| Issue |
E3S Web Conf.
Volume 694, 2026
Third International Conference on Green Energy, Environmental Engineering and Sustainable Technologies 2025 (ICGEST 2025)
|
|
|---|---|---|
| Article Number | 04017 | |
| Number of page(s) | 8 | |
| Section | Infrastructure, Transports and Sustainability | |
| DOI | https://doi.org/10.1051/e3sconf/202669404017 | |
| Published online | 16 February 2026 | |
Application of operating systems for the combined development of ground vehicles and drones for cargo delivery based on artificial intelligence
1 Lviv Polytechnic National University, Department of Higher Mathematics, 12 Stepana Bandera Street, Lviv, Lviv region, Ukraine
2 State University “Kyiv Aviation Institute”, Air Transportation Management Department, 1 Liubomyra Huzara Ave., Kyiv, Ukraine
3 State University “Kyiv Aviation Institute”, Management of Foreign Economic Activity of Enterprises Department, 1 Liubomyra Huzara Ave., Kyiv, Ukraine
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
The relevance of this study is determined by the need to improve the efficiency of international cargo delivery and the intellectualization of service markets. The methodological basis of the study consists of methods of theoretical generalization, abstract-logical method, statistical analysis, as well as a group of expert assessment methods, namely the Delphi method and the method of predictive graph with the formation of a system of interrelationships. A mechanism has been created for managing the operational systems of the combined development of ground vehicles and drones for cargo delivery based on artificial intelligence, as well as a mechanism for the combined use of ground vehicles and drones in the organization of cargo delivery. The efficiency of the delivery of groups of special cargoes using combinations of ground vehicles and drones has been assessed, which made it possible to prove the effectiveness of the proposed tools and determine the optimal options based on scenario modelling.
Key words: artificial intelligence / transport / operating system / freight delivery / vehicles / drones / supply chains / sustainable
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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