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Systematic literature review on autonomous ground vehicles for airport operations: Challenges, risks, and technological innovations

Mechanical Engineering for Society and Industry · Vol. 5 No. 2 (2025) · hlm. 521–541

DOI
10.31603/mesi.14635
ISSN
2798-5245
Terbit
2025-12-28
Penerbit
Universitas Muhammadiyah Magelang
Bahasa
en

Abstrak

This systematic literature review explores the integration of Autonomous Ground Vehicles (AGVs) into airport operations, focusing on key challenges, associated risks, and enabling technological innovations. The adoption of AGVs promises significant improvements in efficiency, safety, and sustainability across tasks such as baggage handling, aircraft towing, and runway maintenance. However, deploying AGVs in the dynamic, complex environments of airports presents significant obstacles, including challenges related to perception accuracy, sensor limitations, real-time decision-making, and cyber security risks. We applied the PRISMA methodology to screen 206 peer-reviewed articles from major databases, including Scopus, Web of Science, and PubMed. After screening, 14 studies were selected based on the inclusion criteria. The findings highlight the importance of advanced perception systems, multi-agent coordination, and Artificial Intelligence (AI)-based algorithms in enhancing AGVs performance. Furthermore, emerging innovations such as sensor fusion, transfer learning, and simulation-based development have proven effective in improving reliability and operational efficiency. This review contributes to current understanding of AGVs applications in airports and provides practical insights and recommendations for future research and development.

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  • Akademi Komunitas Perkebunan Yogyakarta
  • Badan Pengkajian dan Penerapan Teknologi
  • Afiliasi tidak diketahui
  • Organisasi berbeda
  • Organisasi sama
  • Afiliasi tidak diketahui
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Rekan penulisOrganisasiArtikel bersama
Dwitya Harits WaskitoAfiliasi tidak diketahui8
Mutharuddin MutharuddinAfiliasi tidak diketahui4
Novi IrawatiAfiliasi tidak diketahui4
Sunarto KalegAfiliasi tidak diketahui4
Angjuang PratamaAfiliasi tidak diketahui4
Defi Rizki MaulaniAfiliasi tidak diketahui4
Ayumi Putri VaraditaAfiliasi tidak diketahui4
Heri SetyawanAkademi Komunitas Perkebunan Yogyakarta2
Nurul Aldha Mauliddina SiregarAfiliasi tidak diketahui2
Irfan AnsoriAfiliasi tidak diketahui2
Tetty Sulastri MardianaAfiliasi tidak diketahui2
Djoko Wahyu KarmiadjiBadan Pengkajian dan Penerapan Teknologi2
M. RosyidiAfiliasi tidak diketahui2
Hastiya Annisa FitriAfiliasi tidak diketahui2
Tetty Sulastry MardianaAfiliasi tidak diketahui2
Koko SetiawanAkademi Komunitas Perkebunan Yogyakarta1
Herry ListiantoAkademi Komunitas Perkebunan Yogyakarta1
Olivia ElfatmaAkademi Komunitas Perkebunan Yogyakarta1
Subakho Aryo SalokoAkademi Komunitas Perkebunan Yogyakarta1
Edy PurwantoAfiliasi tidak diketahui1
Maman RachmanAfiliasi tidak diketahui1
Bagas Maulana Pasha Aditya PradaAfiliasi tidak diketahui1
Marcellus S KolopakingAfiliasi tidak diketahui1
Novita KusumadewiAfiliasi tidak diketahui1
Hanik MahliatusikkahAfiliasi tidak diketahui1
Achmad ToheAfiliasi tidak diketahui1
Franto NovicoAfiliasi tidak diketahui1
Andi EgonAfiliasi tidak diketahui1
Davide MerliAfiliasi tidak diketahui1

Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.

Sumber metadata: OAI-PMH (metadata jurnal) https://journal.unimma.ac.id/index.php/mesi/oai, pertama di-harvest 9 Nov 2026, terakhir terlihat 9 Nov 2026.
Metadata asli (oai_dc) 
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en">Systematic literature review on autonomous ground vehicles for airport operations: Challenges, risks, and technological innovations</dc:title>
	<dc:creator xml:lang="en">Gusti, Ayudhia Pangestu</dc:creator>
	<dc:creator xml:lang="en">Bowo, Ludfi Pratiwi</dc:creator>
	<dc:creator xml:lang="en">Kurnia, Siti Hidayanti Mutia</dc:creator>
	<dc:creator xml:lang="en">Ramadhan, Prastya Rizky</dc:creator>
	<dc:creator xml:lang="en">Sulastri, Tetty</dc:creator>
	<dc:creator xml:lang="en">Handoyo, Tris</dc:creator>
	<dc:creator xml:lang="en">Nugroho, Sinung</dc:creator>
	<dc:creator xml:lang="en">Kurniawan, Indra</dc:creator>
	<dc:creator xml:lang="en">Subaryata, Subaryata</dc:creator>
	<dc:creator xml:lang="en">Wiguna, I Kadek Candra Parmana</dc:creator>
	<dc:subject xml:lang="en">Autonomous ground vehicles (AGVs)</dc:subject>
	<dc:subject xml:lang="en">Airport operations</dc:subject>
	<dc:subject xml:lang="en">Risk assessment</dc:subject>
	<dc:subject xml:lang="en">Baggage handling</dc:subject>
	<dc:subject xml:lang="en">Technological innovation</dc:subject>
	<dc:description xml:lang="en">This systematic literature review explores the integration of Autonomous Ground Vehicles (AGVs) into airport operations, focusing on key challenges, associated risks, and enabling technological innovations. The adoption of AGVs promises significant improvements in efficiency, safety, and sustainability across tasks such as baggage handling, aircraft towing, and runway maintenance. However, deploying AGVs in the dynamic, complex environments of airports presents significant obstacles, including challenges related to perception accuracy, sensor limitations, real-time decision-making, and cyber security risks. We applied the PRISMA methodology to screen 206 peer-reviewed articles from major databases, including Scopus, Web of Science, and PubMed. After screening, 14 studies were selected based on the inclusion criteria. The findings highlight the importance of advanced perception systems, multi-agent coordination, and Artificial Intelligence (AI)-based algorithms in enhancing AGVs performance. Furthermore, emerging innovations such as sensor fusion, transfer learning, and simulation-based development have proven effective in improving reliability and operational efficiency. This review contributes to current understanding of AGVs applications in airports and provides practical insights and recommendations for future research and development.</dc:description>
	<dc:publisher xml:lang="en">Universitas Muhammadiyah Magelang</dc:publisher>
	<dc:date>2025-12-28</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unimma.ac.id/mesi/article/view/14635</dc:identifier>
	<dc:identifier>10.31603/mesi.14635</dc:identifier>
	<dc:source xml:lang="en">Mechanical Engineering for Society and Industry; Vol. 5 No. 2 (2025); 521-541</dc:source>
	<dc:source>2798-5245</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unimma.ac.id/mesi/article/view/14635/6438</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2025 Ayudhia Pangestu Gusti, Ludfi Pratiwi Bowo, Siti Hidayanti Mutia Kurnia, Prastya Rizky Ramadhan, Tetty Sulastri, Tris Handoyo, Sinung Nugroho, Indra Kurniawan, Subaryata Subaryata, I Kadek Candra Parmana Wiguna</dc:rights>
</oai_dc:dc>