{"paper_id":"100441c6-b4d0-46ef-b65b-e11435191f77","body_text":"Advancing Passenger Next Station Prediction via Collaborative Knowledge Graph Representational Learning | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Advancing Passenger Next Station Prediction via Collaborative Knowledge Graph Representational Learning Xiaoqi Duan, Jianlong Wang, Zhibang Xu, Wenxin Teng, Youliang Tian This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5691827/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Conventional passenger next station prediction models are often restricted by rigid graph structures, failing to account for the dynamic interactions between passengers and stations. This limitation results in an insufficient representation of travel patterns and associated knowledge. To address these shortcomings, this paper proposes a novel approach that integrates reinforcement learning with knowledge graphs to enable a holistic fusion of heterogeneous data. The proposed method enriches the environmental variables within reinforcement learning frameworks and introduces collaborative updating mechanisms for representing passenger-station interactions based on human travel knowledge graphs. These enhanced representations are then employed to improve the accuracy of next-station prediction. To evaluate the effectiveness of the approach, ablation experiments and comparative analyses with classical algorithms were conducted. The results demonstrate that the proposed method significantly outperforms existing models in predicting next-stations, routes, and travel distances, establishing its efficacy in capturing complex passenger travel behaviors. Earth and environmental sciences/Ecology/Population dynamics Earth and environmental sciences/Environmental social sciences/Sustainability Earth and environmental sciences/Solid earth sciences/Geophysics Next-station prediction Knowledge Graph Representational learning Smart card data Reinforcement learning Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 07 Jul, 2025 Reviews received at journal 08 Apr, 2025 Reviewers agreed at journal 07 Apr, 2025 Reviewers invited by journal 07 Apr, 2025 Submission checks completed at journal 04 Apr, 2025 First submitted to journal 25 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-5691827\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Article\",\"associatedPublications\":[],\"authors\":[{\"id\":440363663,\"identity\":\"0c472214-5962-45e2-a9a5-44d62c6e8a01\",\"order_by\":0,\"name\":\"Xiaoqi Duan\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Guizhou University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Xiaoqi\",\"middleName\":\"\",\"lastName\":\"Duan\",\"suffix\":\"\"},{\"id\":440363664,\"identity\":\"bef65d14-63c1-4331-80c0-9f7c006da61b\",\"order_by\":1,\"name\":\"Jianlong Wang\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/ElEQVRIiWNgGAWjYLACCQMGBj4Q4wPDARBlQJwWNiDNOINoLSAA0sLMQ4wWg+NnD7+wKLDLY2PvPfzatu1OYgN78zYJhpo7uLWcyUuzkDBILmbjOZdmndv2LLGB51iZBMOxZzi1mB3IMTOQMGBObJPIMTPO3XY4sQHIkGBsOIxby/k3IC31EC2WIC3ybwhouZFj/EDC4DBIi/FjRrAtPPi12N94YwYM5OOJbTxnzBh7/x02buNJK7ZIOIZbi2R/jvFniT/Vif3sPcYffpw5LNvPfnjjjQ81uLUAAZu0BJQBpkERxJCATwMwAj9+gDI+4Fc4CkbBKBgFIxUAADGkVc7a8jOZAAAAAElFTkSuQmCC\",\"orcid\":\"\",\"institution\":\"Changjiang Spatial Information Technology Engineering Co., Ltd. (Wuhan)\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Jianlong\",\"middleName\":\"\",\"lastName\":\"Wang\",\"suffix\":\"\"},{\"id\":440363665,\"identity\":\"f9a54407-77bd-4335-90f1-a6d7d825f23d\",\"order_by\":2,\"name\":\"Zhibang Xu\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Chinese academy of sciences\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Zhibang\",\"middleName\":\"\",\"lastName\":\"Xu\",\"suffix\":\"\"},{\"id\":440363666,\"identity\":\"b2b2fd35-7b2c-43cb-86c4-df60ec1053f3\",\"order_by\":3,\"name\":\"Wenxin Teng\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Wuhan university\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Wenxin\",\"middleName\":\"\",\"lastName\":\"Teng\",\"suffix\":\"\"},{\"id\":440363667,\"identity\":\"249c557e-c74b-45d1-9781-158dad4c4991\",\"order_by\":4,\"name\":\"Youliang Tian\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Guizhou University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Youliang\",\"middleName\":\"\",\"lastName\":\"Tian\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2024-12-22 03:08:05\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-5691827/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-5691827/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":80276379,\"identity\":\"016be586-49a4-495d-bd78-3d77c40604b9\",\"added_by\":\"auto\",\"created_at\":\"2025-04-10 05:04:55\",\"extension\":\"pdf\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":1011641,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"MS0315revisedclean.