Interactive Relationship Between Ridership Characteristics At Subway Station And Surrounding Land-use

As a place for passengers getting on or off rail transit, rail transit station is a link between the passengers and rail traffic transit system, so rail lines as well as network passenger flow characteristics are essentially superposition and exchange of station passenger flow characteristics. At present, there is much research on rail lines and network passenger flow characteristics, but the research on the passenger flow characteristics of rail transit station is still a little. However, research on passenger flow characteristics of rail transit station has important implications for aspects of rail transit planning, passenger flow volume forecasting, land development around the station, the station scale design, operation organization, station access mode planning. Accordingly, this article take Beijing rail transit system as an example, researching on the passenger flow characteristics of rail transit station, and analyzing the relationship between the station passenger flow characteristics and the surrounding landuse characteristics. Furthermore, the impact on landuse from rail transit station even the leading role on urban space layout from rail transit network are discussed.The article carried out the following research aspects.Cluster analysis is implemented to classify Beijing rail transit stations based on full-time enter and exit passenger flow data of all time period, and the result of classification is test in two ways. On the one hand, the two-factor analysis of variance test indicates significant differences between the each classification; On the other hand, underlying causes of differences between each categories is analysed in connection with the categories of the population, jobs and landuse around the station positions. Furthermore, other station passenger flow characteristics in each category are analysed. All above research demonstrates that different landuse mode lead to the significant difference in enter and exit passenger flow time distribution, peak-hour factor, peak hour period, difference between weekday and weekend passenger flow characteristics. The non-parametric regression model was built between passenger flow volume of rail transit station and population, jobs, landuse, development intensity, station location. Furthermore, the non-parametric density estimation is implemented, it demonstrates that it exists significant factor relevance between the station passengers flow volume and the factors above. Besides, passengers flow volume of rail transit station can be predict by the non-parametric model established, it also would be useful to related work. By researching the impact of rail transit stations on the surrounding land use, it suggested that the land use and development intensity around the station show regular change with increasing distance from the center of the station. In addition, the rail transit station service scope increases by expansion of station access. Furthermore, expanding the scope of the study to the rail network, it demonstrates that urban rail transit network play an important role in supporting and guiding spatial layout.Some suggestions are proposed based on this study about rail transit planning and design, operation, landuse and development around the station, and station access planning and several aspects in the future work.