Creating Sustainable Urban Transportation Systems Through Innovative Traffic Management Strategies

In recent years, research on urban microclimates has become increasingly important, drawing attention from both governments and scientists. Continuous monitoring and management of urban air quality are crucial for ensuring the health and well-being of city residents. In this study, an assessment of pollutant emissions at an intersection in Chelyabinsk city was conducted using the AIMS-Eco monitoring system. This system utilizes real-time video processing with the YOLOv4 neural network, which collects information on traffic movement and air quality. Based on data analysis, a mathematical model for dynamic regulation of the traffic flow speed in ensuring uninterrupted passage through a regulated intersection by group vehicles was developed. The evaluation of harmful emissions, specifically carbon dioxide, was performed. The model takes into account factors such as the number of vehicles in the queue, the length of the section, acceleration and speed of the traffic flow, and waiting times. The mathematical modeling demonstrated that by optimizing the speed regime of vehicles, it is possible to reduce emissions by up to 30%. Therefore, the establishment of sustainable urban transportation systems, aided by innovative traffic management strategies, plays a significant role in improving the lives of city residents and preserving the environment.