This paper uses nest logit model to analyze the travel behavior data of passengers at Pudong Airport. This study classifies the travel mode, occupations and travel purposes. Our modeling outcomes show that: (1) women are more likely to choose self-driving than men, which is different from the existing literature; (2) the passengers who go to the airport in the morning have the highest probability of choosing a taxi, especially before 9 o'clock; (3) the higher the bus accessibility, the lower the possibility of choosing airport bus; (4) taxis should also be listed in private transportation besides car passenger and self-driving. In addition, an interesting new variable has been found, data acquisition time can be used for model analysis. The moment when questionnaire is to be filled is recorded in the system, which to be found has great contributions to model. Key Words: Travel behavior, Travel time value, Policy, Variable composition

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