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Journals / Akıllı Ulaşım Sistemleri ve Uygulamaları Dergisi / 2026 / Cilt: 8 Sayı: 1

A bibliometric analysis of studies on intelligent transportation systems and applications using data mining methods

Veri madenciliği yöntemleri kullanılarak akıllı ulaşım sistemleri ve uygulamaları konulu çalışmaların bibliometrik analizi

Kadir Kesgin(BANDIRMA ONYEDİ EYLÜL ÜNİVERSİTESİ)0000-0001-5973-8622
Dilek Zeren Özer(ULUDAG UNIVERSITY)0000-0003-4869-0015
Pages
184–203
Publication Date
2025-03-25
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

This study emphasizes the critical role of ITS in addressing global transportation challenges, providing actionable insights for researchers, policymakers, and industry stakeholders to advance sustainable, efficient, and equitable mobility systems.

📌 3 Key Takeaways

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Objective & Hypothesis:This study conducts a bibliometric analysis of Intelligent Transportation Systems (ITS) research, using data from Web of Science (WoS), Scopus, and TR Dizin covering 2015–2024.
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Key Findings & Data:The analysis reveals a 440% increase in annual publications, driven by advancements in artificial intelligence (AI), the Internet of Things (IoT), and sustainability-focused technologies.
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Conclusion & Impact:This study emphasizes the critical role of ITS in addressing global transportation challenges, providing actionable insights for researchers, policymakers, and industry stakeholders to advance sustainable, efficient, and equitable mobility systems.
🔬Design:Modeling & Simulation
📍Scope:2015–2024 Verileri
⚙️Variables:Akıllı ulaşım sistemleri · Yapay Zeka (AI) · Nesnelerin İnterneti (IoT)

Abstract

This study conducts a bibliometric analysis of Intelligent Transportation Systems (ITS) research, using data from Web of Science (WoS), Scopus, and TR Dizin covering 2015–2024. The analysis reveals a 440% increase in annual publications, driven by advancements in artificial intelligence (AI), the Internet of Things (IoT), and sustainability-focused technologies. Dominant research themes include IoT, machine learning, and smart city solutions, with sustainability-related topics such as eco-routing and renewable energy integration gaining prominence. Geographic analysis identifies India, China, and the United States as leading contributors, while emerging economies like Turkey and South Korea are expanding their research footprints. Collaboration networks highlight interdisciplinary and international partnerships, with key hubs including MIT, Tsinghua University, and Delft University of Technology. Machine learning models predict steady growth in ITS publications, projecting approximately 950 annual outputs by 2026. Despite progress, challenges remain, including ethical concerns around autonomous vehicles, infrastructure integration, and a lack of user-centric designs. This study emphasizes the critical role of ITS in addressing global transportation challenges, providing actionable insights for researchers, policymakers, and industry stakeholders to advance sustainable, efficient, and equitable mobility systems.

Özet

Bu çalışma, 2015-2024 yılları arasında Web of Science (WoS), Scopus ve TR Dizin veritabanlarından elde edilen verilerle Akıllı Ulaşım Sistemleri (AUS) araştırmalarının bibliyometrik bir analizini sunmaktadır. Analiz, yıllık yayınlarda %440’lık bir artış olduğunu ortaya koymuş, bu artışın yapay zeka (AI), Nesnelerin İnterneti (IoT) ve sürdürülebilirlik odaklı teknolojilerdeki gelişmelerle desteklendiği görülmüştür. Çalışmada IoT, makine öğrenimi ve akıllı şehir çözümleri gibi konuların başlıca araştırma temaları olduğu, eko-yönlendirme ve yenilenebilir enerji entegrasyonu gibi sürdürülebilirlik temalı konuların ise giderek önem kazandığı belirlenmiştir. Coğrafi analiz, Hindistan, Çin ve Amerika Birleşik Devletleri'nin önde gelen katkı sağlayıcılar olduğunu, Türkiye ve Güney Kore gibi gelişmekte olan ekonomilerin ise araştırma alanında büyüyen etkisini göstermektedir. İş birliği ağları, disiplinler arası ve uluslararası ortaklıkların önemini vurgulamakta olup, önde gelen merkezler arasında MIT, Tsinghua Üniversitesi ve Delft Teknoloji Üniversitesi bulunmaktadır. Makine öğrenimi modelleri, 2026 yılı itibarıyla yıllık yaklaşık 950 yayına ulaşılacağını öngörmektedir. Ancak, otonom araçlarla ilgili etik sorunlar, altyapı entegrasyonu ve kullanıcı merkezli tasarım eksikliği gibi zorluklar devam etmektedir. Bu çalışma, AUS'un küresel ulaşım sorunlarını çözmedeki kritik rolünü vurgulamakta ve sürdürülebilir, verimli ve adil hareketlilik sistemlerini ilerletmek için araştırmacılara, politika yapıcılara ve sektör paydaşlarına uygulanabilir öneriler sunmaktadır.

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Cite This Article

Kesgin, K., Özer, D. Z. (2025). A bibliometric analysis of studies on intelligent transportation systems and applications using data mining methods. Akıllı Ulaşım Sistemleri ve Uygulamaları Dergisi, Cilt: 8 Sayı: 1, 184–203. https://doi.org/10.51513/jitsa.1607689

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