Hongke Xie , Pengyu Yan , Mingyan Bai , Zhibin Chen
{"title":"通过车主合作、稳健的车位分配和激励性收入分配,实现高效的停车位共享计划","authors":"Hongke Xie , Pengyu Yan , Mingyan Bai , Zhibin Chen","doi":"10.1016/j.tre.2024.103697","DOIUrl":null,"url":null,"abstract":"<div><p>This article introduces an <em>intra-owner-cooperation</em> mechanism for parking-sharing programs, which assigns private parking slot owners to use other owners’ parking slots within a community and compensates them in the meanwhile. This mechanism extends the availability of some shared slots for external drivers. To ensure practicality, this study addresses two crucial issues: (i) robust assignment of parking slots to mitigate parking conflicts caused by user unpunctuality and (ii) revenue allocation encouraging owner participation through truthful report of inconvenience costs coefficient for using others’ slots. To address the first issue, we propose a distributionally robust approach that leverages a data-driven method to estimate potential conflicts in parking schedules. For the second issue, we introduce an equitable owner-Pareto-optimal core-selecting payment rule under a cooperative game setting, which prevents collusion among owners and encourages owners to truthfully report the inconvenience cost coefficients for satisfying compensation. An efficient algorithm with core constraint generation is further developed to calculate the payments within a reasonable computational time. Several practical extensions are also presented. Numerical experiments demonstrate that the proposed mechanism significantly outperforms the existing matching approach without owner cooperation in terms of parking slot utilization, fulfillment ratio of demand, and platform income. This paper demonstrates the performance of <em>intra-owner-cooperation</em> mechanism, which ultimately enhances the overall system welfare jointly enjoyed by slot owners, drivers, and the platform.</p></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":null,"pages":null},"PeriodicalIF":8.3000,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An efficient parking-sharing program through owner cooperation with robust slot assignment and incentive revenue distribution\",\"authors\":\"Hongke Xie , Pengyu Yan , Mingyan Bai , Zhibin Chen\",\"doi\":\"10.1016/j.tre.2024.103697\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This article introduces an <em>intra-owner-cooperation</em> mechanism for parking-sharing programs, which assigns private parking slot owners to use other owners’ parking slots within a community and compensates them in the meanwhile. This mechanism extends the availability of some shared slots for external drivers. To ensure practicality, this study addresses two crucial issues: (i) robust assignment of parking slots to mitigate parking conflicts caused by user unpunctuality and (ii) revenue allocation encouraging owner participation through truthful report of inconvenience costs coefficient for using others’ slots. To address the first issue, we propose a distributionally robust approach that leverages a data-driven method to estimate potential conflicts in parking schedules. For the second issue, we introduce an equitable owner-Pareto-optimal core-selecting payment rule under a cooperative game setting, which prevents collusion among owners and encourages owners to truthfully report the inconvenience cost coefficients for satisfying compensation. An efficient algorithm with core constraint generation is further developed to calculate the payments within a reasonable computational time. Several practical extensions are also presented. Numerical experiments demonstrate that the proposed mechanism significantly outperforms the existing matching approach without owner cooperation in terms of parking slot utilization, fulfillment ratio of demand, and platform income. This paper demonstrates the performance of <em>intra-owner-cooperation</em> mechanism, which ultimately enhances the overall system welfare jointly enjoyed by slot owners, drivers, and the platform.</p></div>\",\"PeriodicalId\":49418,\"journal\":{\"name\":\"Transportation Research Part E-Logistics and Transportation Review\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":8.3000,\"publicationDate\":\"2024-09-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Research Part E-Logistics and Transportation Review\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1366554524002886\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part E-Logistics and Transportation Review","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1366554524002886","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
An efficient parking-sharing program through owner cooperation with robust slot assignment and incentive revenue distribution
This article introduces an intra-owner-cooperation mechanism for parking-sharing programs, which assigns private parking slot owners to use other owners’ parking slots within a community and compensates them in the meanwhile. This mechanism extends the availability of some shared slots for external drivers. To ensure practicality, this study addresses two crucial issues: (i) robust assignment of parking slots to mitigate parking conflicts caused by user unpunctuality and (ii) revenue allocation encouraging owner participation through truthful report of inconvenience costs coefficient for using others’ slots. To address the first issue, we propose a distributionally robust approach that leverages a data-driven method to estimate potential conflicts in parking schedules. For the second issue, we introduce an equitable owner-Pareto-optimal core-selecting payment rule under a cooperative game setting, which prevents collusion among owners and encourages owners to truthfully report the inconvenience cost coefficients for satisfying compensation. An efficient algorithm with core constraint generation is further developed to calculate the payments within a reasonable computational time. Several practical extensions are also presented. Numerical experiments demonstrate that the proposed mechanism significantly outperforms the existing matching approach without owner cooperation in terms of parking slot utilization, fulfillment ratio of demand, and platform income. This paper demonstrates the performance of intra-owner-cooperation mechanism, which ultimately enhances the overall system welfare jointly enjoyed by slot owners, drivers, and the platform.
期刊介绍:
Transportation Research Part E: Logistics and Transportation Review is a reputable journal that publishes high-quality articles covering a wide range of topics in the field of logistics and transportation research. The journal welcomes submissions on various subjects, including transport economics, transport infrastructure and investment appraisal, evaluation of public policies related to transportation, empirical and analytical studies of logistics management practices and performance, logistics and operations models, and logistics and supply chain management.
Part E aims to provide informative and well-researched articles that contribute to the understanding and advancement of the field. The content of the journal is complementary to other prestigious journals in transportation research, such as Transportation Research Part A: Policy and Practice, Part B: Methodological, Part C: Emerging Technologies, Part D: Transport and Environment, and Part F: Traffic Psychology and Behaviour. Together, these journals form a comprehensive and cohesive reference for current research in transportation science.