Design of a Microcontroller-Based Traffic Light Control System for Urban Intersections in Kano State

This project designs and simulates a microcontroller-based adaptive traffic light control system intended to reduce congestion and improve traffic flow at urban intersections in Kano State, North West Nigeria. Rapid urbanisation in Kano has outpaced traffic management infrastructure, resulting in chronic gridlock at major intersections during peak hours. The proposed system uses infrared sensors placed at each approach lane to estimate vehicle queue lengths in real time. An ATmega328P microcontroller processes the sensor inputs and applies a proportional time allocation algorithm that grants longer green phases to approaches with heavier queues. The control logic enforces minimum and maximum green time constraints to prevent starvation of low-traffic approaches. Phase sequencing complies with standard four-phase traffic signal plans, including amber clearance intervals. A Proteus simulation environment was used to validate the control algorithm across multiple traffic density scenarios before hardware prototyping. The prototype was assembled and bench-tested, demonstrating correct phase transitions and sensor-responsive timing adjustments. Comparison of the adaptive algorithm against a fixed-time baseline in simulation shows a 28 percent reduction in average vehicle delay under peak-hour traffic distributions representative of Kano intersections. The system supports remote monitoring through a serial communication interface. Future work is recommended to incorporate machine learning for demand prediction and to integrate emergency vehicle preemption capability. Keywords: traffic light control, adaptive signal, microcontroller, congestion, Kano State.