Mitigating network traffic congestion via link- and path-based incentives

This study investigates the potential of link- and path-based incentives to mitigate congestion in urban transportation networks under a budget constraint. Both incentive schemes are formulated as non-linear optimisation problems with complementarity constraints. Mathematically, it is demonstrated that the feasible region of the link-based model is a subset of the feasible region of the path-based model under the same budget constraint. Consequently, path-based incentives exhibit greater potential to shift the user equilibrium flow pattern toward the system optimum compared to link incentives. A column generation-based iterative solution technique, which generates new paths at each iteration, is devised to efficiently solve both optimisation problems. Numerical experiments conducted for various transport networks also highlight the efficiency and scalability of the proposed algorithm, and the superiority of path-based incentives in reducing total travel time in urban transportation networks.

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Publication Details

Journal
Transportation Research Part B Methodological
Published
2026-06-30
DOI
https://doi.org/10.1016/j.trb.2026.103531
Primary Topic
Transportation Planning and Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Mitigating network traffic congestion via link- and path-based incentives

Shaghayegh Vosough, Marco Rinaldi, Claudio Roncoli, Ramin Niroumand et al.
Transportation Research Part B Methodological
Transportation Planning and Optimization
article

Mitigating network traffic congestion via link- and path-based incentives

Shaghayegh Vosough, Marco Rinaldi, Claudio Roncoli, Ramin Niroumand, Fahim Kafashan, Richard D. Connors
article en

Abstract

This study investigates the potential of link- and path-based incentives to mitigate congestion in urban transportation networks under a budget constraint. Both incentive schemes are formulated as non-linear optimisation problems with complementarity constraints. Mathematically, it is demonstrated that the feasible region of the link-based model is a subset of the feasible region of the path-based model under the same budget constraint. Consequently, path-based incentives exhibit greater potential to shift the user equilibrium flow pattern toward the system optimum compared to link incentives. A column generation-based iterative solution technique, which generates new paths at each iteration, is devised to efficiently solve both optimisation problems. Numerical experiments conducted for various transport networks also highlight the efficiency and scalability of the proposed algorithm, and the superiority of path-based incentives in reducing total travel time in urban transportation networks.

Transportation Research Part B MethodologicalVol. 211
North Carolina State University (US), Optym (United States) (US), Transport & Mobility Leuven (Belgium) (BE), Luxembourg Institute of Science and Technology (LU), Delft University of Technology (NL), Aalto University (FI)
Academy of Finland, HORIZON EUROPE Reforming and enhancing the European Research and Innovation system
Sustainable cities and communities
Openalex Percentile: Top 6%
Transportation Planning and Optimization
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