Optimizing Urban Mobility in Hangzhou: A Case Study of the City Brain’s AI-Driven Traffic Management
This study examines Hangzhou’s City Brain as an AI-enabled traffic governance platform. Using Leong & Kumar (2023) four-dimensional ITS framework—data acquisition, connectivity, intelligence, and responsiveness, the paper evaluates operational outcomes, governance conditions, and transferability...
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| Format: | Article |
| Language: | English English |
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INTI International University
2025
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| Online Access: | http://eprints.intimal.edu.my/2171/ http://eprints.intimal.edu.my/2171/1/ij2025_25.pdf http://eprints.intimal.edu.my/2171/2/719 |
| _version_ | 1848766983783317504 |
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| author | Guo, Hanxiang Leong, Wai Yie |
| author_facet | Guo, Hanxiang Leong, Wai Yie |
| author_sort | Guo, Hanxiang |
| building | INTI Institutional Repository |
| collection | Online Access |
| description | This study examines Hangzhou’s City Brain as an AI-enabled traffic governance platform. Using Leong & Kumar (2023) four-dimensional ITS framework—data acquisition, connectivity, intelligence, and responsiveness, the paper evaluates operational outcomes, governance conditions, and transferability. We find that (i) average traffic efficiency improved in pilot corridors and (ii) emergency response times shortened markedly, with (iii) gains shaped by a public–private partnership that couples municipal mandates with cloud-scale analytics. However, challenges persist around data governance and public trust, interoperability with legacy ITS, and context-dependent scalability. Comparative references to Singapore and Amsterdam underscore how institutional design conditions technological payoffs. The case contributes practice-oriented insights for cities seeking reproducible, ethically governed AI in transport. |
| first_indexed | 2025-11-14T11:59:49Z |
| format | Article |
| id | intimal-2171 |
| institution | INTI International University |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T11:59:49Z |
| publishDate | 2025 |
| publisher | INTI International University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | intimal-21712025-09-02T08:46:21Z http://eprints.intimal.edu.my/2171/ Optimizing Urban Mobility in Hangzhou: A Case Study of the City Brain’s AI-Driven Traffic Management Guo, Hanxiang Leong, Wai Yie T Technology (General) TA Engineering (General). Civil engineering (General) TE Highway engineering. Roads and pavements This study examines Hangzhou’s City Brain as an AI-enabled traffic governance platform. Using Leong & Kumar (2023) four-dimensional ITS framework—data acquisition, connectivity, intelligence, and responsiveness, the paper evaluates operational outcomes, governance conditions, and transferability. We find that (i) average traffic efficiency improved in pilot corridors and (ii) emergency response times shortened markedly, with (iii) gains shaped by a public–private partnership that couples municipal mandates with cloud-scale analytics. However, challenges persist around data governance and public trust, interoperability with legacy ITS, and context-dependent scalability. Comparative references to Singapore and Amsterdam underscore how institutional design conditions technological payoffs. The case contributes practice-oriented insights for cities seeking reproducible, ethically governed AI in transport. INTI International University 2025-09 Article PeerReviewed text en cc_by_4 http://eprints.intimal.edu.my/2171/1/ij2025_25.pdf text en cc_by_4 http://eprints.intimal.edu.my/2171/2/719 Guo, Hanxiang and Leong, Wai Yie (2025) Optimizing Urban Mobility in Hangzhou: A Case Study of the City Brain’s AI-Driven Traffic Management. INTI JOURNAL, 2025 (25). pp. 1-6. ISSN e2600-7320 https://intijournal.intimal.edu.my |
| spellingShingle | T Technology (General) TA Engineering (General). Civil engineering (General) TE Highway engineering. Roads and pavements Guo, Hanxiang Leong, Wai Yie Optimizing Urban Mobility in Hangzhou: A Case Study of the City Brain’s AI-Driven Traffic Management |
| title | Optimizing Urban Mobility in Hangzhou: A Case Study of the City Brain’s AI-Driven Traffic Management |
| title_full | Optimizing Urban Mobility in Hangzhou: A Case Study of the City Brain’s AI-Driven Traffic Management |
| title_fullStr | Optimizing Urban Mobility in Hangzhou: A Case Study of the City Brain’s AI-Driven Traffic Management |
| title_full_unstemmed | Optimizing Urban Mobility in Hangzhou: A Case Study of the City Brain’s AI-Driven Traffic Management |
| title_short | Optimizing Urban Mobility in Hangzhou: A Case Study of the City Brain’s AI-Driven Traffic Management |
| title_sort | optimizing urban mobility in hangzhou: a case study of the city brain’s ai-driven traffic management |
| topic | T Technology (General) TA Engineering (General). Civil engineering (General) TE Highway engineering. Roads and pavements |
| url | http://eprints.intimal.edu.my/2171/ http://eprints.intimal.edu.my/2171/ http://eprints.intimal.edu.my/2171/1/ij2025_25.pdf http://eprints.intimal.edu.my/2171/2/719 |