the budapest transportation planning model a cube cloud demonstration model andreas köglmaier...
TRANSCRIPT
The Budapest Transportation Planning Model
A Cube Cloud demonstration model
Andreas KöglmaierRegional Director
Overview of transport issues in Hungary and Budapest The transport system of Budapest The Budapest transport plan Model structure The Cube Cloud trial account Using the Budapest model to test Cube Cloud
Content
Geographic context: Hungary
Budapest conurbation (Model area)
Year Population
1950 1,600,000
1960 1,800,000
1970 2,000,000
1980 2,100,000
1990 2,000,000
2000 1,800,000
2010 1,700,000
Source: Budapest statisztikai évkönyve
Budapest road network
Public transport modes in Budapest
Metro (two systems) 33 km Tram 155 km Local Rail Trolleybus, Bus Cogwheel railway, funicular Steam train, chair lift
Budapest metro
Source: Budapest statisztikai évkönyve
Budapest mode share
Transportation infrastructure and traffic project’s impact analysis
Data provision for cost-benefit analyses Data supply for environmental analyses
Support establishment of project selection and project prioritisation
Role of modeling in Master Plan
Road and public transit infrastructure• Road network• MÁV, HÉV és Metro railway networks• Public transport network and timetables (2008)• BKV• MÁV• Volánbusz and others
Household surveys• 2004 évi BKV household survey• 2007 évi S-bahn household survey
Model data
Traffic counts• Roadway traffic (2004-2008)• BKV public transport patronage data (2007)• MÁV public transport patronage data (2005)• Year 2006 MÁV és Volán traffic counts in the outbound
direction within Budapest (2006) Population, employment, vehicle ownership forecasts
Model data
Trip table calibration: CUBE Analyst• Highway trip table calibration (AM peak, PM peak,
evening, night)• Transit trip calibration (AM peak, PM peak, daily)
Trip table forecast:• Multiple regression analyses: SPSS• Matrix manipulation: CUBE Voyager 5.0
Mode choice model• Calibration: Biogeme 1.7• Incremental logit model: CUBE Voyager 5.0
Highway and transit assignment: CUBE Voyager 5.0
Software used for Budapest model
10 initial road/public transit scenarios (Phase I)• 5 low budget scenarios • 5 high budget scenarios
2 final scenarios Special analyses
• Area wide toll• Unified tariff system
Project level analysis: 56 road and PT projects (Phase II)
Model scenarios
Model structureExternal data• Transport networks, timetables• Land use data• Population, employment, vehicle ownership• Costs (tariffs, patrol, parking)
Trip table and skim table calibration• Raw trip tables from Household surveys -> calibration by traffic
counts• Time skims (using time talbes and posted speeds) -> calibrate by real
time/floating car data
Trip table forecasts• Growth rate method (multiple regression model)• Peak hour spreading model (elasticity model)
Mode choice model• Calibration of utility models (Household surveys)• Incremental logit model (9 segments by purpose and area)
Highway and Transit assignments• Highways: equilibrium method• Public transportation: multi-path logit assignment with capacity
constraint
Highway assignment• Four time periods (AM, PM, evening, night) • Equilibrium assignment with 3 vehicle classes• Fixed number of iterations between 8-40• Daily volumes derived by the linear combination of 4
periods via using factors by road and area type Public transport assignment
• Daily assignment (AM peak timetable)• Multi path assignment • Capacity constrained (crowding) model with six
iterations
Assignment
Budapest Model on Cube Cloud
Budapest Model on Cube Cloud
Budapest Model on Cube Cloud
Budapest Model on Cube Cloud
Budapest Model on Cube Cloud
Budapest Model on Cube Cloud
Budapest Model on Cube Cloud
Budapest Model on Cube Cloud
Test the benefits of Cube Cloud Internet: movement from a desktop-bound, ‘locked’ environment to an internet-based,
‘open’, sharable, ‘work from anywhere/anytime’ environment
Community Resource: model application and planning analysis done by non-experts using common web-browsers moving models to an active role in collaborative transportation planning
Cloud-Computing: placement of the models, data and software in a cloud-computing environment lowering hardware costs locally while providing ‘unlimited’ high-spec resources
Lower costs for the user: movement from locally licensed desktops to a software as a service model. Monthly subscription business model allowing many to use the model at low, or even, no cost
Lessens IT complexity: much of the IT burden of modeling is shifted from the user to the vendor
Data and Software Integration: easier to integrate with external systems: development reviews, regional air quality analysis, pavement maintenance systems, traffic and transit ITS systems and to receive and use data from data probes, detectors and static data sources
Csaba KelenAddress: Kozlekedes Ltd, H-1052 Budapest, Bécsi utca 5Phone: +36.1.235.2020/105Fax: +36.1.235.2021Email: [email protected]
Acknowledgement
