İç mekân navigasyon rotaları ve yayaların yürüme örüntüleri arasındaki geometrik benzerliklerin Coğrafi Bilgi Sistemi ve Çok Kriterli Karar Analizi aracılığıyla değerlendirilmesi

Öz

Navigasyon ağ modelleri aracılığıyla yayaları bir iç mekânda yönlendirirken, yayalara sunulan iç mekân rotaları, yön bulma eyleminde başarıya ulaşmaları için yayaların mekânsal bilişlerine uygun olmalı ve böylece yayaların bilişsel yüklerini azaltmalıdır. Bu açıdan, yayalara sunulan iç mekân rotaları ve onların iç mekân içerisindeki gerçek yürüyüş örüntüleri geometrik açıdan benzer olmalıdır. Bu çalışmada, literatürde sıklıkla kullanılan dört navigasyon ağ modeli çalışma alanı için oluşturulmuştur. Ardından, çalışma alanında bir kullanıcı deneyi yapılarak yayaların iç mekân yürüyüş örüntüleri toplanmış ve CBS ortamında yeniden oluşturulmuştur. Bu işlemi takiben, yayaların yürüdüğü altı segment için ağ modelleri kullanılarak iç mekân rotaları hesaplanmıştır. Daha sonra, hesaplanan iç mekân rotaları ve yayaların yürüyüş örüntüleri için çeşitli geometrik benzerlik ölçüleri hesaplanmıştır. Geometrik benzerlik ölçüleri Bulanık Analitik Hiyerarşi Süreci (BAHS) yöntemi ile ağırlıklandırılarak ağ modelleri aracılığıyla üretilen iç mekân rotaları ve yayaların yürüyüş örüntüleri geometrik benzerlik açısından İdeal Çözüme Benzerliğine Göre Tercih Sıralaması Tekniği (Technique for Order Preference by Similarity to Ideal Solution - TOPSIS) yöntemi ile karşılaştırılmıştır. Deneysel çalışmada elde edilen bulgulara göre, Orta Nokta İlişki Yapısı Segment Girişi (ONİYSG) ağ modeli, çalışma alanı için geometrik benzerlik açısından yayaların yürüyüş örüntülerine en benzer ağ modeli olarak bulunmuştur, ONİYSG ağ modelini, sırasıyla Orta Eksen Dönüşümü (OED) tabanlı ağ modeli ve Grid tabanlı ağ modeli izlemiştir. Literatürde rota uzunluğu ve dönüş sayısı kriteri için en uygun bulunan görünürlük bölümlendirmesi tabanlı Evrensel Dolaşım Ağı (EDA) ağ modeli ise geometrik benzerlik açısından en geride kalmıştır.

Anahtar Kelimeler

• İç Mekan Navigasyonu
• Ağ Modeli
• Yürüme Örüntüleri
• Geometrik Benzerlik
• Çok Kriterli Karar Verme

Evaluating geometric similarities between indoor navigation routes and walking patterns of pedestrians through Geographic Information System and Multi-Criteria Decision Analysis

Öz

While guiding pedestrians in an indoor space through navigation network models, indoor routes conveyed to pedestrians should comply with their spatial reasoning to achieve success in wayfinding, thus reducing the cognitive load of pedestrians. In this respect, the indoor routes and actual walking patterns of pedestrians should be geometrically similar. In this study, four navigation network models frequently used in the literature were created for the study area. Then, a user experiment was conducted in the study area, and the walking patterns of the pedestrians were collected and regenerated in the GIS environment. Following this process, indoor routes were calculated using network models for the six segments where pedestrians walked. Then, various geometric similarity measures were calculated for the indoor routes and walking patterns of the pedestrians. The geometric similarity measures were weighted with the Fuzzy Analytical Hierarchy Process (FAHP) method, and the indoor routes were computed through network models, and the walking patterns of pedestrians were compared with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method in terms of geometric similarity. According to the findings of the experimental study, the Middle Point Relation Structure Segment Entrance (MPRSSE) network model was found to be the most similar to pedestrian walking patterns for the study area in terms of geometric similarity. The MPRSSE network model was followed by the Medial Axis Transform (MAT) based network model and the Grid based network model, respectively. The visibility partitioning-based Universal Circulation Network (UCN) network model, which was found to be the most suitable for route length and number of turns criteria in the literature, fell behind in terms of geometric similarity.

Anahtar Kelimeler

• Indoor Navigation
• Network Model
• Walking Patterns
• Geometric Similarity
• Multi-Criteria Decision Making

Kaynakça

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