Szczegóły publikacji

Opis bibliograficzny

Autorzy (2)

• AGHOskroba Jarosław
• AGHMendrok Krzysztof

Słowa kluczowe

Dane bibliometryczne

ID BaDAP	139276
Data dodania do BaDAP	2022-02-24
DOI	10.1007/978-3-030-93377-7_1
Rok publikacji	2022
Typ publikacji	fragment monografii pokonferencyjnej
Otwarty dostęp
Wydawca	Springer
Czasopismo/seria	Lecture Notes in Networks and Systems

Abstract

In recent years, there has been intense progress in the autonomous car field. In large part of the publication, the problem of controlling the movement of an autonomous vehicle is solved based on machine learning algorithms that require training data, significant computing power, and memory resources. The work aimed to find an alternative methodology that would allow adaptive car control in various road scenarios. The following tasks were analyzed: driving in a column of cars with a safe distance, overtaking maneuver and returning to the correct lane, keeping the vehicle in the middle of the lane while moving along a winding track with automatic speed adjustment. During the simulation, data from sensors (cameras, LIDAR) were used by adaptive controllers. A state machine was used to switch between controllers. The visualization of the system's operation was realized thanks to the newly introduced possibility of integrating the graphics engine “Unreal Engine” and “Matlab 2021a”. Based on the algorithm's operation, it was found that adaptive controllers can effectively cope with the control of autonomous vehicles in various situations.

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