Study on Identification Method for Urban Road Traffic Conditions with Inductive Loop Data

A real-time identification method for identifying urban road traffic conditions is presented based on fuzzy clustering algorithm according to SCOOT inductive loop data, and a method of determining the identified time interval and a method to verify the identification algorithm are proposed. Finally, a simulated experiment is performed to validate the presented methods by combining an external program with VISSIM software. A comparative analysis shows that the algorithm can improve the identified effects of the urban road traffic conditions in real-time and the proposed evaluation method can evaluate the performance of an identification algorithm for urban road traffic conditions.