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TransMob 
An Agent-based Simulation of Transport 
Demand and Residential Mobility in South 
East Sydney 
Pascal Perez 
Nam Huynh 
Vu Lam Cao 
Rohan Wickramasuriya 
Matthew Berryman 
September 2014
WHAT IS IT?
TransMob – fast facts 
TransMob includes: 
110,000 Agents 
85,000 Private Motorized Vehicles 
50,000 Households (17 categories) 
60 Travel Zones 
32 Bus Routes 
8 Transport Modes 
6 Transport Purposes 
4 Dwelling Categories 
TransMob generates: 
~ 450,000 Trips/Weekday 
~ 9,000 Transport Mode Choices/Year 
~ 7,000 Residential Changes/Year 
(Baseline scenario, indicative values only) 
Period: 2006-2026 
Calibration: Census 2006 
Validation: Census 2011
TransMob – User Interface 
Study Area Travel Zone Road Network 
YES 
NO
WHY IS IT 
IMPORTANT?
HOW DOES IT 
WORK?
Model Components 
Synthetic 
Population 
Liveability 
Transport Micro 
simulator 
Travel Diaries 
Agent Decisions 
Transport Mode 
Choice 
Residential 
Location Choice 
Output Data Warehouse 
(scenarios and runs) 
Socio-demographic data 
Transims data 
Visualisation Dashboard 
Scenarios and runs 
Study Area 
Travel Zones 
Major Road Links 
3D Traffic Simulator 
Traffic density-based 
Interactive sessions 
Temporarily staged 
TransMob - Architecture 
Census 
2006 
HTS 
2006-2010 
Liveability 
2011 
JtW 
2006 
HILDA 
2001-2010
Perceived Liveability - Calibration 
Influence 
of 
Age Group 
Satisfaction 
with 
transport
42% 
(51%) 
Traffic Micro-Simulator - Validation 
(HTS 2006-2010) 
26% 
(29%)
Traffic Micro-Simulator - Validation 
Trip Counts per Mode Trip Counts per Purpose
Synthetic Population - Validation
Validation – Residential Mobility
Exploring What-If? scenarios 
Scenario 1: Baseline (calibrated on 2006 Census) 
Scenario 2: Double Income No Kids (DINKs) 
Scenario 3: Virtual Light Rail (VLR) 
These 3 scenarios are purely hypothetical and do not reflect upon results 
being currently assessed by Transport for NSW
Scenario 1 – Study Area - Year 2016 
4% population increase 
50% car drivers 
12% public transport 
39,000 peak trips 
Liveability: stable
Scenario 2 – Study Area - Year 2016 
4% population decrease 
46% car drivers 
16% public transport 
36,000 peak trips 
Liveability: improved
Scenario 3 – Study Area - Year 2016 
7% population increase 
46% car drivers 
18% public transport 
45,000 peak trips 
Liveability: stable
Scenario 1 – Travel Zone - Year 2016 
20% couple#0 
53% 1-2 bedroom 
12% public transport 
0.40 satisfaction couple#0
Scenario 2 – Travel Zone - Year 2016 
48% couple#0 
58% 1-2 bedroom 
15% public transport 
0.47 satisfaction couple#0
Scenario 3 – Travel Zone - Year 2016 
21% couple#0 
57% 1-2 bedroom 
33% public transport 
0.41 satisfaction couple#0
Scenario 1 – Road Traffic Profile - Year 2016 
Northbound peak traffic (morning) 2,000 vehicle/hour 
Southbound peak traffic (morning) 1,250 vehicle/hour
Scenario 2 – Road Traffic Profile - Year 2016 
Northbound peak traffic (morning) 1,650 vehicle/hour 
Southbound peak traffic (morning) 1,100 vehicle/hour
Scenario 3 – Road Traffic Profile - Year 2016 
Northbound peak traffic (morning) 2,200 vehicle/hour 
Southbound peak traffic (morning) 1,600 vehicle/hour
TransMob – Current Limitations 
No Macro-Economic Model for Employment 
Model uses a simple ‘job event’ probability to trigger a salary update and a 
residential relocation test. This probability is estimated using employment 
statistics from the Australian Bureau of Statistics. 
No Proactive Real Estate Market 
Baseline scenario uses a bootstrapping approach based on the evolution of 
dwelling stocks and prices in each travel zone between 2006 and 2011. 
Alternative scenarios allow only for demand-driven allocation. 
No Urban Zoning or Planning Mechanisms 
Despite repeated requests, we were not able to access and implement simple 
rules for local urban planning and zoning. 
No Freight Transport Being Modelled 
This is a major impediment as South East Sydney is connected to Mascot Airport 
/ Port Botany Precinct!
Pascal Perez 
Research Director 
SMART Infrastructure Facility 
+61 2 4252 8238 
pascal_perez@uow.edu.au

