The Solution to the Problem of Traffic Accidents

A noticeable increase in traffic accidents has been observed in recent years, as the Kingdom of Saudi Arabia recorded the highest death rate from traffic accidents among the G20 countries, reaching 9,031 deaths, at a rate of 28.8 per 100,000 people for the year 2019. According to the World Health Organization, about 1.25 million people die annually as a result of traffic accidents.

The sustainable development plans attach great importance to safety on public roads and strive to reduce the number of accidents and deaths resulting from them. By studying the reasons, we find that traffic violations in 1439 increased by 222% compared to the previous year 1438, according to a recent statistic issued by the General Traffic Department, and these violations often lead to a traffic crisis represented in traffic congestion and an increase in traffic accidents.

Consequently, the transportation infrastructure is damaged, which will negatively affect the national economy. Therefore, there is a great need to effectively and systematically monitor and track traffic.

Although laws and fines have been put in place for traffic violations and surveillance cameras in the streets to track vehicles, monitor violating cars and accident places, and analyze traffic to estimate peak locations in some streets, these traditional methods are not effective in all cases. The surveillance cameras face difficulties that lead to the lack of clarity of the captured images. Thus the inability to obtain the data of this vehicle and sometimes not distinguish it due to various reasons such as weather conditions [5], the different sizes, and types of vehicles, especially in traffic congestion cases. This hinders the detection of some vehicles, and the similarity of the shapes of some vehicles is difficult to determine their type in the blurred images due to the inability to distinguish the vehicle logo or the license plate as well, and thus it will be difficult to identify the vehicles.

With the emergence of the concept of artificial intelligence, which brought about a great technical revolution in all fields, it was quickly used in various sectors to serve humanity medically, economically, agricultural, industrialized and other sectors. Among the areas of its use in the field of machine learning that can be used in smart traffic monitor systems and it is expected to obtain useful results and get high-quality information.

Therefore, in this research, artificial intelligence techniques will be used to specifically address the problems that traffic systems face. The first problem is the inability to recognize the type of vehicles in the image.

Depending on deep learning that follows the concept of machine learning, it works to create algorithms that allow devices to learn, deduce, and address the problems they encounter. His role in this research is to train the convolutional neural network using Dataset to identify different types of compounds according to their external specifications (size, length, width, etc.). And Classifying them according to their type (truck, car, motorcycle, etc.).

As for the second problem of unclear images captured from surveillance cameras, the image will also be processed using several procedures (edge detection, etc.) To obtain a clear image, as image processing is one of the most important areas of computer science.

After obtaining clear images, it will be possible to detect all vehicles in the image and determine their type. The major challenge to transportation management is the need to obtain high-quality information, in order to take effective administrative measures and decisions and to develop strategies for managing and organizing traffic.

To conclude, this proposed system has a great role in tracking vehicles, monitoring traffic, detecting violations, and reducing traffic accidents, and thus it will have a positive impact on economic and social development plans not only in the Kingdom of Saudi Arabia but can be used in all countries of the world that rely on surveillance cameras and aim to use a traffic monitoring system Intelligent.