The main objective of this proposed project is to manage the movement of people and goods efficiently. This traffic management system is based on AI and deep learning, which works with a traffic signal controller, vehicle classifier, and fine system. In this project, the programmable peripheral interface's buffer and ports are used to connect the traffic lights to the microprocessor system. As a result, the traffic lights can be turned ON or OFF automatically. The Interface Board was created to operate with the parallel port of the microprocessor system. A vehicle classifier is a vision-based vehicle classifier that uses machine learning algorithms to recognize vehicles and trucks in video pictures. Drivers and owners of motor vehicles who disobey traffic laws are subject to a fine system. When a traffic challenge is issued, it suggests that the recipient is liable to pay a fine that varies in amount according to the specific type of traffic infringement that was observed.
Top1. Introduction
In emerging nations, the sale of vehicles is increasing, leading to a rise in traffic on the roads. In countries like India, traffic management has become a critical concern, especially in major cities such as Mumbai, Chennai, and Delhi. To address this issue, smart traffic solutions are being explored to efficiently manage traffic.
According to a WHO assessment, developing countries account for a small fraction of the world's vehicles but experience a disproportionately high number of traffic fatalities. Low- and middle-income nations bear around 85% of all traffic fatalities globally, with 90% of years of life lost to disabilities and 96% of all children killed in traffic injuries occurring in these countries. India alone accounted for 10% of all road fatalities worldwide in 2008 (Lanke & Kouln, 2013). The primary cause of accidents, injuries, and fatalities, according to the Government of India (GOI), is driver error, responsible for 77% of all road accidents, 79% of injuries, and 73% of fatalities based on 2006 statistics.
Despite these alarming figures and the underlying issues in traffic management, policymakers often overlook the problem. Finding solutions, especially in mixed traffic conditions typical of developing nations like India, remains a challenge. The main objective of the proposed project is to efficiently and safely manage the movement of people and goods using an AI and Deep Learning-based traffic management system (Ouallane et al., 2022). This system incorporates a Traffic Signal Controller, Vehicle Classifier, and Fine System.
The traffic lights in the system are connected to the microprocessor using the programmable peripheral interface's buffer and ports. This allows the traffic lights to automatically turn on or off in a specified order. The Interface Board was designed to work with the Parallel Port of the Microprocessor System (Olayode et al., 2020). The Vehicle Classifier in the project is a vision-based classifier that uses machine learning algorithms to recognize vehicles and trucks in video images. Additionally, a fine system is implemented to penalize drivers and vehicle owners who disobey traffic laws. When a traffic challan is issued, it indicates that the recipient is liable to pay a fine, the amount of which varies depending on the specific type of traffic violation observed.