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Erişilebilir Akıllı Şehirler İçin Dijital Bir Adım: Engelsiz Ulaşım Haritası Platformu Örneği

Yıl 2025, Sayı: Akıllı Şehirler, 160 - 178, 01.12.2025

Öz

Hızla artan kentleşme, hareket kabiliyeti kısıtlı bireyler için şehir içi hareketliliği daha
karmaşık hale getirmektedir. Tekerlekli sandalye kullanıcıları, yaşlılar, bebek arabası
kullanıcıları ve geçici hareket kısıtlılığı bulunan gruplar günlük yaşamda ciddi erişim
engelleriyle karşılaşmaktadır. Uluslararası girişimler dijital haritalama, kullanıcı katkısına
dayalı veri toplama (crowdsourcing) ve erişilebilirlik odaklı rotalama çözümlerinin
potansiyelini göstermiştir ancak mevcut bu girişimlerin çoğu yeterli düzeyde
yaygınlaşmamıştır veya erişilebilirlik bilgisi içeriği sınırlı düzeyde sunulmaktadır. Bu
çalışmada, Türkiye’de ilk kez kapsamlı bir erişilebilirlik platformu geliştirilmesini hedefleyen
Engelsiz Ulaşım Haritası Platformu için bir öneri model ortaya koymaktadır.
Önerilen model, kullanıcı katkısına dayalı veri toplama (crowdsourcing), yapay zekâ
desteği ile farklı kaynaklardan toplanan verileri doğrulama ve CBS tabanlı mekânsal
analizleri bir araya getirerek sürekli güncellenen dinamik bir yapı içermektedir. Platformun
hem mobil uygulama hem de web tabanlı erişim seçenekleri, farklı kullanıcı
gruplarına katılım imkânı tanımakta; açık API yapısı sayesinde yerel yönetimlerin kent
bilgi sistemleriyle entegrasyona olanak sağlamaktadır. Teknolojik altyapının yanı sıra,
modelin sosyal, çevresel, ekonomik ve sürdürülebilirlik boyutları da analiz edilmiştir.
Platform, toplumsal katılımı ve bağımsız yaşamı desteklemekte, sürdürülebilir kentsel
hareketliliğe katkı sunmakta, yerel işletmeler için ekonomik fırsatlar yaratmakta ve çok
paydaşlı iş birlikleriyle uzun vadeli sürdürülebilirlik hedeflenmektedir. Sonuç olarak,
Engelsiz Ulaşım Haritası Platformu, Türkiye’de erişilebilirlik bilgilendirmesi boşluğunu
doldurmayı amaçlayan teknolojik yenilikleri sosyal kapsayıcılık, çevresel sorumluluk ve
ekonomik uygulanabilirlik ile bütünleştirerek akıllı şehirler için kapsayıcı ve veri temelli
bir çözüm sunmaktadır.

