 Managing network congestion with link-based incentives: A surrogate-based optimization approachQuanlu Fu, Jiyan Wu, Xuemian Wu, Jian Sun and Ye Tian Transportation Research Part A: Policy and Practice, 2024, vol. 182, issue C Abstract: Incentive-based travel demand management (IBTDM) programs endow monetary incentives to encourage travel demand redistribution across space and time. They are more appealing than alternatives such as congestion charging because commuters do not need to pay out of pocket. However, such congestion-alleviation solutions are usually managed by small private companies with constrained incentive budgets. Thus, the incentive should be wisely determined so that a limited incentive budget can be effectively used to fulfill maximum social welfare while maintaining the financial health of the IBTDM program. It is essential to know whether IBTDM is financially sound—that is, whether financial investment in IBTDM will lead to more than the equivalent value in total system travel time reduction. However, optimizing the link-based endowment scheme in a large-scale network is challenging because 1) the objective function and the budget constraint are both characterized by expensive-to-evaluate functions without closed form, and 2) it is a large-scale optimization problem that contains massive amount of decision variables. In this study, a computationally efficient surrogate-based optimization framework that is suitable for high-dimensional problems is proposed. A simulation-based dynamic traffic assignment model is used to evaluate the performance of transportation systems, and a Kriging model with partial least squares acts as the surrogate to approximate the simulation model. The results show that the optimal network-wide link-based incentive scheme improves the performance of the system. The higher the incentive budget, the more effective the incentive and the lower the marginal utility of the incentive. Furthermore, in a well-designed incentive scheme, a $1M investment in IBTDM would lead to much more than the equivalent of $1M in total system travel time reduction, which proves the economic viability of IBTDM and provides support for its promotion. IBTDM implemented within smaller regions and tighter incentive budgets produces higher utility ratios. Keywords: Travel demand management; Simulation-based optimization; Incentive budget; Dynamic traffic assignment; Large-scale network; Loss aversion (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:transa:v:182:y:2024:i:c:s0965856424000818 Ordering information: This journal article can be ordered from DOI: 10.1016/j.tra.2024.104033 Access Statistics for this article Transportation Research Part A: Policy and Practice is currently edited by John (J.M.) Rose More articles in Transportation Research Part A: Policy and Practice from Elsevier |
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