This study aims to compare traffic sign (TS) and obstacle detection for autonomous vehicles using different methods. The review will be performed based on the various methods, and the analysis will be done based on the metrics and datasets.

    Design/methodology/approach

    In this study, different papers were analyzed about the issues of obstacle detection (OD) and sign detection. This survey reviewed the information from different journals, along with their advantages and disadvantages and challenges. The review lays the groundwork for future researchers to gain a deeper understanding of autonomous vehicles and is obliged to accurately identify various TS.

    Findings

    The review of different approaches based on deep learning (DL), machine learning (ML) and other hybrid models that are utilized in the modern era. Datasets in the review are described clearly, and cited references are detailed in the tabulation. For dataset and model analysis, the information search process utilized datasets, performance measures and achievements based on reviewed papers in this survey.

    Originality/value

    Various techniques, search procedures, used databases and achievement metrics are surveyed and characterized below for traffic signal detection and obstacle avoidance.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    A systematic study of traffic sign recognition and obstacle detection in autonomous vehicles


    Beteiligte:


    Erscheinungsdatum :

    25.11.2024


    Format / Umfang :

    19 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    DSCC2017-5187 Traffic Sign Recognition in Autonomous Vehicles Using Edge Detection

    Vishwanathan, Harish / Peters, Diane L. / Zhang, James Z. | British Library Conference Proceedings | 2017


    Traffic Sign Recognition using Deeplearning for Autonomous Driverless Vehicles

    Suriya Prakash, A / Vigneshwaran, D / Seenivasaga Ayyalu, R et al. | IEEE | 2021


    Traffic Sign Recognition Using Neural Networks Useful for Autonomous Vehicles

    Rezgui, Jihene / Hbaieb, Amal / Chaari, Lamia et al. | IEEE | 2019


    Sign Recognition for Autonomous Vehicles

    LIU DONGRAN / JAIN JINESH J | Europäisches Patentamt | 2018

    Freier Zugriff

    Traffic Sign and Obstacle Detection for Autonomous Vehicle Navigation using Edge Computing

    Vijayalakshmi, M. / Bharathwaj, M. / Dharshini, D. Anjelin Deva | IEEE | 2025