According to the research studies in recent years, it is predicted that level 5 autonomous vehicles will take the place of conventional vehicles. These driverless vehicles can make decisions according to the environmental data and accomplish the driving task accordingly. In order to accomplish this, autonomous vehicles use different types of sensors in order to detect and perceive their local environment. But sensors can still malfunction due to environmental conditions, manufacturing defects or noise; so the information obtained from one sensor would not be reliable for the tasks associated with driverless vehicles. A feasible solution for this issue is to collaborate multiple sensors and fuse their data to accomplish more accurate driving tasks in Autonomous Driving systems. The various methods used to improve the navigation system of driverless vehicles are being reviewed in this survey.


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    Titel :

    Sensor Data Fusion Methods for Driverless Vehicle System: A Review


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Ranganathan, G. (Herausgeber:in) / Bestak, Robert (Herausgeber:in) / Fernando, Xavier (Herausgeber:in) / Kurian, Nitheesh (Autor:in) / Vadivukkarasi, K. (Autor:in)


    Erscheinungsdatum :

    2022-09-02


    Format / Umfang :

    12 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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