The Automated Driving License Test System (ADLTS) is a cutting-edge project that aims to automate and enhance the process of evaluating candidates for driving licenses. It uses a combination of sensors and algorithms to objectively assess an applicant's driving skills and provide instant results on their performance. The ADLTS is a forward-looking approach to modernizing driving license testing in an era of evolving automotive technology.The applicants are fingerprinted with fingerprint sensor to ensure that no one else can impersonate them. This application and authentication process is handled by software application. The testing procedure is monitored by three sensors: a proximity sensor, an RPM sensor, and a human face identification system powered by OpenCV, a Machine Learning Library. Proximity sensor is used to monitor the distance between the vehicle and the external objects, while the RPM sensor is used to determine if the vehicle is turned on thereby monitoring the status of the engine. The Face Detection sensor monitors the presence of candidates in the vehicle. Violations of these testing procedures result in license rejection. The license is approved once the car is successfully parked without violating the cues.The sensors and the software system are integrated with a user-friendly UI to form a comprehensive model. This automated system improves safety, consistency, and cost efficiency in the licensing process, reducing the reliance on human evaluators and the risk of accidents during testing.


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    Titel :

    Automated Driving License Testing System


    Beteiligte:
    Rachel, Sheeba (Autor:in) / B, Sanjay Krishna (Autor:in) / A, Saranya (Autor:in) / R, Yashika (Autor:in)


    Erscheinungsdatum :

    08.10.2024


    Format / Umfang :

    417454 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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