1. The Stockholm trials – Emme/2 as a tool for designing a congestion charges system 1.The trials and the congestion charges system 2.Observed effects 3.Transportation forecast results compared to observed effects 4.The referendum

2. The Stockholm trials Extended public transport More park-and-ride facilities Implementation of a congestion tax

3. Objectives Reduce traffic volumes on the busiest roads during peak hours by 10-15% Improve the flow of traffic on streets and roads Reduce emissions of pollutants harmful to human health and of carbon dioxide Improve the urban environment as perceived by Stockholm residents

4. The congestion charges system

5. 10 SEK = 1,06 Euro, = 1,33 USD The congestion charges system ”Weekdays 6:30 am – 6:30 pm” SEK 10, 15 or 20 for passage into and out of the inner city No charges on evenings, nights, saturdays, sundays public holidays and the day before a public holiday Maximum charge of SEK 60 per day and vehicle

6. Percentage change in traffic flows in and out of the congestion charge zone during the charge period (6.30 am – 6.30 pm)

7. Traffic passing in and out of the inner city on an average day in spring 2005 compared with spring 2006 Number of vehicles per hour Time No charge 15 SEK 20 SEK 10 SEK (1,06 Euro, 1,33 USD)

8. Difference in journey time along various monitoring routes, 2005-2006 Increase Unchanged Reduction Big reduction

9. Transportation forecasts – the purpose To supply: basic data for decision about the design of the congestion charges system basic data as input to other actors planning activities because of the Stockholm trial (for example Stockholm Transport (SL))

10. Transportation forecasts – analyzed scenarios Different price structures Different number of charging zones With and without congestion charges on Essingeleden With and without congestion charges for residents in Lidingö

11. Transportation forecasts – the forecast model Sampers: Trip frequency Mode split (car, public transport, walk, cykle) Destination choice Emme/2: Auto assignment (auto volumes on road network) Transit assignment (passenger volumes on transit lines)

12. Transportation forecasts – model features Traffic during the average weekday Traffic during peak period and between peak periods Different time values for different categories of people Choice of departure time

13. Percentage change in traffic flows in and out of the congestion charge zone during the charge period Observed effect = -22 % Transportation forecast = -25 %

14. Forecasted number of vehicles passing in and out of the inner city on an average day Number of vehicles per 15 minutes Time Without charges With charges

15. Observed number of vehicles passing in and out of the inner city on an average day Autumn 2005 January 2006 February 2006 Number of vehicles per 15 minutes Time

16. Number of vehicles on different parts on E4-Essingeleden during the charge period (6.30 am – 6.30 pm) Observed increase = 4-5 % Forecast = +7 % Essingeleden Frösunda Midsommar -kransen 2006 2005 Numver of vehicles Month

17. What’s the results? Percentage differences in traffic flows during an average weekday were forecasted with relative good results –The increase of traffic flow on Essingeleden were slightly overestimated –The decrease of traffic flow across the zone boundary were slightly overestimated Incorrect distribution of the effects on morning peak period, between peaks and afternoon peak period The forecasts missed the decrease in evening traffic The effects of time departure choices were overestimated Underestimated time values and underestimated travel time effects => more people opted to travel through the city than expected Shortages in the model of time distribution functions and neglecting “turn and return thinking” => the real effects were bigger during afternoon peak period and between peaks and smaller during morning peak period

18. The referendum No referendum Referendum