Design and Implementation of an Automated Toll Collection System


Abstract

Manual toll collection systems exacerbate traffic congestion, economic inefficiency, and environmental pollution, particularly in rapidly urbanizing regions. Several technologies were introduced over the years to address problems associated with manual toll collection. Despite these developments, challenges remain in making the toll collection system more efficient. This study therefore presents the design, construction, and validation of a fully functional prototype of an Automated Toll Collection System (ATCS) to address traffic congestion and its associated issues. The system integrates an ESP32 microcontroller, an MFRC522 Radio Frequency Identification (RFID) reader for vehicle identification, and a load cell with an HX711 amplifier for Weight-In-Motion (WIM) measurement. A dynamic toll calculation algorithm implements a fair, weight-based pricing model which provides a practical solution for addressing the issues of vehicular traffic congestion associated with the traditional manual system of toll collection. Firebase, together with a custom Node.js webhook, has been integrated with the Paystack payment system Application Programming Interface (API) to process real-time mobile money toll payment/top-ups, and If This Then That (IFTTT) services are used for transaction logging and user notifications. Validation demonstrates the prototype’s robust functionality by successfully processing transactions with sufficient balances and intelligently handling insufficient funds by recording debt and automatically generating payment links. By enabling non-stop vehicular flow, cashless transactions, and equitable data-driven tolling, this scalable IoT-based solution is applicable in transportation infrastructure, enhancing traffic flow, revenue security, and sustainable urban mobility.

Keywords:

Automated Toll Collection, Cashless Payment, Internet of Things (IoT), Radio Frequency Identification, Smart Transportation, Weigh-In-Motion

References

    Issue

    2026 Vol.4 No.1

    Copyright & License

    Copyright (c) 2026 Moses Kwasi Torkudzor, Stephen Andoh Baffoe, Gabriel Senyah, Micheal Gyamfi Opoku, Yitzak Ofori, Patrick Atsu Agbemabiese

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