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This paper proposes an enhanced passenger flow simulation method integrating an adaptive social force model (SFM) with a bounded rationality path decision mechanism. In the study, the probability model of route change is established to quantitatively describe the probability of passengers\u2019 route change under the influence of the bounded rationality psychology. It can more realistically reflect the routing behavior of passengers. Explore the impact of the proposed method on passenger flow evacuation in crowded areas by building a simple passenger flow simulation scenario. The experimental results show that compared with the original SFM, the proposed method can improve the evacuation efficiency by more than 26%. Validation through a typical island platform simulation experiment and a case study of a Chinese URT station demonstrates that the proposed method effectively captures key passenger flow trends in critical station areas, showing strong alignment with actual operational observations. This work advances URT crowd simulation methodologies by bridging psychological decision-making with physical movement dynamics, offering theoretical foundations for smart station planning with improved crowd perception capabilities.<\/jats:p>","DOI":"10.1177\/00375497251379904","type":"journal-article","created":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T11:11:06Z","timestamp":1761563466000},"page":"125-148","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["An improved passenger flow simulation method of urban rail transit based on adaptive social force model and bounded rational path decision mechanism"],"prefix":"10.1177","volume":"102","author":[{"given":"Jinyi","family":"Liu","sequence":"first","affiliation":[{"name":"College of Information Science and Technology, Beijing University of Chemical Technology, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7719-3301","authenticated-orcid":false,"given":"Liqiang","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology, Beijing University of Chemical Technology, China"}]},{"given":"Jinjin","family":"Tang","sequence":"additional","affiliation":[{"name":"School of Traffic and Transportation, Beijing Jiaotong University, China"}]},{"given":"Shuixiong","family":"Tang","sequence":"additional","affiliation":[{"name":"Beijing Yilu Rail Transit Engineering Corporation Limited, China"}]},{"given":"Mengqian","family":"Guo","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology, Beijing University of Chemical Technology, China"}]}],"member":"179","published-online":{"date-parts":[[2025,10,27]]},"reference":[{"key":"e_1_3_3_2_2","first-page":"2035845","article-title":"Modeling pedestrian behaviors of boarding and alighting dynamics in urban railway stations","volume":"19","author":"Qu Y","year":"2023","unstructured":"Qu Y, Liu X, Wu J, et al. 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