In order to study the optimal parking lot allocation model under the intelligent parking guidance system, parking lot allocation model was established under the constraints of dual-objective function by considering the factors that influence the travelers when choosing a parking lot. The parking lot selection sets were obtained based on grey entropy theory. The optimal allocation scheme was verified according to the result of an example. Results indicate that the allocation scheme obtained by the model not only reduces the impacts of parking behavior on regional traffic but also lowers the parking cost of traveler and system. It is obviously superior to the traveler’s choice. When the capacity of parting lot is limited, all attributes of the parking lot allocation from the model are higher than that without parking lot capacity restriction. The parking lot selection of some vehicles is also not optimal. This indicates that the model can obtain the optimal parking lot allocation considering the interests of the travelers and provide a new way for parking lot management.