Algorithm Analysis and Implementation of the Real-time Traffic State Identification of Signalized Intersections Based on Floating Car Data

The knowledge of the actual current state of the road traffic for the entire road network is a important component of Intelligent Transportation System applications. Identification of traffic state on signalized intersections is the focus of research on urban road network traffic state identification. In this paper, the use of real-time Floating Car Data (FCD), based on traces of global positioning system (GPS) positions, is emerging as a reliable and cost-effective way to gather accurate traffic flow information in a road network. Based on the analysis of traffic flow’s moving process on the approach of signalized intersections, the paper puts forward a classification method of traffic state on signalized intersections while the relationship between queue length and the capacity of the approach is under consideration, and the algorithm to identify the real-time traffic state on signalized intersections based on FCD is established at last. To test the effectiveness of this algorithm, a field experiment using FCD was conducted at an intersection in Nanjing. The test results indicate that the proposed method provides very satisfactory accuracy in application.