Optimizing Traffic Flow: Utilizing IR and Load Cell Sensors for Cost-Effective Traffic Congestion Alleviation at Smart City Intersections

Cities face a significant challenge of increasing traffic congestion due to the rising number of vehicles. Developed countries have introduced smart traffic management systems as a solution to mitigate congestion and improve traffic flow. These systems employ various techniques such as image processing, radar sensing, ultrasonic and microwave detectors, and other sensors. However, each of these methods has its drawbacks, including susceptibility to weather conditions, high costs, and lower accuracy. Intelligent traffic control methods like inductive loop detection, wireless sensor networks, and video data analysis have proven to be efficient. However, they suffer from lengthy installation processes and high installation and maintenance expenses. In response to this issue, this article proposes a system that can detect lane density and adjust traffic signal timers accordingly to optimize traffic flow. The proposed system utilizes IR sensors and load sensors to calculate the density of each lane at an intersection, and an RFID system is implemented to accommodate emergency response vehicles. The system is centered around an ATmega 2560 chip. To demonstrate the effectiveness of the proposed approach, real-time experiments are conducted on a scaled-down model of the system. The results showed promising outcomes. The authors argue that this system could serve as a cost-effective and efficient solution for managing traffic in cities, particularly in Pakistan.