A path-based incentive scheme toward de-carbonized trips in a bi-modal traffic network
Document Type
Journal Article
Publication Date
2023
Subject Area
mode - car, mode - subway/metro, planning - travel demand management, planning - methods, policy - congestion, policy - fares, policy - environment, technology - emissions
Keywords
travel demand management (TDM), congestion, emissions
Abstract
This study proposes an innovative travel demand management (TDM) scheme of path-based incentives to relieve congestion and reduce carbon emissions in a bi-modal network of road traffic and subway. The path-differentiated incentive is rewarded to travelers in the form of subway credits, which can be exchanged for free subway tickets. Thus, the scheme can potentially ameliorate road traffic distribution and meanwhile attract travelers to take the subway. We thereby establish user equilibrium (UE) model in the bi-modal network and solve it via a Frank–Wolfe-type algorithm. Furthermore, a sensitivity-analysis-based (SAB) method is adopted to design the incentive scheme under a given budget. Numerical results demonstrate that with a limited credit budget, the incentive scheme can significantly reduce total travel cost and carbon emissions in the traffic system. Finally, a day-to-day microscopic simulation based on real data validates the robustness of the proposed scheme in a time-variant traffic system with strong randomness.
Rights
Permission to publish the abstract has been given by Elsevier, copyright remains with them.
Recommended Citation
Hu, X., Chen, X., Lin, X., & Li, M. (2023). A path-based incentive scheme toward de-carbonized trips in a bi-modal traffic network. Transportation Research Part D: Transport and Environment, 122, 103853.
Comments
Transportation Research Part D Home Page:
http://www.sciencedirect.com/science/journal/13619209