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Embedded system vehicle based on multi-sensor fusion
IEEE Access ; : 1-1, 2023.
Artigo em Inglês | Scopus | ID: covidwho-20243873
ABSTRACT
As intelligent driving vehicles came out of concept into people’s life, the combination of safe driving and artificial intelligence becomes the new direction of future transportation development. Autonomous driving technology is developing based on control algorithms and model recognitions. In this paper, a cloud-based interconnected multi-sensor fusion autonomous vehicle system is proposed that uses deep learning (YOLOv4) and improved ORB algorithms to identify pedestrians, vehicles, and various traffic signs. A cloud-based interactive system is built to enable vehicle owners to master the situation of their vehicles at any time. In order to meet multiple application of automatic driving vehicles, the environment perception technology of multi-sensor fusion processing has broadened the uses of automatic driving vehicles by being equipped with automatic speech recognition (ASR), vehicle following mode and road patrol mode. These functions enable automatic driving to be used in applications such as agricultural irrigation, road firefighting and contactless delivery under new coronavirus outbreaks. Finally, using the embedded system equipment, an intelligent car was built for experimental verification, and the overall recognition accuracy of the system was over 96%. Author
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Texto completo: Disponível Coleções: Bases de dados de organismos internacionais Base de dados: Scopus Idioma: Inglês Revista: IEEE Access Ano de publicação: 2023 Tipo de documento: Artigo

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Texto completo: Disponível Coleções: Bases de dados de organismos internacionais Base de dados: Scopus Idioma: Inglês Revista: IEEE Access Ano de publicação: 2023 Tipo de documento: Artigo