{"title":"Dynamics in credit-based mobility systems: Convergence to periodic mode usage equilibrium","authors":"Hongxing Ding , Xinwei Li , Hai Yang , Yafeng Yin","doi":"10.1016/j.trb.2025.103310","DOIUrl":null,"url":null,"abstract":"<div><div>This study examines the flow, behavior, and credit dynamics under a credit charge-cum-reward (CCR) scheme that operates periodically. In this scheme, travelers incur an end-of-period credit cost, determined by their periodic mode usage patterns, in addition to regular mode-specific time and monetary costs. As such, travelers are incentivized to make decisions minimizing individual periodic travel costs rather than focusing solely on daily cost minimization. To formulate a CCR-scheme-based dynamic system, we analyze travelers’ intra-period and inter-period learning behaviors and propose two adaptation rules—myopic and forward-looking—for travelers making day-to-day choices. We provide optimal strategies for each traveler under these two rules and derive stability conditions for the dynamic system. Our findings demonstrate that, under mild conditions, both rules, along with travelers’ learning behaviors, lead the dynamic system to converge to a periodic mode usage equilibrium (PUE), where each traveler minimizes their periodic travel costs. Numerical examples illustrate the variations in system performance and traveler behavior across two adaptation rules. This study not only explores the evolution of a CCR-scheme-based dynamic mobility system toward the PUE but also highlights the distinct adaptation behaviors under periodic mobility management policies.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"201 ","pages":"Article 103310"},"PeriodicalIF":6.3000,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part B-Methodological","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0191261525001596","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
This study examines the flow, behavior, and credit dynamics under a credit charge-cum-reward (CCR) scheme that operates periodically. In this scheme, travelers incur an end-of-period credit cost, determined by their periodic mode usage patterns, in addition to regular mode-specific time and monetary costs. As such, travelers are incentivized to make decisions minimizing individual periodic travel costs rather than focusing solely on daily cost minimization. To formulate a CCR-scheme-based dynamic system, we analyze travelers’ intra-period and inter-period learning behaviors and propose two adaptation rules—myopic and forward-looking—for travelers making day-to-day choices. We provide optimal strategies for each traveler under these two rules and derive stability conditions for the dynamic system. Our findings demonstrate that, under mild conditions, both rules, along with travelers’ learning behaviors, lead the dynamic system to converge to a periodic mode usage equilibrium (PUE), where each traveler minimizes their periodic travel costs. Numerical examples illustrate the variations in system performance and traveler behavior across two adaptation rules. This study not only explores the evolution of a CCR-scheme-based dynamic mobility system toward the PUE but also highlights the distinct adaptation behaviors under periodic mobility management policies.
期刊介绍:
Transportation Research: Part B publishes papers on all methodological aspects of the subject, particularly those that require mathematical analysis. The general theme of the journal is the development and solution of problems that are adequately motivated to deal with important aspects of the design and/or analysis of transportation systems. Areas covered include: traffic flow; design and analysis of transportation networks; control and scheduling; optimization; queuing theory; logistics; supply chains; development and application of statistical, econometric and mathematical models to address transportation problems; cost models; pricing and/or investment; traveler or shipper behavior; cost-benefit methodologies.