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TransMob: An Agent-based Simulation of Transport Demand and Residential Mobility in South East Sydney

  • 1. TransMob An Agent-based Simulation of Transport Demand and Residential Mobility in South East Sydney Pascal Perez Nam Huynh Vu Lam Cao Rohan Wickramasuriya Matthew Berryman September 2014
  • 3. TransMob – fast facts TransMob includes: 110,000 Agents 85,000 Private Motorized Vehicles 50,000 Households (17 categories) 60 Travel Zones 32 Bus Routes 8 Transport Modes 6 Transport Purposes 4 Dwelling Categories TransMob generates: ~ 450,000 Trips/Weekday ~ 9,000 Transport Mode Choices/Year ~ 7,000 Residential Changes/Year (Baseline scenario, indicative values only) Period: 2006-2026 Calibration: Census 2006 Validation: Census 2011
  • 4. TransMob – User Interface Study Area Travel Zone Road Network YES NO
  • 5. WHY IS IT IMPORTANT?
  • 6.
  • 7.
  • 8. HOW DOES IT WORK?
  • 9. Model Components Synthetic Population Liveability Transport Micro simulator Travel Diaries Agent Decisions Transport Mode Choice Residential Location Choice Output Data Warehouse (scenarios and runs) Socio-demographic data Transims data Visualisation Dashboard Scenarios and runs Study Area Travel Zones Major Road Links 3D Traffic Simulator Traffic density-based Interactive sessions Temporarily staged TransMob - Architecture Census 2006 HTS 2006-2010 Liveability 2011 JtW 2006 HILDA 2001-2010
  • 10. Perceived Liveability - Calibration Influence of Age Group Satisfaction with transport
  • 11.
  • 12. 42% (51%) Traffic Micro-Simulator - Validation (HTS 2006-2010) 26% (29%)
  • 13. Traffic Micro-Simulator - Validation Trip Counts per Mode Trip Counts per Purpose
  • 16. Exploring What-If? scenarios Scenario 1: Baseline (calibrated on 2006 Census) Scenario 2: Double Income No Kids (DINKs) Scenario 3: Virtual Light Rail (VLR) These 3 scenarios are purely hypothetical and do not reflect upon results being currently assessed by Transport for NSW
  • 17. Scenario 1 – Study Area - Year 2016 4% population increase 50% car drivers 12% public transport 39,000 peak trips Liveability: stable
  • 18. Scenario 2 – Study Area - Year 2016 4% population decrease 46% car drivers 16% public transport 36,000 peak trips Liveability: improved
  • 19. Scenario 3 – Study Area - Year 2016 7% population increase 46% car drivers 18% public transport 45,000 peak trips Liveability: stable
  • 20. Scenario 1 – Travel Zone - Year 2016 20% couple#0 53% 1-2 bedroom 12% public transport 0.40 satisfaction couple#0
  • 21. Scenario 2 – Travel Zone - Year 2016 48% couple#0 58% 1-2 bedroom 15% public transport 0.47 satisfaction couple#0
  • 22. Scenario 3 – Travel Zone - Year 2016 21% couple#0 57% 1-2 bedroom 33% public transport 0.41 satisfaction couple#0
  • 23. Scenario 1 – Road Traffic Profile - Year 2016 Northbound peak traffic (morning) 2,000 vehicle/hour Southbound peak traffic (morning) 1,250 vehicle/hour
  • 24. Scenario 2 – Road Traffic Profile - Year 2016 Northbound peak traffic (morning) 1,650 vehicle/hour Southbound peak traffic (morning) 1,100 vehicle/hour
  • 25. Scenario 3 – Road Traffic Profile - Year 2016 Northbound peak traffic (morning) 2,200 vehicle/hour Southbound peak traffic (morning) 1,600 vehicle/hour
  • 26. TransMob – Current Limitations No Macro-Economic Model for Employment Model uses a simple ‘job event’ probability to trigger a salary update and a residential relocation test. This probability is estimated using employment statistics from the Australian Bureau of Statistics. No Proactive Real Estate Market Baseline scenario uses a bootstrapping approach based on the evolution of dwelling stocks and prices in each travel zone between 2006 and 2011. Alternative scenarios allow only for demand-driven allocation. No Urban Zoning or Planning Mechanisms Despite repeated requests, we were not able to access and implement simple rules for local urban planning and zoning. No Freight Transport Being Modelled This is a major impediment as South East Sydney is connected to Mascot Airport / Port Botany Precinct!
  • 27. Pascal Perez Research Director SMART Infrastructure Facility +61 2 4252 8238 pascal_perez@uow.edu.au

Editor's Notes

  1. What client wants!
  2. SMART’s starting point on integrated transport and land use planning
  3. Models need a paradigm shift to better support urban planning
  4. Model architecture
  5. Unique aspect of TransMob…
  6. A model of perceived liveability that reconciliates objective and subjective standpoints