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Accuracy of the Gothenburg congestion charges forecast

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  • West, Jens
  • Börjesson, Maria
  • Engelson, Leonid

Abstract

This paper explores the accuracy of the transport model forecast of the Gothenburg congestion charges, implemented in 2013. The design of the charging system implies that the path disutility cannot be computed as a sum of link attributes. The route choice model is therefore implemented as a hierarchical algorithm, applying a continuous value of travel time (VTT) distribution. The VTT distribution was estimated from stated choice (SC) data. However, based on experience of impact forecasting with a similar model and of impact outcome of congestion charges in Stockholm, the estimated VTT distribution had to be stretched to the right. We find that the forecast traffic reductions across the cordon and travel time gains were close to those observed in the peak. However, the reduction in traffic across the cordon was underpredicted off-peak. The necessity to make the adjustment indicates that the VTT inferred from SC data does not reveal the travellers’ preferences, or that there are factors determining route choice other than those included in the model: travel distance, travel time and congestion charge.

Suggested Citation

  • West, Jens & Börjesson, Maria & Engelson, Leonid, 2016. "Accuracy of the Gothenburg congestion charges forecast," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 266-277.
  • Handle: RePEc:eee:transa:v:94:y:2016:i:c:p:266-277
    DOI: 10.1016/j.tra.2016.09.016
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    Cited by:

    1. Börjesson, Maria & Kristoffersson, Ida, 2018. "The Swedish congestion charges: Ten years on," Transportation Research Part A: Policy and Practice, Elsevier, vol. 107(C), pages 35-51.
    2. Lehe, Lewis J. & Devunuri, Saipraneeth, 2022. "Large Elasticity at Introduction," Research in Transportation Economics, Elsevier, vol. 95(C).
    3. Börjesson , Maria & Kristoffersson, Ida, 2017. "The Swedish congestion charges: ten years on: - and effects of increasing charging levels," Working papers in Transport Economics 2017:2, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    4. Lorenzo Varela, Juan Manuel & Börjesson, Maria & Daly, Andrew, 2018. "Public transport: One mode or several?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 113(C), pages 137-156.
    5. Varela, Juan Manuel Lorenzo & Börjesson, Maria & Daly, Andrew, 2018. "Quantifying errors in travel time and cost by latent variables," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 520-541.
    6. Varela, Juan Manuel Lorenzo & Börjesson, Maria & Daly, Andrew, 2018. "Quantifying errors in travel time and cost by latent variables," Working papers in Transport Economics 2018:3, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    7. Jens West & Maria Börjesson, 2020. "The Gothenburg congestion charges: cost–benefit analysis and distribution effects," Transportation, Springer, vol. 47(1), pages 145-174, February.
    8. Börjesson, Maria & Asplund, Disa & Hamilton, Carl, 2023. "Optimal kilometre tax for electric vehicles," Transport Policy, Elsevier, vol. 134(C), pages 52-64.

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    More about this item

    Keywords

    Congestion charges; Transport model; Validation; Value of time; Volume delay function; Decision support;
    All these keywords.

    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • R42 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government and Private Investment Analysis; Road Maintenance; Transportation Planning
    • R48 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government Pricing and Policy

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