Traditional parking systems are limited by the limited field of view and perception range of sensors, and cannot adapt to constantly changing parking lot and road conditions, as well as excessive manual programming requirements. The purpose of this study was to improve the vehicle's environmental perception and intelligent decision-making capabilities through advanced sensor and computer vision technology, combined with deep learning and machine learning algorithms, enabling the vehicle to independently select parking spaces, adapt to different parking lots and road conditions, simplify the user interface, and enable drivers to easily activate and monitor automatic parking functions. This article established an artificial intelligence based autonomous parking system for new energy vehicles, which can control the error between the center point of the vehicle and the center point of the parking space within a range of 0.43 m. The median system response time under normal conditions was 2.07 s, comprehensively improving the performance and user experience of the automatic parking system. The design concept and foundation of this system also provide a good reference and reference for subsequent researchers.


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    Title :

    Design of Automatic Driving and Parking System for New Energy Vehicles Based on Artificial Intelligence


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Hung, Jason C. (editor) / Yen, Neil (editor) / Chang, Jia-Wei (editor) / Ma, Bin (author)

    Conference:

    International Conference on Frontier Computing ; 2024 ; Singapore July 10, 2024 - July 14, 2024



    Publication date :

    2025-02-21


    Size :

    9 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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