Abstract
The article describes the models and software implementation at different architectural levels of the control system for a self-driving car for cross-country travel. A car powered by an internal combustion engine was chosen as a platform. At the level of electronic components, solutions are described that allow control typical components of a car: gear shifting, clutch, brake, steering and gas. The software implementation of the control system describes the computer vision component for recognizing near and far obstacles in order to maneuver along the road in rough terrain, taking into account the geometry of the car. A mapping service is also described, which allows to set the initial, final coordinates and intermediate points of the route. Schemes and models for re-equipping a typical car for unmanned control, as well as an unmanned driving algorithm for driving in rough terrain, claim novelty.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Gavanas, N.: Autonomous road vehicles: challenges for urban planning in European cities. Urban Sci. 3, 61 (2019). https://doi.org/10.3390/urbansci3020061
Autonomous Vehicle Market Size, Share, Trends, Report 2022–2030. Available online: URL https://www.precedenceresearch.com/autonomous-vehicle-market. Last accessed 08 June 2022
Using a powerful integrated digital solution to develop autonomous vehicles. Available online: URL https://www.plm.automation.siemens.com/global/ru/resource/autonomous-vehicle-development-software/93559. Last accessed 27 June 2022
Bojarski, M., Testa, D.D., Dworakowski, D.: End to end learning for self-driving cars. arXiv: Computer Vision and Pattern Recognition (2016). Available online: https://arxiv.org/pdf/1604.07316.pdf. Last accessed 18 June 2022
Liu, L., Lu, S., Zhong, R., Wu, B., Yao, Y., Zhang, Q., Shi, W.: Computing Systems for Autonomous Driving: State-of-the-Art and Challenges. Available online: URL https://arxiv.org/pdf/2009.14349.pdf. Last accessed 19 June 2022
Eskandarian, A.: Handbook of Intelligent Vehicles, vol. 2. Springer, Berlin (2012)
Haavaldsen, H., Aasboe, M., Lindseth, F.: Autonomous Vehicle Control: End-to-end Learning in Simulated Urban Environments. Available online: URL https://arxiv.org/abs/1905.06712. Last accessed 20 June 2022
Montanaro, U., Dixit, S., Fallah, S., Dianati, M., Stevens, A., Oxtoby, D., Mouzakitis, A.: Towards connected autonomous driving: review of use-cases. Veh. Syst. Dyn. 1–36 (2018)
Omeiza, D., Webb, H., Jirotka, M., Kunze, L.: Explanations in Autonomous Driving: A Survey. Available online: URL https://arxiv.org/pdf/2103.05154.pdf. Last accessed 01 June 2022
Apollo Auto Homepage. https://developer.apollo.auto/. Last accessed 20 June 2022
Autoware Auto Homepage. https://www.autoware.org/. Last accessed 22 June 2022
Nvidia Drive Homepage. https://www.nvidia.com/ru-ru/self-driving-cars/. Last accessed 22 June 2022
Comma.ai Homepage. https://comma.ai/. Last accessed 22 June 2022
Baidu Apollo Open Source Autonomous Driving Platform. https://www.neousys-tech.com/en/discover/fanless-in-vehicle-pc/baidu-apollo-open-source-autonomous-driving-platform. Last accessed 22 June 2022
LaValle, S.M.: Rapidly-Exploring Random Trees: A New Tool for Path Planning (1998). Available online: http://lavalle.pl/papers/Lav98c.pdf. Last accessed 22. June 2022
OpenStreetMap Homepage. http://openstreetmap.ru. Last accessed 19 June 2022
Openstreetmap Tile Server sources. https://github.com/Overv/openstreetmap-tile-server. Last accessed 23 June 2022
Acknowledgements
The work was supported by the FASIE under the agreement 8GUKodIIS12-D7/72685 27.12.2021 dated December 27, 2021 (Program CodeAI).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Svyatov, K., Dementev, V., Rubcov, I., Jhitkov, R., Mikhailov, V., Kanin, D. (2023). Off-Road Autonomous Vehicle Control System. In: Dolinina, O., et al. Artificial Intelligence in Models, Methods and Applications. AIES 2022. Studies in Systems, Decision and Control, vol 457. Springer, Cham. https://doi.org/10.1007/978-3-031-22938-1_47
Download citation
DOI: https://doi.org/10.1007/978-3-031-22938-1_47
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-22937-4
Online ISBN: 978-3-031-22938-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)