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1
Developing a methodology for network simulation
E*Space ConferenceNaples and Benevento June 2005
Colin Arrowsmith1, Bob Itami2 and Silvester (Sungchan) Kim1
1Department of Geospatial Science, RMIT University
2GeoDimensions Pty. Ltd.
2
Methodology objectives
• to understand spatial behaviour of mobile objects along networks
• to develop typical itineraries for various types of mobile objects
• to model mobile objects along networks given differing environmental conditions
3
Rationale
• predicted increases in traffic flow along networks
• physical constraints results in loss of amenity and threats to safety
• need to test management options under differing scenarios
4
Methodology
• develop inventory of network
• survey design - detection, observation and recording of mobile objects
• developing typical itineraries for dynamic objects
• spatial analyses of movements
• identification of types of dynamic objects
• modelling movements
5
Develop inventory
• base spatial information acts as datum for analyses and modelling
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Survey design – attributes required
• position
• duration
• sequence or “itinerary”
• flow
• speed and orientation
• type of object
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Survey techniques
• questionnaire and interviewing
• video monitoring
• detectors and sensors
• tracking mechanisms including GPS
8
Itinerary determination
• identify network sequences
• classify network sequences
• statistical probability analyses
9
Spatial analyses
• extract topological linkages
• apply segmentation for analyses– duration
– velocity
– diurnal patterns
10
Classification of types
• classification of object types using – cluster or
– data mining techniques
– direct observation
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Simulating movements and behaviour
• agent-modelling– autonomous agents
– linked to GIS
– agent-rules
– wayfinding
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Case study 1 – Loch Ard Gorge
• objective– to identify typical spatial behaviour patterns at a popular
tourist attraction
• rationale– increased visitation to tourist sites with constrained physical
parameters
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Develop inventory for Loch Ard Gorge
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Attractions
• 26 point attractions– lookouts– river– car parks
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Survey design
• GPS survey
• questionnaire survey
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The GPS receivers used
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GPS survey attributes
Attribute Units
point_id integer
survey_id integer
Easting AMG66 metres
Northing AMG66 metres
Date dd/mm/yyyy
Time hour:min:sec
Altitude metres
Leg_length metres
Leg_time seconds
Leg_speed kmph
Bearing Whole degrees
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Topological linkages
4 (3)
19 (7)
18 (7)
16 (6)
17 (6)
12 (4)
15 (5) 10 (4)
11 (3)
8 (2)
7 (4)
6 (4)5 (3)
3 (2)
2 (1)
1 (0)
9 (3)
14 (6)
13 (5)
A
DDC
BG
F
E
I
H
7 (4) Node number (associated number)
Labelled sequence node
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Describing spatial-temporal data
• development of regions to assist in describing movement patterns
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Nodes visited
Number of sequence nodes visited
Number of participants
Average duration (mins)
1 3 65.67
2 21 38.14
3 40 54.20
4 17 67.94
5 10 87.00
6 8 128.00
7 1 111
8 1 105
9 1 212
Average = 3.48 102 65.12
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Visitor typologies
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Simulation modelling
• RBSim3 is a computer model
• maintains a database of visitor experiences through a simulation
• itinerary can be built for an agent
• agent movement is modified by the changing conditions of a network
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RBSim Simulator
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Case study 2 – River Traffic Study
• objectives
• rationale
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Objectives
• to determine the capacity of the Yarra and Maribyrnong rivers to meet growing demands
• identify management systems and infrastructure to control boat traffic in a safe and sustainable manner
• develop a management strategy to control river traffic
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Rationale
• broad range of users and vessels with different patterns of use
• knowledge of impacts of different watercraft on environmental and social conditions is uncertain
• volumes of traffic predicted to increase substantially
• capacity of river has not been defined
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Inventory development
• river depth
• bank conditions
• land and water facilities
• adjacent land use
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Inventory development
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Survey design
• interviews with user groups
• new river counts
• published schedules
• GPS tracking
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GPS Tracking
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Topological linkages
A
KL
B
M
C
B1 F
G
D E
I
J
H
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Patterns of movement
AAA (4)
AABB (1) AABBA (1)
AA (39-28) AAB (6-1) AABCB (2) AABCBA (2)AABC (4-1)
AABCD (1) AABCDE (1)AAB1 (1)
ABAA (1)ABA (4-2)
ABAB (1)
ABBAA (1) ABBAAA (1)ABBA (2)
ABB (5-2) ABBAB (1)
ABBB (1) ABBBB1 (1) ABBBB1A(1) ABBBB1AA(1)
ABCBA (4-3) ABCBAB (1)ABCB (5)
A (115) ABCBB (1)AB (66-19)
ABCCB (4) ABCCBA (4-3) ABCCBABC (1)ABC (35-12) ABCC (9-3)
ABCCC (2-1) ABCCCB (1) ABCCCBA (1)
ABCDED (2) ABCDEDC (2) ABCDEDCB (2) ABCDEDCBA (2-1) ABCDEDCBAA (1)ABCD (8-3) ABCDE (5-1)
ABCDEED (1) ABCDEEDC (1) ABCDEEDCB (1) ABCDEEDCBA (1)ABCDEE (2)
ABCDEEE (1) ABCDEEEE (1)
ABG (3) ABGH (3-2) ABGHH (1) ABGHHG (1) ABGHHB (1) ABGHHBA (1)
AB1B (2-1) AB1BC (1) AB1BCD (1) AB1BCDE (1) AB1BCEECB (1) AB1BCEECBA (1)AB1 (9-6)
AB1B1 (1) AB1B1B (1) AB1B1BC (1) AB1B1BCC (1) AB1B1BCCB (1) AB1B1BCCBA (1)
AK (1) AKA (1) AKAB (1) AKABC (1)
TOTAL 115 115 62 38 27 18 10 7 3 2
BAAA (1)BAA (10-4)
BAABA (1)BAAB (5-3)
BA (42-28) BAABB (1)
BAB (4-3) BABC (1) BABCL (1) BABCLK (1) BABCLKL (1) BABCLKLK (1) BABCLKLKL (1) BABCLKLKLK (1)
BBA (2) BBAA (2-1) BBAAB (1)BB (10-4)
BBBA (1) BBBAB (1) BBBABB (1)BBB (4-2)
BBBB (1) BBBBB (1)
B (64)BCB (1)
BC (10-1) BCC (3) BCCB (3) BCCBA (3-2) BCCBAB (1) BCCBABC (1)
BCDC (1) BCDCB (1) BCDCBA (1) BCDCBAA (1) BCDCBAAB (1) BCDCBAABC (1) BCDCBAABCD (1)BCD (5-3)
BCDE (1) BCDEE (1) BCDEED (1) BCDEEDC (1) BCDEEDCB (1) BCDEEDCBB1 (1) BCDEEDCBB1A (1)
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Boat types
• rowing boats
• commercial craft
• government vessels
• motor charter
• tug boats
• motor private
• ship
• non-motor sail
• sail under motor
• non-motor oar
• non-motor paddle
57
Conclusions
• developed a consistent methodology that can be applied to model mobile objects along different networks under different management scenarios