Analysis of Urban Rail Transit Station Planning Combining Simulated Annealing Algorithm

Abstract

As a crucial node in the network system of urban transportation infrastructure, the consistent planning of the urban rail transit stations scientifically and reasonably is of highly significant importance to have a thorough understanding of the functional area division of a city and assess the improvement of facilities correlated with the rail transit infrastructure. In this study, the simulated annealing algorithm (SAA) is applied to the data analysis of the rail transit stations in a city. The method for the analysis of the urban rail transit stations combined with the SAA can achieve the dimensionality reduction in high-dimensional data information and the assessment of the similarity in traffic rail transits effectively. Finally, through in-depth analysis of the daily passenger flow features and the spatial location distribution of each type of station, a valuable reference can be obtained for the planning and design of urban rail transit stations.