Functional Model of a Self-Driving Car Control System

被引:3
|
作者
Sviatov, Kirill [1 ]
Yarushkina, Nadejda [1 ]
Kanin, Daniil [1 ]
Rubtcov, Ivan [1 ]
Jitkov, Roman [1 ]
Mikhailov, Vladislav [1 ]
Kanin, Pavel [1 ]
机构
[1] Ulyanovsk State Tech Univ, Fac Informat Syst & Technol, Severny Venetc 32, Ulyanovsk 432027, Russia
关键词
self-driving car; visual scene recognition; deep learning; computer aided design;
D O I
10.3390/technologies9040100
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The article describes a structural and functional model of a self-driving car control system, which generates a wide class of mathematical problems. Currently, control systems for self-driving cars are considered at several levels of abstraction and implementation: Mechanics, electronics, perception, scene recognition, control, security, integration of all subsystems into a solid system. Modern research often considers particular problems to be solved for each of the levels separately. In this paper, a parameterized model of the integration of individual components into a complex control system for a self-driving car is considered. Such a model simplifies the design and development of self-driving control systems with configurable automation tools, taking into account the specifics of the solving problem. The parameterized model can be used for CAD design in the field of self-driving car development. A full cycle of development of a control system for a self-driving truck was implemented, which was rub in the "Robocross 2021" competition. The software solution was tested on more than 40 launches of a self-driving truck. Parameterization made it possible to speed up the development of the control system, expressed in man-hours, by 1.5 times compared to the experience of the authors of the article who participated in the same competition in 2018 and 2019. The proposed parameterization was used in the development of individual CAD elements described in this article. Additionally, the implementation of specific modules and functions is a field for experimental research.
引用
收藏
页数:11
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