Chun-Chieh Wang
Department of Automation Engineering and Institute of Mechatronoptic Systems, Chienkuo Technology University, Taiwan
pp. 263–267
ABSTRACT
In this paper, a fuzzy theory based identification system has been developed to improve the self-driving image recognition technology. The Raspberry Pi microprocessor is used as the main controller of the car. The author writes a Python program to deal with the image recognition problem. The image processing techniques include grayscale, binarization, morphology, image cutting and so on. There are four main functional tests in the scenario setting. It includes road identification, conversion of lane turning arc into front wheel turning angle, intersection identification, and traffic light identification. The purpose is to verify the functionality of fuzzy-based identified self-driving cars. The experimental results show that the developed recognition system based on fuzzy theory can successfully improve the recognition effect and reduce the probability of self-driving walking errors.

ARTICLE INFO
Article History
Received 10 November, 2021
Accepted 01 August 2022

Keywords
Fuzzy theory based identification system (FTBIS)
Raspberry Pi
Python
Tiny self-driving cars (TSDC)


JRNAL9309

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