While traveling to an unknown place via road navigation is critical, in the same way, the condition of the road is imperative to reach the destination within a certain time. Even though if we know the route of the source to destination but we are not aware of the condition of that road hence we are not able to reach within the desired frame of time. It could be avoided if you are aware of the condition of roads. This project aims at developing an Intelligent Vehicle road surface classifier system that categorizes road based on the roughness of the road. The core idea is to make available realtime information about the quality of the surface of the route along with navigation. the roughness of the road is calculated using the working piston movement of the suspension. Based on measured dynamic data, conditions of road will be analyzed, and we can upload this information on the central database so, in the future, any applicable end user can use this information during a traveling to get a brief idea about road conditions. Shock absorbers are a vital part of automobile suspension. Shock absorbers work on the principle of fluid displacement on the movement of the working piston of suspension in both compression and expansion cycle. The roughness of the road surface is classified into a smooth surface, mediocre rough surface and dangerous bumpy surface based on the working piston of suspension movement. Also, it will suggest you fastest and safest route source to destination.


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    Titel :

    Intelligent Vehicle Road Surface Classifier System


    Beteiligte:


    Erscheinungsdatum :

    01.03.2020


    Format / Umfang :

    394940 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch