MODELLING THE IMPACTS OF ROAD PRICING IN BUDAPEST

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MODELLING THE IMPACTS OFROAD PRICING IN BUDAPEST
Dr. habil Janos MONIGL Zsolt BERKI
IMPRINT Seminar Budapest 10 May 2015
TRANSMANConsulting for Transport System
Management Ltd. 1051 Budapest Hercegprimas u.
10. Tel. [phone] Fax [phone] E-ma
il transman_at_transman.hu Internet
http//www.transman.hu
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Scope of the investigation

• Within EUROPRICE (Energy Efficiency of Urban Road
  Pricing Investigation in Capitals of Europe)
• Project leader Trinity College Dublin for EC DG
  XVII.
• London, Dublin, Athens, Budapest
• Impact assessment of Road Pricing in Budapest
• - a Case Study
• Energy savings because of pricing?
• Congestion, air pollution more important

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Road transport network and loads (TRANSURS)
PEST
BUDA
Trucks gt 3.5t are banned in the inner area
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Public transport network and loads (TRANSURS)
1,4 billion passengers/year - Decrease
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Car trips to the city by trip origin, purpose and
leaving trip destination
Modal split local PT vs car (6040)
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The share of car trips by household car ownership
and destinating area
car
PT
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Inbound passenger traffic to Budapest by modes
Modal split inbound PT vs car (4060)
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Development tendencies of car traffic and public
transport in Budapest
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Transport policy implications

• Budapest Transport System Development Plan
• - Reducing demand for transport by improved land
  use
• management
• - Improving traffic organisation and management
• - Mitigating the environmental impacts of
  transport
• activity
• - Minimising costs and improving the efficiency
  of the
• transport system.

Is pricing a tool to meet the goals?
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Area related indicators for the inner city
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Road pricing scenario 1 (Danube Crossing
Tolling)
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Road pricing scenario 2 (Inner City Tolling )
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Road pricing scenario 3 (Pest Additional
Tolling)
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Modelling by TRANSURS model
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Modelling work - TRANSURS model

• Trip generation
• trip rates
• with location potential dependency
• Trip distribution two stages
• area choice (logsum)
• zonal distribution (gravity)
• Modal split
• logit by person group, by activity, car
  availability,
• pass ownership, trip purpose (chain)
• Assignment equilibrium
• Impact calculation by speed and volumes
• for time, fuel, air pollution, etc.

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Trip rates in function of location potentials
Potential
Potential
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Comparison of the measured and the calculated
trip destination area choice
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Comparison of the measured and the calculated
mode choice
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Deterrence functions
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Traffic load difference map of road pricing
Scenario2
increase
decrease
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Modal shifts because of road pricing in
Budapest(2nd Scenario)
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Impacts of road pricing in Budapest (2nd
Scenario)
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Area related indicators for the inner city
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Main model results Scenario 2

• Origin/destination trips in inner area 4
• Shifts in transport modes
• cars 40, public transport 8, bike 3, walk
  2
• Changes in the inner city/whole city
• traffic performance (-48/0)
• transport time (-65/1)
• fuel consumption (-54/-1)
• NOX emission (-31/3)
• Traffic reassignment from the inner bridges to
  Lágymányosi bridge (south) Árpád bridge (north)
• Annual toll-box revenue HUF 7,2 billion/year
  (1995)
• 28 million EUR/year

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Network wide impacts of the road pricing
scenarios
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Theoretic Marginal Cost Proportional Road Pricing
Scheme by Area and Daily Time Period Using Paper
Vignettes