Description

Traffic congestion has become a global concern due to the continual increase in the number of vehicles on the roads. In addition, a large expense, time waste and lost fuel are incurred by drivers, along with negative effects on the environment due to increased car emissions and greater demand for infrastructure improvements. Similar to other countries, Sri Lanka also employs a general traffic light controlling system to regulate congestion. However, it is not successful since the existing systems are designed often based on fixed time sequences or reliant on programmable logic controllers (PLCs) which struggle to adapt to dynamic traffic conditions. To overcome this problem, we introduced an intelligent system capable of making decisions in real-time regarding existing traffic congestion with less human inference. Our project stands out from other similar traffic control systems primarily due to its interconnected microcontrollers at each junction, facilitating seamless communication and data analysis between them. This interconnectedness enables efficient traffic management and decision-making, ensuring smoother traffic flow throughout the network. In addition, the transparency of the project will be increased with the help of the web application. The accuracy will be increased due to the utilization of the best algorithm that suits every scenario. Also, through this system, the average waiting time of an individual will be reduced compared to the present waiting time. Thus, the efficiency of the new product is increased. For the development, we employed a blend of cutting-edge technologies. Firstly, we leveraged computer vision technology, utilizing cameras strategically placed at intersections. These cameras captured video footage, which was then processed using object detection algorithms, particularly the (YOLO) approach known for its speed and accuracy in recognizing objects within images. The implementation cycle was initiated by developing suitable object detection algorithms that were necessary to be fed into the single-board computer, which was used to identify the application regarding image processing and computer vision. Afterwards, a separate PCB was designed with PIC microcontrollers, relays, resistors, oscillators, and other components to aid the functionality of the system. The completely designed PCB was installed at the traffic control post; this circuit worked as a detached system to compute the time sequences of the different arteries and to implement our new idea and algorithm. To stimulate the system and perform video processing techniques, the Python programming language was used alongside the OpenCV libraries. To brand the initiative, the name "Go Traffic" was devised, which had two meanings: one signifying the project’s dynamic and unique nature, and the other representing the project’s future vision. Methsoft Inc. was publicly outlined as the holder of the project within the law and in its dealings with authorities, society, and bureaucracy. When a technical project like this concludes, the undergraduates at the university gain significant exposure to industrial electronics. This exposure greatly enhances the reputation of our IES Student Branch Chapter. Additionally, it positively impacts how students and faculty perceive our chapter. The successful implementation and outcome of the "Go Traffic" project not only showcases the technical prowess and innovative spirit of our students but also strengthens the chapter's status as a center of excellence and progressive solutions within the university and the wider community.