MODELLING THE IMPACTS OF ROAD PRICING IN BUDAPEST TRANSMAN Consulting for Transport System Management Ltd Budapest Hercegprimas u. 10. Tel.: Fax: Internet: Dr. habil Janos MONIGL Zsolt BERKI IMPRINT Seminar Budapest 28 June June June 2015

2 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

3 Road transport network and loads (TRANSURS) BUDA PEST Trucks > 3.5t are banned in the inner area

4 Public transport network and loads (TRANSURS) 1,4 billion passengers/year - Decrease

5 Car trips to the city by trip origin, purpose and leaving trip destination Modal split „local”: PT vs car (60%:40%)

6 The share of car trips by household car ownership and destinating area PT car

7 Inbound passenger traffic to Budapest by modes Modal split inbound: PT vs car (40%:60%)

8 Development tendencies of car traffic and public transport in Budapest

9 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. Transport policy implications Is pricing a tool to meet the goals?

10 Area related indicators for the inner city

11 Road pricing scenario – 1 (Danube Crossing Tolling) 1 litre petrol = 100HUF = 1 crossing

12 Road pricing scenario – 2 (Inner City Tolling )

13 Road pricing scenario – 3 (Pest Additional Tolling)

14 Modelling by TRANSURS model

15 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.

16 Trip rates in function of location potentials Potential Potential

17 Comparison of the measured and the calculated trip destination area choice

18 Comparison of the measured and the calculated mode choice

19 Deterrence functions

20 Traffic load difference map of road pricing Scenario2 increase decrease

21 Modal shifts because of road pricing in Budapest (2 nd Scenario)

22 Impacts of road pricing in Budapest (2 nd Scenario)

23 Area related indicators for the inner city

24 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%) NO X 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

25 Network wide impacts of the road pricing scenarios

26 Theoretic Marginal Cost Proportional Road Pricing Scheme by Area and Daily Time Period Using Paper Vignettes