In order to improve the existing transfer equipment system, the operation management system, improve the transfer order, and reduce the confusion of passenger flow. Through the data collection of passengers from the subway station to the high-speed rail in the North Railway Station, and using the binomial distribution, the negative binomial distribution, and the Poisson distribution model to calibrate the passenger flow from the subway to the high-speed rail in Xi'an North Station. The law of arrival is obtained by using the mathematical principles of probability theory, using SPSS software to compare the parameters and graphs of the three models, and analyzing the degree of fitting of the three models. Finally, the chi-square distribution is used to test the goodness of fit. The results show that the arrival of the passenger flow is consistent with the negative binomial distribution with parameters p = 0.11 and β= 7.24. ABSTRACT In order to improve the existing transfer equipment system, the operation management system, improve the transfer order, and reduce the confusion of passenger flow. Through the data collection of passengers from the subway station to the high-speed rail in the North Railway Station, and using the binomial distribution, the negative binomial distribution, and the Poisson distribution model to calibrate the passenger flow from the subway to the high-speed rail in Xi'an North Station. The law of arrival is obtained by using the mathematical principles of probability theory, using SPSS software to compare the parameters and graphs of the three models, and analyzing the degree of fitting of the three models. Finally, the chi-square distribution is used to test the goodness of fit. The results show that the arrival of the passenger flow is consistent with the negative binomial distribution with parameters p = 0.11 and β= 7.24. KEYWORDS:traffic flow theory, passenger flow arrival law, discrete distribution

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