The Budapest Transportation Planning Model

Transcript The Budapest Transportation Planning Model

The Budapest Transportation Planning Model

A Cube Cloud demonstration model Andreas Köglmaier Regional Director

Content

      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

Geographic context: Hungary

Budapest conurbation (Model area) Year

1950 1960 1970 1980 1990 2000 2010

Population

1,600,000 1,800,000 2,000,000 2,100,000 2,000,000 1,800,000 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

Role of modeling in Master Plan

   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

Model data

  • • • • • 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 2007 évi BKV household survey 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

Software used for Budapest model

    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

Model scenarios

   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 structure External 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

Assignment

  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

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

Acknowledgement

Csaba Kelen Address: Kozlekedes Ltd, H-1052 Budapest, Bécsi utca 5 Phone: +36.1.235.2020/105 Fax: +36.1.235.2021

Email: [email protected]

Thank you!

Andreas Köglmaier Regional Director [email protected]