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@article{195591,
        author = {Pola Sai Likitha and Niddana Leela Sai Kumar and Patnana Thanu Sri and Palla Sai Sarvan and Surendra Kumar Choudhary},
        title = {SMART DRIVER RECOMMENDATION AND BOOKING SYSTEM USING ML AND DS},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {795-799},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=195591},
        abstract = {The ride-hailing industry faces a significant challenge in fairly and accurately pricing insurance for drivers, as traditional models rely on static premiums that do not account for real-time driving behavior. This paper presents a Smart Driver Recommendation and Booking System using Machine Learning (ML) and Data Structures (DS) that assesses driver risk and recommends suitable drivers dynamically. The proposed system classifies drivers as Good, Average, or Poor based on trip-level behavioral metrics such as average speed, maximum speed, harsh braking events, rapid acceleration, and traffic violations. These classifications directly determine daily insurance premiums and driver recommendations, enabling personalized and fair service. The system is implemented as a Flask-based web application offering three distinct modules: a user (passenger) interface with AI-powered driver recommendations, a driver portal for registration and trip management, and an administrative dashboard for monitoring insurance policies, claims, and financial reports. A dataset of 40 drivers with over 600 synthetic trips was generated to simulate real-world conditions. Results demonstrate accurate behavioral classification, dynamic premium adjustments, and streamlined insurance claim processing. The system serves as a scalable, data-driven framework for modernizing driver recommendation and insurance in the gig economy.},
        keywords = {Behavior-Based Insurance, Booking System, Data Structures, Driver Recommendation, Dynamic Premium, Flask, Machine Learning, Ride- Hailing, Risk Classification, Usage-Based Insurance.},
        month = {April},
        }