Kaynakça

  • Asghari, H., Stolberg-Larsen, J., & Züger, T. (2022, April 28). “Approximating Accessibility of Regions from Incomplete Volunteered Data.” Conference on Human Factors in Computing Systems - Proceedings. https://doi.org/10.1145/3491101.3519706.
  • Beale, L., Field, K., Briggs, D., Picton, P., & Matthews, H. (2006). “Mapping for wheelchair users: Route navigation in urban spaces.” Cartographic Journal, 43(1), 68–81. https://doi.org/10.1179/000870406X93517.
  • Biagi, L., Brovelli, M. A., & Stucchi, L. (2020). “Mapping the accessibility in openstreetmap: A comparison of different techniques.” International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 43(B4), 229–236. https://doi.org/10.5194/isprs-archives-XLIII-B4-2020-229-2020.
  • Fernandes, J., Machado, J., Duarte, J., & Peixoto, H. (2024). “Innovative mobile solutions for visual and mobility disabilities: a comprehensive overview.” Procedia Computer Science, 251, 684–689. https://doi.org/10.1016/j.procs.2024.11.169.
  • Ferretti, E. C., Curi, H. T., Andrade, L. F., Cooper, R. A., & Soárez, P. C. de. (2024). “Conceptual mapping proposed to comprehend the effect of wheelchair mobility on social participation and quality of life: a systematic review*.” Disability and Rehabilitation: Assistive Technology (cilt: 19, sayı: 3, s. 814–830). Taylor and Francis Ltd. https://doi.org/10.1080/17483107.2022.2126904.
  • Hong, S. (2025). “A pilot study on mapping wheelability in urban environment.” Disability and Rehabilitation: Assistive Technology. Taylor and Francis Ltd. https:// doi.org/10.1080/17483107.2025.2539437.
  • Meng, S., Su, X., Sun, G., Li, M., & Xue, F. (2025). “From 3D pedestrian networks to wheelable networks: An automatic wheelability assessment method for highdensity urban areas using contrastive deep learning of smartphone point clouds.” Computers, Environment and Urban Systems, 117. https://doi.org/10.1016/j. compenvurbsys.2025.102255.
  • Mobasheri, A., Deister, J., & Dieterich, H. (2017). “Wheelmap: the wheelchair accessibility crowdsourcing platform.” Open Geospatial Data, Software and Standards, 2(1). https://doi.org/10.1186/s40965-017-0040-5.
  • Suryotrisongko, H., Kusuma, R. C., & Ginardi, R. H. (2017). “four-Hospitality: Friendly Smart City Design for Disability.” Procedia Computer Science, 124, 615–623. https:// doi.org/10.1016/j.procs.2017.12.197.
  • Ullrich, P., Hummel, M., Buchner, T., Hauer, K., Bauer, J. M., & Werner, C. (2024). “Translation, feasibility, and construct validity of a German version of the Stakeholders Walkability/Wheelability Audit in neighbourhoods in older adults.” Journal of Transport and Health, 36. https://doi.org/10.1016/j.jth.2024.101802.
  • Verma, A., Shrivastava, S., & Ramkumar, J. (2024). “Mapping wheelchair functions and their associated functional elements for stair climbing accessibility: a systematic review.” Disability and Rehabilitation: Assistive Technology (cilt: 19, sayı: 1, s. 200–221). Taylor and Francis Ltd. https://doi.org/10.1080/17483107.2022.2075476.
  • Voigt, C., Dobner, S., Ferri, M., Hahmann, S., & Gareis, K. (2016). “Community engagement strategies for crowdsourcing accessibility information: Paper, Wheelmaptags and Mapillary-walks.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9759, 257–264. https://doi.org/10.1007/978-3-319-41267-2_35.

A Digital Step Toward Accessible Smart Cities: Accessible Transportation Map Platform Case Study

Yıl 2025, Sayı: Akıllı Şehirler, 160 - 178, 01.12.2025

Öz

Rapid urbanization is making urban mobility increasingly complex for individuals with limited physical abilities. Wheelchair users, older adults, stroller users, and groups with temporary mobility restrictions face significant accessibility barriers in their daily lives. International initiatives have demonstrated the potential of digital mapping, crowdsourced data collection, and accessibility-focused routing solutions; however, most of these efforts have not achieved sufficient scale or provide only limited accessibility information. This study proposes a model for the Accessible Transportation Map Platform, aiming to develop Türkiye’s first comprehensive accessibility platform. The proposed model integrates crowdsourced data collection, AI-assisted verification of data from multiple sources, and GIS-based spatial analysis to create a continuously updated and dynamic structure. By offering both mobile and web-based access, the platform enables participation from diverse user groups, while its open API structure allows integration with municipal urban information systems. In addition to the technological infrastructure, the model is examined through its social, environmental, economic, and sustainability dimensions. The platform supports social participation and independent living, contributes to sustainable urban mobility, creates economic opportunities for local businesses, and ensures long term sustainability through multi-stakeholder collaborations. In conclusion, the Accessible Transportation Map Platform addresses the current gap in accessibility information in Türkiye by combining technological innovation with social inclusion, environmental responsibility, and economic feasibility, thereby offering an inclusive and data-driven solution for smart cities.

