Research on Traffic State Discrimination of Intersections Based on Fuzzy Clustering Analysis

Intersections are bottlenecks in road traffic, and their traffic conditions directly impact travel efficiency and comfort. By utilizing a large amount of traffic data to assess the current vehicle operating status at intersections, not only can drivers be prompted to choose smoother routes, but it also benefits traffic management departments in real-time monitoring of traffic conditions. This paper defines the levels of traffic state classification and the indicators used to determine the operational status of intersections. It employs the Fuzzy C-Means algorithm to construct a model for discriminating the traffic operational status at intersections, classifies the traffic states at intersections, and analyzes the results based on the classification.