Analysis And Modeling Of College Students' Travel Behavior Under The Influence Of Shared Bicycles

Shared bicycles are a new form of bicycle transportation born under the “Internet +” background,which solves the “last mile” problem of residents' travel and changed the structure of urban residents' travel mode.However,the sharing bike management policy is in its infancy,the business operation model is not yet stable,and the characteristics of urban bicycle travel are full of “variables”.The related research shows that the group of college students is a strong support for ensuring the sharing of users.In order to better formulate the development policy of bicycle transportation,it is particularly important to analyze the factors affecting the sharing of college students' travel mode sharing age.On the basis of summarizing the existing related literatures,this paper proposes to establish a logit model theory based on the principal components of explanatory variables as a shared bicycle research model of influence factors of college students travel mode under the age.Firstly,a stratified random sampling method was used to investigate college students,and 517 RP survey data including individual information characteristics,riding habits,daily travel characteristics,etc.were collected,and data analysis software was applied to college students.The characteristics of the report are descriptive statistical analysis,and from the qualitative level,the impact of individual attributes and travel attributes on the sharing rate of each travel mode is analyzed.Then,based on the research needs of this paper,a two-story nested logit model(NL)is constructed with the riding frequency rank as the upper selection branch and the trip selection as the lower selection branch(NL).Using the SPSS software,the correlation analysis of travel mode-factor and riding frequency level-factor are performed respectively;using factor analysis methods to select the main components of the factors affecting travel mode and the factors affecting cycling frequency;according to the principal component regression principle,the principal components of the selected branch influence factors are used as independent variables of the Logit model utility function.And using SPSS analysis software to calibrate the logit model parameters;according calibration results,statistical indicators include containment factor,likelihood ratio,goodness ratio and hit rate verified the prediction accuracy of the behavior analysis model established in this paper was good.Finally,based on the calibration results of the model parameters,the influence of relevant factors on the mode of travel and riding frequency is analyzed from the qualitative level;a sensitivity analysis method based on expected values are proposed to analyze the impact of the main impacts on the choice of the college students' travel mode and the frequency of riding impact.The study in this article has the following meanings:(1)Firstly,in order to ensure the amount of bicycle users,and then obtain advantages in a fierce market environment,to achieve optimal allocation of enterprise resources,maximize the efficiency of enterprises.Operators formulate the scientific and reasonable operation management strategy with the reference to the conclusions of this paper;(2)Government departments refer to the research conclusions and formulate a scientific non-motorized transport infrastructure construction policy,this will create a good slow-moving travel environment,better guide the green travel of urban residents,and maximize the social benefits of shared bicycles in solving the problem in citizen last kilometer travel.