The rationality of the location of bus stations is an important factor affecting the level of urban bus services. In order to more reasonably select the location of the bus station, the GPS data of the taxi is used to extract the coordinates of the passengers' latitude and longitude as the best point of travel, and the iterative self-organizing algorithm is introduced to plan the bus station. Taking xi 'an city as an example, the algorithm is realized by Matlab programming, and the clustering center is the potential location of bus station identified by the algorithm. In addition, k-means clustering algorithm is introduced for comparative analysis from macro and micro perspectives to verify the effectiveness of iterative self-organization algorithm, and it is concluded that the attraction potential between sites under iterative self-organization algorithm is greater than that between sites under k-means clustering algorithm, and it can better identify and avoid noise points.

CICTP