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5691827/v1_covered_5e9db176-86d3-43cd-9963-a1f3e20d9972.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Advancing Passenger Next Station Prediction via Collaborative Knowledge Graph Representational Learning\",\"fulltext\":[],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":false,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":true,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":true,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"scientific-reports\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"scirep\",\"sideBox\":\"Learn more about [Scientific Reports](http://www.nature.com/srep/)\",\"snPcode\":\"\",\"submissionUrl\":\"\",\"title\":\"Scientific Reports\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"Scientific Reports\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Next-station prediction, Knowledge Graph, Representational learning, Smart card data, Reinforcement learning\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-5691827/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-5691827/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003e \\u003cb\\u003eConventional passenger next station prediction models are often restricted by rigid graph structures, failing to account for the dynamic interactions between passengers and stations. This limitation results in an insufficient representation of travel patterns and associated knowledge. To address these shortcomings, this paper proposes a novel approach that integrates reinforcement learning with knowledge graphs to enable a holistic fusion of heterogeneous data. The proposed method enriches the environmental variables within reinforcement learning frameworks and introduces collaborative updating mechanisms for representing passenger-station interactions based on human travel knowledge graphs. These enhanced representations are then employed to improve the accuracy of next-station prediction. To evaluate the effectiveness of the approach, ablation experiments and comparative analyses with classical algorithms were conducted. The results demonstrate that the proposed method significantly outperforms existing models in predicting next-stations, routes, and travel distances, establishing its efficacy in capturing complex passenger travel behaviors.\\u003c/b\\u003e \\u003c/p\\u003e\",\"manuscriptTitle\":\"Advancing Passenger Next Station Prediction via Collaborative Knowledge Graph Representational Learning\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-04-10 04:32:49\",\"doi\":\"10.21203/rs.3.rs-5691827/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Revision requested\",\"date\":\"2025-07-07T10:04:28+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-04-09T02:54:35+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"307881084916376391946043799274311028656\",\"date\":\"2025-04-07T08:43:46+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2025-04-07T08:14:35+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2025-04-04T09:10:50+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"Scientific Reports\",\"date\":\"2025-03-26T02:01:15+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"scientific-reports\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"scirep\",\"sideBox\":\"Learn more about [Scientific Reports](http://www.nature.com/srep/)\",\"snPcode\":\"\",\"submissionUrl\":\"\",\"title\":\"Scientific Reports\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"Scientific Reports\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"de710269-954a-4ee6-85d3-586dc1c1e965\",\"owner\":[],\"postedDate\":\"April 10th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"under-review\",\"subjectAreas\":[{\"id\":46881822,\"name\":\"Earth and environmental sciences/Ecology/Population dynamics\"},{\"id\":46881823,\"name\":\"Earth and environmental sciences/Environmental social sciences/Sustainability\"},{\"id\":46881824,\"name\":\"Earth and environmental sciences/Solid earth sciences/Geophysics\"}],\"tags\":[],\"updatedAt\":\"2026-05-10T08:53:15+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2025-04-10 04:32:49\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-5691827\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-5691827\",\"identity\":\"rs-5691827\",\"version\":[\"v1\"]},\"buildId\":\"XKTyCvWXoU3ODBz1xrDgd\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}