Kaynakça

  • Asghari, H., Stolberg-Larsen, J., & Züger, T. (2022, April 28). “Approximating Accessibility of Regions from Incomplete Volunteered Data.” Conference on Human Factors in Computing Systems - Proceedings. https://doi.org/10.1145/3491101.3519706.
  • Beale, L., Field, K., Briggs, D., Picton, P., & Matthews, H. (2006). “Mapping for wheelchair users: Route navigation in urban spaces.” Cartographic Journal, 43(1), 68–81. https://doi.org/10.1179/000870406X93517.
  • Biagi, L., Brovelli, M. A., & Stucchi, L. (2020). “Mapping the accessibility in openstreetmap: A comparison of different techniques.” International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 43(B4), 229–236. https://doi.org/10.5194/isprs-archives-XLIII-B4-2020-229-2020.
  • Fernandes, J., Machado, J., Duarte, J., & Peixoto, H. (2024). “Innovative mobile solutions for visual and mobility disabilities: a comprehensive overview.” Procedia Computer Science, 251, 684–689. https://doi.org/10.1016/j.procs.2024.11.169.
  • Ferretti, E. C., Curi, H. T., Andrade, L. F., Cooper, R. A., & Soárez, P. C. de. (2024). “Conceptual mapping proposed to comprehend the effect of wheelchair mobility on social participation and quality of life: a systematic review*.” Disability and Rehabilitation: Assistive Technology (cilt: 19, sayı: 3, s. 814–830). Taylor and Francis Ltd. https://doi.org/10.1080/17483107.2022.2126904.
  • Hong, S. (2025). “A pilot study on mapping wheelability in urban environment.” Disability and Rehabilitation: Assistive Technology. Taylor and Francis Ltd. https:// doi.org/10.1080/17483107.2025.2539437.
  • Meng, S., Su, X., Sun, G., Li, M., & Xue, F. (2025). “From 3D pedestrian networks to wheelable networks: An automatic wheelability assessment method for highdensity urban areas using contrastive deep learning of smartphone point clouds.” Computers, Environment and Urban Systems, 117. https://doi.org/10.1016/j. compenvurbsys.2025.102255.
  • Mobasheri, A., Deister, J., & Dieterich, H. (2017). “Wheelmap: the wheelchair accessibility crowdsourcing platform.” Open Geospatial Data, Software and Standards, 2(1). https://doi.org/10.1186/s40965-017-0040-5.
  • Suryotrisongko, H., Kusuma, R. C., & Ginardi, R. H. (2017). “four-Hospitality: Friendly Smart City Design for Disability.” Procedia Computer Science, 124, 615–623. https:// doi.org/10.1016/j.procs.2017.12.197.
  • Ullrich, P., Hummel, M., Buchner, T., Hauer, K., Bauer, J. M., & Werner, C. (2024). “Translation, feasibility, and construct validity of a German version of the Stakeholders Walkability/Wheelability Audit in neighbourhoods in older adults.” Journal of Transport and Health, 36. https://doi.org/10.1016/j.jth.2024.101802.
  • Verma, A., Shrivastava, S., & Ramkumar, J. (2024). “Mapping wheelchair functions and their associated functional elements for stair climbing accessibility: a systematic review.” Disability and Rehabilitation: Assistive Technology (cilt: 19, sayı: 1, s. 200–221). Taylor and Francis Ltd. https://doi.org/10.1080/17483107.2022.2075476.
  • Voigt, C., Dobner, S., Ferri, M., Hahmann, S., & Gareis, K. (2016). “Community engagement strategies for crowdsourcing accessibility information: Paper, Wheelmaptags and Mapillary-walks.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9759, 257–264. https://doi.org/10.1007/978-3-319-41267-2_35.
Toplam 12 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Şehir ve Bölge Planlama
Bölüm Araştırma Makalesi
Yazarlar

Mustafa Eruyar 0000-0003-0181-675X

Gönderilme Tarihi 8 Eylül 2025
Kabul Tarihi 19 Eylül 2025
Yayımlanma Tarihi 1 Aralık 2025
Yayımlandığı Sayı Yıl 2025 Sayı: Akıllı Şehirler

Kaynak Göster

APA Eruyar, M. (2025). Erişilebilir Akıllı Şehirler İçin Dijital Bir Adım: Engelsiz Ulaşım Haritası Platformu Örneği. Çevre Şehir ve İklim Dergisi(Akıllı Şehirler), 160-178.