Dynamic scheduling modelling of congestion pricing: Assessing travel behaviour and welfare impacts in Greater Helsinki

Congestion charging systems have emerged as a promising policy tool for mitigating traffic congestion and reducing emissions in urban areas. This study applies a dynamic activity scheduling model to assess the effects of congestion pricing in the Greater Helsinki region. By simulating daily activity patterns and travel behaviour, we analyse the impacts of congestion charges on mode choice, destination selection, and departure time adjustments. Our findings reveal a 10% reduction in car use and a 27% decrease in total car kilometres travelled, demonstrating the effectiveness of congestion pricing in alleviating traffic congestion. However, the analysis also highlights the potential equity concerns, with impacts varying across locations and commuting patterns. These insights contribute to the growing body of evidence on the behavioural and distributional consequences of congestion pricing, offering valuable guidance for policymakers. • Scaper captures changes in mode, timing, and destination choices under pricing. • Scaper supports assessing congestion pricing impacts on travel, welfare, and equity. • Welfare losses are greatest among car-dependent commuters in suburban areas. • Congestion pricing slightly widens spatial inequality, stressing the need for mitigation.

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Publication Details

Journal
Transport Policy
Published
2025-12-02
DOI
https://doi.org/10.1016/j.tranpol.2025.103929
Primary Topic
Transportation Planning and Optimization
Type
article
Field-Weighted Citation Impact
0.00
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article

Dynamic scheduling modelling of congestion pricing: Assessing travel behaviour and welfare impacts in Greater Helsinki

Daniel Jönsson, Anders Karlström, Qian Wang
Transport Policy
Transportation Planning and Optimization
article

Dynamic scheduling modelling of congestion pricing: Assessing travel behaviour and welfare impacts in Greater Helsinki

Daniel Jönsson, Anders Karlström, Qian Wang
article en

Abstract

Congestion charging systems have emerged as a promising policy tool for mitigating traffic congestion and reducing emissions in urban areas. This study applies a dynamic activity scheduling model to assess the effects of congestion pricing in the Greater Helsinki region. By simulating daily activity patterns and travel behaviour, we analyse the impacts of congestion charges on mode choice, destination selection, and departure time adjustments. Our findings reveal a 10% reduction in car use and a 27% decrease in total car kilometres travelled, demonstrating the effectiveness of congestion pricing in alleviating traffic congestion. However, the analysis also highlights the potential equity concerns, with impacts varying across locations and commuting patterns. These insights contribute to the growing body of evidence on the behavioural and distributional consequences of congestion pricing, offering valuable guidance for policymakers. • Scaper captures changes in mode, timing, and destination choices under pricing. • Scaper supports assessing congestion pricing impacts on travel, welfare, and equity. • Welfare losses are greatest among car-dependent commuters in suburban areas. • Congestion pricing slightly widens spatial inequality, stressing the need for mitigation.

Transport PolicyVol. 177
KTH Royal Institute of Technology (SE)
Openalex Percentile: Top 63%
Transportation Planning and Optimization
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