Research on the Evaluation System of Urban Rail Transit Operation Safety in the Context of Intelligent Transportation

Abstract

With the rapid development of the Internet and intelligent control technology, intelligent transportation has become a research hotspot in building a smart city. Under the background of intelligent transportation, it is particularly important to effectively evaluate the rail transit as the framework of urban public transport in this study, and fuzzy mechanism is introduced to optimize the support vector machine (SVM), and on this basis, analytic hierarchy process (AHP) and SVM are combined to improve the classification accuracy and improve the rail transit operation safety evaluation index system. The experimental results show that the classification accuracy of the fuzzy SVM combined with AHP is above 85% on all the datasets, and it can effectively eliminate the less-relevant indicators. In the actual evaluation of Shanghai Rail Transit safety, the prediction accuracy exceeded 80% and the highest reached 94.51%. Among them, the accuracy of management level and infrastructure were increased by 24.1% and 18.34%, respectively, indicating that this method can effectively screen the evaluation indicators. In the evaluation of Beijing Rail Transit, the accuracy rate of the combined algorithm reaches 95.67%, with high classification accuracy, which provides a reference direction for the establishment of the rail transit operation safety evaluation system.