INTELLIGENT TRANSPORTATION SYSTEMS: AN OVERVIEW OF SOLUTIONS FOR TRAFFIC OPTIMIZATION

The study analyzes modern intelligent transportation systems aimed at optimizing urban traffic. It examines adaptive traffic light control solutions, as well as systems for prioritizing public and emergency transport and automatic incident detection technologies. The findings reveal that the application of V2X, IoT, and artificial intelligence technologies enables achieving a traffic light phase prediction accuracy of up to 98% with an error margin of no more than 2 seconds, and ensures data transmission with a delay of less than 1 second. Public transport priority systems contribute to improving punctuality by 10–15% and reducing delays by 20–35%, while adaptive technologies, notably SCATS, increase road capacity by 5–10%. Automatic incident detection systems demonstrate a reaction time of 2 to 3 seconds, facilitating prompt responses to emergencies. The results underscore the effectiveness of modern traffic management systems in enhancing safety, optimizing traffic flow, and reducing harmful emissions.