Otonom Araçlarda Yapay Zekâ Araştırmalarının Evrimi (2015–2025): Bibliyometrik ve Tematik Bir İnceleme

Abstract

Bu çalışma, 2015–2025 döneminde otonom araçlar (OA) alanındaki yapay zekâ (YZ) araştırmalarını kapsamlı bir bibliyometrik ve tematik incelemeyle ele almaktadır. Web of Science (WoS) veri tabanında dizinlenen 856 akademik yayına dayanan analizde, yayın eğilimleri, atıf dinamikleri, iş birliği ağları, anahtar kelime eş-oluşumları ve bibliyografik eşleşmeler VOSviewer ve Excel programları kullanılarak haritalanmıştır. Ayrıca, en çok atıf alan 25 makale üzerinden yapılan içerik analizi, baskın araştırma temaları ve metodolojik yaklaşımları ortaya koymaktadır. Bulgular, 2019 sonrası yayın hacmi ve akademik etki açısından dikkate değer bir artış olduğunu ve derin öğrenme, planlama algoritmaları, Endüstri 4.0 entegrasyonu ve akıllı ulaşım sistemlerine yoğunlaşan bir ilgi bulunduğunu göstermektedir. Amerika Birleşik Devletleri, Çin ve Birleşik Krallık, araştırma çıktıları ve küresel iş birliklerinde başı çekmektedir. Ancak, etik, düzenleyici ve toplumsal boyutların belirgin biçimde yeterince temsil edilmediği disipliner bir dengesizlik tespit edilmiştir. Nicel bibliyometrik yöntemleri nitel tematik analizle birleştiren bu inceleme, YZ destekli otonom mobilitenin evrimine bütüncül bir bakış sunmakta ve gelecekteki araştırmalar için kavramsal ve metodolojik öneriler getirmektedir. Çalışma, hızla dönüşen otonom araç teknolojileri alanında yön bulmak isteyen akademisyenler, politika yapıcılar ve sektör temsilcileri için değerli bir rehber niteliği taşımaktadır.

Keywords

• Otonom Araçlar
• Yapay Zekâ
• Bibliyometrik Analiz
• Tematik Analiz
• Akıllı Ulaşım Sistemleri
• VOSviewer

The Evolution of Artificial Intelligence Research in Autonomous Vehicles (2015–2025): A Bibliometric and Thematic Review

Abstract

This study presents a comprehensive bibliometric and thematic review of artificial intelligence (AI) research in the domain of autonomous vehicles (AV) over the period 2015–2025. Based on 856 academic publications indexed in the Web of Science (WoS) database, the analysis utilizes VOSviewer and Excel to map publication trends, citation dynamics, collaborative networks, keyword co-occurrences, and bibliographic coupling. Furthermore, content analysis of the top 25 most-cited articles reveals dominant research themes and methodological approaches. The findings show a substantial surge in publication volume and scholarly impact after 2019, with core attention given to deep learning, planning algorithms, Industry 4.0 integration, and intelligent transportation systems. The United States, China, and the United Kingdom lead in research output and global collaborations. However, the study identifies a disciplinary imbalance, with ethical, regulatory, and societal dimensions significantly underrepresented. By combining quantitative bibliometric methods with qualitative thematic insights, this review provides a holistic overview of the evolution of AI-powered autonomous mobility and proposes conceptual and methodological directions for future research. The study offers valuable guidance for academics, policymakers, and industry stakeholders seeking to navigate the rapidly transforming landscape of autonomous vehicle technologies.

Keywords

• Autonomous Vehicles
• Artificial Intelligence
• Bibliometric Analysis
• Thematic Analysis
• Intelligent Transportation Systems
• VOSviewer

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