{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T13:30:11Z","timestamp":1777901411296,"version":"3.51.4"},"reference-count":10,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2019,11,14]],"date-time":"2019-11-14T00:00:00Z","timestamp":1573689600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100009592","name":"beijing municipal science and technology commission","doi-asserted-by":"publisher","award":["No. Z171100001117100"],"award-info":[{"award-number":["No. Z171100001117100"]}],"id":[{"id":"10.13039\/501100009592","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"national natural science foundation of china","doi-asserted-by":"publisher","award":["No. 51578028"],"award-info":[{"award-number":["No. 51578028"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Science Progress"],"published-print":{"date-parts":[[2020,1]]},"abstract":"<jats:p>Urban public transport is a very essential mode for urban residents\u2019 commute travel; however, the unbalanced spatial and temporal distribution of travel demand usually leads to passenger flow congestion risk at certain section and time. Meanwhile, the risk is short of quantified description. Based on the Pressure-State-Response framework, the study puts forward three bus passenger flow congestion risk evaluation indexes including the alternative pressure, the congestion intensity, and the transport efficiency. Then, the evaluation model is proposed based on the entropy method, and the risk is divided into four levels by K-means clustering. The article considers the 3rd Ring Road corridor in Beijing as a case to identify the risk level. The results show that the risk in the peak hours of weekdays is generally about 1.5 times higher than the risk in the weekends. The congestion risk is stable in level 3 during the majority time of morning peak hours. The duration intensity of level 4 risk is less than 0.1 during weekdays, indicating that the highest flow congestion can be quickly evacuated in a short time. The integrated passenger risk identification and evaluation model was proposed to identify the passenger flow risk level and induce the network flow distribution more reasonable. The study also provides technical support for ensuring the public transit system safety.<\/jats:p>","DOI":"10.1177\/0036850419883567","type":"journal-article","created":{"date-parts":[[2019,11,15]],"date-time":"2019-11-15T02:15:21Z","timestamp":1573784121000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":3,"title":["Bus passenger flow congestion risk evaluation model based on the Pressure-State-Response framework: A case study in Beijing"],"prefix":"10.1177","volume":"103","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1594-8836","authenticated-orcid":false,"given":"Siyong","family":"Ma","sequence":"first","affiliation":[{"name":"Key Laboratory of Transportation Engineering, Beijing University of Technology, Beijing, P.R. 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China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dimitrios","family":"Alivanistos","sequence":"additional","affiliation":[{"name":"Knowledge Representation and Reasoning Group, Computer Science Department, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pengfei","family":"Lin","sequence":"additional","affiliation":[{"name":"Key Laboratory of Transportation Engineering, Beijing University of Technology, Beijing, P.R. 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