The rapid construction of high-speed rail promotes the agglomeration effect, improves the accessibility of station area traffic, drives the spatial flow of different elements and the agglomeration of people, and forms the driving force for development. The gathering rules of people are related to the characteristics of the station area. The construction of the station area has an impact on crowd behavior, and the characteristics of crowd activities can provide a basis for the optimization and layout adjustment of the station area. Due to the limitation of data and other reasons, the existing research focuses on the spatial form of the station area, economic development, etc., and the research on the quantitative analysis of population agglomeration and the influence mechanism is insufficient. This paper uses big data and traditional data such as mobile phone signaling and POI of Amap to analyze the population distribution characteristics and influencing factors of 13 high-speed rail stations in four cities of Beijing, Shanghai, Chongqing and Chengdu. It carried out researches according to the logical main line of “population characteristics-influencing factors-influencing mechanisms-planning response”. By analyzing the characteristics of high-speed rail stations, it is found that the proportion of resident passenger flows at different stations are different. The non-resident passenger flow is significantly higher than the resident passenger flow. The resident passenger flow accounts for about 22% of the total passenger flow of high-speed rail travel. The non-high-speed rail passenger flow has significant characteristics in terms of the built environment and gathering direction. The population living or working in the station area has a relatively low dependence on the high-speed rail, and the dependence of the residents on the high-speed rail is greater than that of the workers. Among non-high-speed rail passenger flows, few significant differences of the proportion of residents and workers at most stations is found. The paper extracts and analyzes the significant influencing factors of population agglomeration in transportation service facilities, commercial and business facilities, public service facilities, station location, etc. The results show that there are differences in the relevant factors affecting people clustering in different types of high-speed rail stations. High-speed rail passenger flow is positively correlated with population scale, transportation facilities, and station building scale. Non-high-speed rail passenger flow is positively correlated with commercial and public service facilities, and negatively correlated with station location. The living or working population is positively correlated with population size, transportation facilities, and station building scale. The paper deeply analyzes the influence mechanism of high-speed railway station area crowd gathering, and explores the function mechanism of basic support force, node comprehensive strength, and place resident force for station area development. In the initial stage of station establishment, the urban development conditions provided the station with “basic support”, the change of traffic accessibility increased the value of the node, and attracted more non-resident passengers, and the station’s transportation facilities played the role of “node comprehensive power”. With the continuous improvement of the station area development and construction, various facilities provide “place resident power”, and the value of the place is prominent. The non-resident passenger flow began to overflow to the resident passenger flow. In addition, the information flow, logistics, and capital flow are converged in the station area, and the high- speed rail passenger flow is further enhanced. The spatial distribution of the agglomeration of non-high-speed rail passenger flows includes three agglomeration modes: fan-shaped agglomeration, balanced direction agglomeration, and insignificant agglomeration. The influence mechanisms of different agglomeration modes have certain differences. The high-speed rail has no obvious impact on the cluster of residents or working people in the station area. On the one hand, the construction time of stations in new urban areas or fringe areas is short. On the other hand, with the development of cities and urban agglomerations, the proportion and frequency of crowd trips have increased, but they have not yet formed a certain scale. Finally, this paper proposes related planning strategies such as coordinating the spatial relationship based on the multi-perspective of “people-station-city”, constructing efficient traffic based on “time-space-quantity” multi-level, and dynamic planning of station area based on “circle-environment-industry” multi-dimensionality.