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    Home / News / Auto News / AI-backed driving test tracks to boost safety in Maharashtra
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    AI-backed driving test tracks to boost safety in Maharashtra
    Maharashtra's AI test tracks will consist of various patterns for different vehicles

    AI-backed driving test tracks to boost safety in Maharashtra

    By Pradnesh Naik
    Aug 31, 2023
    05:09 pm

    What's the story

    Maharashtra's Motor Vehicle Transport Department is set to enhance road safety by introducing AI-driven driving tests. It is done to minimize human involvement in the evaluation process.

    The initiative will feature 17 new automated driving test tracks equipped with AI software.

    These tracks will cater to various vehicle types and address seven of the 24 evaluation points required for issuing licenses.

    Locations

    Mumbai will lead the way with two dedicated test tracks

    Mumbai will lead the way with two dedicated test tracks for two-wheelers and one for Light Motor Vehicles (LMVs).

    The other 16 locations include Badnera (Amravati), Buldhana, Nagpur City, Nagpur Rural, Nagpur East, Nanded, Ahmednagar, Alandi-Pune, Aurangabad, Hadapsar-Pune, Jalgaon, Saswad-Pune, Kolhapur, Nandivali, Panvel, and Pen.

    The primary objective of this project is to reduce human intervention in the assessment process.

    Details

    Test tracks will cater to various types of vehicles

    The automated test tracks will accommodate two-wheelers, light motor vehicles, as well as medium/heavy commercial vehicles.

    The tracks will consist of figure-eight patterns, H-tracks, zig-zag turns, gradient trials, simulated traffic scenarios, zebra crossing tests, and serpentine tracks for two-wheelers.

    Video cameras will be strategically placed across the test tracks to capture critical moments during the evaluation process.

    Information

    AI will simulate real-world scenarios

    AI integration will include facial recognition and real-time applicant identification. The system will instantly generate driving test results for different track configurations using deep learning and machine learning techniques. This will simulate real-world scenarios such as sudden pedestrian appearances or navigating slow-moving traffic.

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