Irregularity Of Rail Transit Passengers Based On Smart Card Data

As a fast and large-capacity public transportation mode,urban rail transit plays an important role in solving residents' traveling problems and guiding urban development.As places for passengers to pick up,board and alight,urban rail transit stations are the link between passengers and rail transit,and passengers are the mainstay of the station.At present,the research on the temporal and spatial regularity of passengers in rail transit is sufficient,but the irregular travels such as sporadic trips are neglected,and the diversity and dispersion of rail transit passengers are rarely studied.The spatial and temporal dispersion of travel is the basis of traffic.The balanced use of facilities is significant.In this regard,this paper takes the passengers and stations in the urban rail transit system as the object and establishes the information entropy model through a large number of smart card data,and analyzes the diversity of the travel behavior of passengers in the temporal and spatial dimensions.The extent to which station visited are decentralized,and the influencing factors affecting the dispersion are explored,providing new insights for solving the problem of rail traffic station current limit and improving the balanced use of rail transit infrastructure.Firstly,the model of spatial entropy and temporal entropy are defined and measured in the spatial and temporal dimension from the perspective of passengers.The entropy of passenger travelling assesses the diversity of passenger travel.When the entropy value is greater than zero,the larger the entropy value is,the stronger the diversity of passenger travel 212s.The calculation results show that the distribution law of spatial and temporal entropy values are similar.In the spatial dimension,the number of passenger who travel once and twice a week is relatively large..In this paper,the spatial and temporal dimensions of passengers with spatial entropy of 0.5 and different trip times are analyzed.The analysis results show that most passengers travel for the purpose of leaving and arriving Beijing and shopping.In terms of the distribution characteristics of passenger flow boarding and alighting,the passenger flow characteristics of passengers traveling twice a week are similar to the overall passenger flow,and the characteristics of passengers who travel multiple times have no obvious morning and evening peaks.Secondly,this paper calculates entropy consisting of station passengers and station passenger visiting slots from the perspective of the station to comprehensively evaluate the service function mixture of the station.The calculation of entropy consisting of station passengers considers the distribution of the number of visited times and the corresponding number of people in Beijing rail transit stations,and establishes the information entropy model for calculation;the calculation of entropy consisting of station passengers' visiting slots considers the temporal distribution uniformity of boarding of Beijing rail transit stations,and calculates entropy consisting of station passenger visiting slots.The results show that the higher entropy consisting of station passengers and passengers' visiting slots of the Beijing rail transit station are mainly distributed within the four rings,and the closer to the outer ring,the smaller the entropy value.For the cross-analysis of entropy consisting of station passengers and passengers' visiting slots,most of the boarding on the weekend is more dispersed in the temporal dimension,while the workday's boarding is more concentrated.Finally,by constructing a geographically weighted regression model and the ordinary least squares regression model which dependent variable is entropy consisting of station passengers and station passenger visiting slots,various factors affecting the entropy consisting of station passengers and station passenger visiting slots are analyzed.Comparing the two models,the entropy consisting of station passengers and station passenger visiting slots has obvious spatial heterogeneity,and the geographical weighted regression model can better explain the difference of station entropy values.For policy formulation and urban planning,they hope that they can study on the positive factor and the entropy value of the station will be bigger so as to avoid the phenomenon of morning and evening peaks where passengers travel too concentrated in a certain period of time,improve the shortage of resources in rail transit facilities during peak hours,improve the low utilization rate of rail transit facilities during flat peak and promote the service level of safety and reliability of the rail transit system.