1. The role of volume-delay functions in forecast and evaluation of congestion charging schemes Application to Stockholm Leonid Engelson and Dirk van Amelsfort The Royal Institute of Technology and WSP Analysis and Strategy

2. Outline Background of the project Model validation by effects of congestion charging Adjustment of VDF Results of the experiment Conclusions and recommendations

3. Background Two research projects at CTS: –Improvement of CC system for Stockholm –Transferability of Stockholm experience to other cities Need a model to calculate benefits of CC Two state of the art regional models were used for forecasts –Destination and mode choice –Static assignment Comprehensive monitoring of CC effects The observed effects differed from the model forecast Is it possible to improve the model by small effort in order to be useful for CBA?

4. The model SAMPERS – a model for whole Sweden (5 regions, national, international), Stockholm + MD = one of the regions Nested logit demand model –6 travel purposes –Frequency, destination, mode choice –Scaling demand matrices from day to assignment period with fixed shares: AM peak, mid-day, PM peak –Scaling to 5 VoT classes with fixed shares Transit and auto assignments in Emme –Auto assignment with generalized cost with 5 VoT classes Feedback travel time and cost to the demand model VDF for Stockholm estimated 1979, adjustments in 80-s and 90-s Travel survey 1990-1995

5. The congestion charging system

6. Traffic flow over the cordon

7. Comparison of modeled and observed effects, aggregate By Jonas Eliasson and Karin Brundell-Freij

8. The cordon and the AVI links

9. Measured 7:30-9:00T/RIMSamPers Traffic flow through the cordon, no charges, veh/h358684229637182 Traffic flow through the cordon, with charges, veh/h312382615326254 Relative change in flow-13%-38%-29% Average speed on AVI links, with charges, veh/h30.835.337.4 Average speed on AVI links, no charges, veh/h34.937.939.4 Relative change in speed13%7.4%5.3% Speed change to flow change ratio-0,2 Comparison of modelled and observed effects, morning peak

10. Demand model or supply model? Flows change stronger than in reality. Travel times change less than in reality If flow changes are improved by better modelling the demand then the discrepancy in time changes will be even worse The supply model needs improvement in the first hand

11. To improve the static model No interaction at intersections No back propagation of queues No queue building and dissipation (”average” conditions) Still we can make VDF steeper in the static model (our VDF are from 1978) Is it possible to calibrate a static model with a VDF slope parameter ? Numerical experiment

12. Modification of VDF time v0v0 v 0 = flow in the base scenario t 0 = time in the base scenario volume t0t0 f g

13. Effect of k on modelled traffic flow and average speed k Relative change of flow over the cordon Relative change of average speed on AVI links Speed change to flow change ratio 1-29%5,3%-0.18 2-28%8%-0.29 3-27%9%-0.33 4-27%10%-0.37 10-26%15%-0.57 Observed-13%13% Still long to the observed ratio

14. Effects of k on benefit of the CC (SEK per day) k Surplus change RevenuesBenefit 1-3 023 7373 532 497508 760 2-2 842 2903 591 849749 558 3-2 742 4753 629 175886 700 4-2 663 1673 663 9921 000 824 10-2 325 4443 772 6731 447 228 The benefit depends on k

15. Comparison of charging systems with different k 1.The current system 2.The current system plus charge on Essinge bypass 3.The current system plus charge for crossing the strait 4.The current system plus charge for crossing the strait but not the Essinge bypass 5.The current system plus charge for crossing the strait plus charge on the Central bridge.

16. Gate locations in the four alternative charging systems

17. Ranking of different charging systems with k=1 and with k=10 (SEK per day) Charging system k=1k=10 Surplus change RevenueBenefitRanking Surplus change RevenueBenefitRanking 1-3 0243 532508 7603-2 3253 7731 447 2283 2-3 8974 505608 2752-2 9774 7781 801 1792 3-5 0205 894873 5451-3 7916 2772 485 6941 4-4 4824 088-393 0805-4 0464 743697 0164 5-3 6613 75997 6504-3 5534 137584 2765 *1000

18. Conclusions Steeper VDF make the model better reproduce effects of CC Even med much steeper VDF the model still underestimates the speed change to flow change ratio With steeper VDF, the calculated benefit of CC is substantially higher than with the original VDF

19. Recommendations Static assignment models are not appropriate for CBA of CC in cities, more advanced tools are needed When the benefit of CC is calculated with a static model the sensitivity analysis w r t slope of VDF is recommended (EMME macro is available)