A Scalable Web-Based Carpooling System for Driver–Passenger Matching Using Dynamic Ride Sharing Architecture

Abstract

The rapid increase in urban population and vehicle ownership has led to severe traffic congestion, environmental pollution, and inefficient utilization of transportation resources. Traditional commuting methods often result in underutilized vehicle capacity, where most cars operate with a single occupant. Carpooling has emerged as an effective solution to address these challenges by enabling multiple users to share rides, thereby reducing traffic density and fuel consumption.This research presents a scalable web-based carpooling application designed to facilitate efficient ride sharing between drivers and passengers. The proposed system leverages modern web technologies and databasedriven architecture to provide a seamless platform for trip creation, search, booking, and management. The application is developed using the Django framework, which ensures robust backend functionality and secure user authentication.The system introduces two primary user roles: car owners (drivers) and passengers. Drivers can create trips by specifying source and destination locations, available seats, pricing, and departure time. Passengers can search for available trips based on their travel requirements and book seats accordingly. The system dynamically updates seat availability and maintains booking records to ensure data consistency.A key feature of the proposed system is realtime trip tracking, which enhances user experience and safety. The system also includes a reporting mechanism that allows users to report issues related to trips or drivers, thereby promoting accountability and trust within the platform. Additionally, an administrative dashboard provides oversight of user activities, trip statistics, and reported issues.The application incorporates relational database models to manage entities such as users, profiles, locations, trips, bookings, and reports. Efficient querying techniques are used to optimize search functionality and ensure fast response times. The system also implements role-based access control to restrict functionalities based on user type.Experimental evaluation demonstrates that the proposed system effectively reduces ride redundancy and improves transportation efficiency. The platform is scalable and can be extended to support advanced features such as route optimization, dynamic pricing, and integration with GPS services.In conclusion, the proposed carpooling application provides a practical and efficient solution for modern urban transportation challenges. It promotes sustainable mobility, reduces environmental impact, and enhances user convenience through intelligent ride-sharing mechanisms.