Simulation Based Decision Intelligence Model for Multicopter Charging Stations in Smart Cities

Yıl 2026, Cilt: 5 Sayı: 1, 169 - 217, 28.02.2026

Kübra Çelik , Haluk Eren

https://doi.org/10.62520/fujece.1768822

https://izlik.org/JA87CR66ZN

Öz

Urban air mobility increasingly relies on autonomous multicopter fleets whose operational sustainability remains constrained by the absence of intelligent recharging infrastructures. This study introduces a simulation based decision intelligence model designed to evaluate six multicopter charging station archetypes under smart city conditions. The proposed framework integrates five normalized evaluation factors, namely Security, Infrastructure Cost, Logistics Compatibility, Smart City Integration, and Sustainability, within a transparent and auditable multi-criteria decision framework. Two complementary evaluation modes are developed to ensure analytical rigor and interpretability. The first mode, Mode A, represents a reproducible baseline configuration that employs equal weighting to retained methodological clarity. The second mode, Mode B, functions as a bounded coordination operator that establishes a controlled relationship between infrastructure capacity and logistics flow, enabling interaction informed evaluation without altering the ranking logic. Synthetic decision data are generated through Latin Hypercube Sampling, while bootstrap resampling is used to quantify uncertainty. The stability of both modes is analytically verified, showing that Kendall’s τ exceeds 0.90 and Top-k retention remains above 95 percent. These results demonstrate that introducing interaction awareness refines interpretability while maintaining analytical consistency across uncertainty ranges. The findings reveal that Last Mile and First Mile stations maintain the highest composite efficiency scores, 0.82 and 0.80 respectively, across various urban morphologies. Roof and Electric Vehicle Coupled configurations also display competitive scalability and improved performance when aligned with renewable energy scenarios. The overall framework provides a reproducible, policy aligned, and scientifically traceable foundation for the planning, deployment, and empirical calibration of urban drone charging networks. It further establishes a consistent methodological pathway for decision making in data scarce environments, ensuring that analytical transparency and operational relevance are sustained throughout future pilot implementations.

Anahtar Kelimeler

Autonomous UAV recharging , Intelligent decision , Smart city logistics , Sustainability , Urban air mobility (UAM).

Etik Beyan

Ethics committee approval was not required for this study; no external funding was received, and the authors declare no competing interests.

Akıllı Şehirlerdeki Multikopter Şarj İstasyonları için Simülasyon Tabanlı Karar Zekası Modeli

https://izlik.org/JA87CR66ZN

Öz

Kentsel hava hareketliliği giderek artan biçimde otonom çok rotorlu hava aracı filolarına dayanmaktadır. Ancak bu filoların operasyonel sürdürülebilirliği, akıllı şarj altyapılarının eksikliği nedeniyle hâlâ önemli ölçüde sınırlıdır. Bu çalışma, akıllı şehir koşulları altında altı farklı çok rotorlu şarj istasyonu arketipini değerlendirmek üzere tasarlanmış simülasyon temelli bir karar zekâsı modeli sunmaktadır. Önerilen çerçeve, Güvenlik, Altyapı Maliyeti, Lojistik Uyumluluk, Akıllı Şehir Entegrasyonu ve Sürdürülebilirlik olmak üzere beş normalleştirilmiş değerlendirme faktörünü, şeffaf ve denetlenebilir bir çok ölçütlü karar yapısı içinde birleştirmektedir. Analitik titizliği ve yorumlanabilirliği güvence altına almak amacıyla iki tamamlayıcı değerlendirme modu geliştirilmiştir. İlk mod olan Mode A, eşit ağırlıklar kullanan ve yöntemsel açıklığı koruyan tekrarlanabilir bir temel yapı sunmaktadır. İkinci mod olan Mode B ise altyapı kapasitesi ile lojistik akış arasında kontrollü bir ilişki kuran sınırlı bir koordinasyon operatörü olarak işlev görmekte ve etkileşim farkındalığını sıralama mantığını değiştirmeden sisteme dâhil etmektedir. Karar verileri Latin Hiperküp Örneklemesi yöntemiyle sentetik olarak üretilmiş, belirsizlik ise bootstrap yeniden örnekleme tekniğiyle nicel biçimde hesaplanmıştır. Her iki modun da kararlılığı analitik olarak doğrulanmış, sonuçlar Kendall’s τ değerinin 0.90’ın üzerinde, Top-k korunum oranının ise yüzde 95’in üzerinde olduğunu göstermiştir. Bu bulgular, etkileşim farkındalığının yorum gücünü artırırken analitik tutarlılığı koruduğunu kanıtlamaktadır. Elde edilen sonuçlar, Son Mil ve İlk Mil istasyonlarının farklı kentsel morfolojilerde en yüksek bileşik verimlilik puanlarını (sırasıyla 0.82 ve 0.80) koruduğunu ortaya koymuştur. Çatı ve Elektrikli Araç Entegreli istasyon konfigürasyonları da yenilenebilir enerjiyle uyumlu senaryolarda rekabetçi bir ölçeklenebilirlik ve gelişmiş performans sergilemiştir. Geliştirilen genel çerçeve, kentsel drone şarj ağlarının planlanması, uygulanması ve ampirik olarak kalibre edilmesi için tekrarlanabilir, politika açısından uyumlu ve bilimsel olarak izlenebilir bir temel sunmaktadır. Ayrıca veri eksikliği bulunan ortamlarda karar alma süreçlerine yönelik tutarlı bir yöntemsel yol haritası oluşturmakta, analitik şeffaflık ve operasyonel anlamlılığın gelecekteki pilot uygulamalar boyunca korunmasını sağlamaktadır.

Anahtar Kelimeler

Otonom İHA şarjı , Akıllı karar , Akıllı şehir lojistiği , Sürdürülebilirlik , Kentsel hava mobilitesi.

Etik Beyan

Bu çalışma için etik kurul onayı gerekmemiştir; herhangi bir dış finansman alınmamıştır ve yazarlar çıkar çatışması olmadığını beyan ederler.

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