The role of artificial intelligence and machine learning in the optimization of transport corridors

The object of research: Artificial intelligence methods in the optimization of transportation tunnels – artificial neural networks and genetic algorithms Investigated problem: In this research, we will explore the role of machine learning in optimizing transportation tunnels and the basis of this process. Utilizing machine learning technologies in traffic control and management can reduce congestion and complexity on roads. The main scientific results: The rapid advancement and application of Artificial Intelligence (AI) and Machine Learning (ML) have led to significant developments across various industries and business sectors. Additionally, utilizing AI-based pioneering technologies is one of the most crucial demands of the modern era for enhancing efficiency in the transportation sector. It is essential to identify methods of utilizing these technologies to create rapid improvements in eliminating traffic congestion and ensuring more reliable travel times for users. The area of practical use of the research results: Machine learning algorithms are used in automotive sensors to identify potential hazards and automatically verify control. Technologies used to optimize transportation corridors and reduce traffic congestion provide optimal solutions by examining different transportation scenarios. Furthermore, the development of autonomous driving technologies in transportation makes the application of ML even more crucial. Innovative technological product: To eliminate optimization problems, there is a need for raster algorithms that simplify computational analytics. For example, we can mention Genetic Algorithm (GA), based on the concept of biological evolution, which was developed by Con Holland in 1988. Scope of the innovative technological product: The use of intelligent technologies in the transportation sector has introduced innovative technological tools that enhance safety and sustainability. Smart management systems and autonomous vehicles have covered a wide range of application areas. Machine learning algorithms are widely used to minimize optimal travel time and fuel consumption. Autonomous transportation vehicles are utilized to navigate complex roads and efficiently manage time, integrating computer vision and sensor fusion techniques.