Review and analysis of tools for designing autonomous ground vehicle control systems
For the successful development of self-driving vehicles, as well as advanced driver-assistance systems, specialized programs are required. The purpose of this article is to provide an overview of the main tools for programming and virtual testing of autonomous driving systems for agricultural and road vehicles. Such tools as Autoware Foundation, Baidu Apollo, Siemens Simcenter Prescan, CARLA, MathWorks, Epic Games Unreal Engine, DSpace AURELION, Unity, Foretellix Foretify platform, IPG CarMaker, Cognata, Vector DYNA4, Nvidia Drive Sim, Vires Virtual Test Drive, VehicleSim, LG SVL Simulator are considered. The features and capabilities of each program are described, and a comparison is made according to the following parameters: distribution scheme – contractual or free, full and partial cycle programs, programming and visualization. The available operating systems for each program are listed. Among domestic companies, Sberbank (SberAutoTech) and Yandex (Yandex Self-Driving Group) stand out, which do not offer software as a product.
Authors
- Sergey Sergeevich Shadrin (ORCID: https://orcid.org/0000-0002-2606-9984)
- Andrei M. Nazarov (ORCID: https://orcid.org/0009-0004-1341-3098)
Institutions
- Moscow Polytechnic University (RU)
Publication Details
- Journal
- Tractors and Agricultural Machinery
- Published
- 2026-11-07
- DOI
- https://doi.org/10.17816/0321-4443-679785
- Primary Topic
- Autonomous Vehicle Technology and Safety
- Type
- article
- Field-Weighted Citation Impact
- 0.00