent-based model
for simulation of economic growth
of a point along a highway
Tatang Suheri1
, Sparisoma Viridi2
1
Department of Urban and Regional Planning, Universitas Komputer Indonesia,
Bandung 40132, Indonesia
2
Department of Physics, Institut Teknologi Bandung, Bandung 40132, Indonesia
1
tatang.suheri@email.unikom.ac.id, 2
dudung@fi.itb.ac.id
20190714_3

2. 18 July 2019
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The 2nd International Conference on
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Outline
• Introduction
• Simulation
• Results and discussion
• Summaries

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Introduction

4. Highway construction
• Its effect on other sectors are greater com-
pared to the effect of other sectors and after
that the induced economic growth had been
increasing
18 July 2019
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The 2nd International Conference on
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Liu N and Zhou Q-m 2006 Quantitative Analysis of Effects of Transportation Infrastructure Investment on National
Economy Journal of Highway and Transportation Research and Development 5 150

5. Highway improvement
• It induces the emergence of a new set of eco-
nomic opportunities and a change in the pat-
tern of relationships between the environ-
ment and social actors
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Gunasekera K, Anderson W and Lakshmanan TR 2008 Highway-Induced Development: Evidence from Sri Lanka
World Development 36 2371

6. Traffic congestion
• Whether it has impact on slowing economy is
still debateable since a critical disconnect
exists between research and practice
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Sweet M 2011 Does Traffic Congestion Slow the Economy? Journal of Planning Literature 26 391

7. Highway expansion
• The spatial variation in road network and its
driving patterns relating economy and popu-
lation
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Hu X, Wu C, Wang J, Qiu R 2018 Identification of Spatial Variation in Road Network and Its Driving Patterns: Economy
and Population Regional Science and Urban Economics 71 37

8. At a point along a highway
• How is economic growth induced?
• How does relationships pattern between the
environment and social actors change?
• Is traffic congestion good economically?
• How is driving pattern connecting economy
and population?
• How are all seen in micro or individual point of
view?
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9. Agent-based model (ABM)
• In this work the agents will represent vehicles
that pendel between two cities, with possibili-
ty to dock on a rest area
• From time duration an agent spending in a
rest area, economy effect can be predicted
18 July 2019
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10. 18 July 2019
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Simulation

11. Gravity model (GM) in economy
• Interaction force Fij between two cities with
separation distance Dij
with cities property Ai and Aj, constant K
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Faiña A, Lopez-Rodríguez J 2003 Population Potentials and Development Levels: Empirical Findings in the European
Union in 43rd Congress of the European Regional Science Association (ERSA): "Peripheries, Centres, and Spatial
Development in the New Europe", 27th - 30th August 2003, Jyväskylä, Finland, European Regional Science
Association (ERSA), Louvain-la-Neuve, url http://hdl.handle.net/10419/115910
β
αα
ij
ji
ij
D
AA
KF =

12. Cities properties
• Parameter Ai can represent
– income
– population
– transportation system
– public facilities
– other things that attract people
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13. Driving force and direction matrix
• The force from GM will be the driving force for
ABM, which construct direction matrix
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















=
45556
34567
33077
22187
21118
iD
Direction number:
1 ( ↑ ), 2 ( ↗ ), 3 ( → ),
4 ( ↘ ), 5 ( ↓ ), 6 ( ↙ ),
7 ( ← ), 8 ( ↖ ), 0 ( ∙ )
Direction where agents
are allowed to move to

14. World matrix
• Agents can only move in 0 area (road, high-
way), where 1 represents obstacle (building,
higway side, etc)
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The 2nd International Conference on
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















=
11111
10001
10101
10001
11111
W

15. Agent matrix
• There could be several types of agents, eg. 1,
2, ..
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















=
00000
00010
02000
00100
00000
A
Agent of type 1 will
behave differently
than type 2, ..

16. Simulation system
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The 2nd International Conference on
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17. • Please visit
https://raw.githack.com/dudung/butiran.js/
master/app/vratcabm/vratcabm.html
Demo
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18. 18 July 2019
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The 2nd International Conference on
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The 2nd International Conference on
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Results and discussion

20. Parameters
• Simulation parameters are as follow
N = 72 (total agents),
N1 = 36, 48, 72 (type 1 agents)
N2 = N – N1 (type 2 agents)
Matrices W (world), D1..D3 (direction), A (agent)
tstop = 0 (00:00), tstart = 75 (06:00),
tmax = 300 (24:00), Δt = 1 (0.08 hour)
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21. Time schedule
• Every day at 00:00 the stoplight is red until
06:00 and then green (not drawn) from 06:00
– 24:00. After 30 tmax or about one month the
simulation is terminated
• Agents can leave their origin cities after 06:00
• If agents enter a city between 24:00 and 06:00
they are forced to rest in the city
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22. Initial configurations
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The red agents must visit rest area,
but not the blue ones

23. Mid configurations
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24. Final configurations
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25. Number of visitors/day (t = 300/day)
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NAB: agents go from city A to B, NBA: agents go from city B to A,
NRA1: agents visiting rest area 1 (A->B), NRA2: rest area 2 (B->A)

26. Agents composition
• Fraction of red agents
c = 0 : all agents are blue (not need rest area)
c = 1 : all agents are red (must visit rest area)
other values are between 0 and 1
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The 2nd International Conference on
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bluered
red
NN
N
c
+
=

27. Daily influence of c
• Daily observation does not show the influence
of c to
– number traveller from A to B (NAB)
– number traveller from B to A (NBA)
– number of visitor to rest area 1 (NRA1)
– number of visitor to rest area 2 (NRA2)
18 July 2019
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28. 18 July 2019
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29. Monthly influence of c
• Monthly observation does show the influence
of c to
– number of visitor to rest area 1 (NRA1)
– number of visitor to rest area 2 (NRA2)
-> NRA1 > NRA2 (nearer is favourable then farther)
but not too strong to
– number traveller from A to B (NAB)
– number traveller from B to A (NBA)
18 July 2019
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30. Travellers/month
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500
550
600
650
700
750
800
0% 20% 40% 60% 80% 100%
N
c
NAB
NBA
Navg
From A
to B
From B
to A

31. Rest area visitors/month
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The 2nd International Conference on
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0
20
40
60
80
100
120
0% 20% 40% 60% 80% 100%
N
c
NRA1
NRA2
Navg
Nearer
rest
area
Farther
rest
area

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Summaries

33. Conclusion
• Variation of initial configurations shows the
influence of composition of agents C in visit-
ing the rest area, if observed data is aggregat-
ed monthly
• Nearer rest area (rest area 1) is also favour-
able than the farther one (rest area 2)
18 July 2019
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34. Future plans
• Make the highways, cities, and rest areas
more realistic but still be able simulated by
ABM with affordable computation facility
• Get observation data from CCTV cameras or
sensors to confirm the simulation results
• Create adjustable time step for better
prediction
18 July 2019
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The 2nd International Conference on
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35. Acknowledgements
• The 2nd INCITEST 2019 Committee and
Universitas Komputer Indonesia for
supporting presentation of this work
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36. 18 July 2019
Bandung, Indonesia
The 2nd International Conference on
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Technology
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https://osf.io/6d5n7/

37. 18 July 2019
Bandung, Indonesia
The 2nd International Conference on
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Thank you