A self-adaptive parking lot changeable entrance and exit control method, comprising: receiving historical vehicle data at entrance and exit barrier gates of a parking lot (step a); on the basis of the historical vehicle data at the entrance and exit barrier gates of the parking lot, predicting the number of vehicles leaving the parking lot in a unit time and the number of vehicles entering the parking lot in the unit time (step b); calculating the minimum value of the number of exit lanes lot and the minimum value of the number of entrance lanes required by the parking (step c); using queuing information of an upstream road section at the entrance and exit of the parking lot, queuing information of a downstream road section of the entrance and exit of the parking lot, queuing information of a road section inside the parking lot, the number of vehicles leaving the parking lot in the unit time, and the number of vehicles entering the parking lot in the unit time as input, and using the minimum value of the number of exit lanes and the minimum value of the number of the entrance lanes of the parking lot, and an entrance and exit lane setting principle as constraint conditions, constructing a parking lot entrance and exit lane setting model, and training the model using interaction data (step d); in the trained model, inputting the real-time information of the queuing information of the downstream road section at the entrance and exit of the parking lot, the queuing information of the road section in the parking lot, the number of vehicles leaving the parking lot in the unit time, and the number of vehicles entering the parking lot in the unit time, and by using the entrance and exit lane setting model of the parking lot, outputting the setting of each entrance and exit lane of the parking lot (step e).


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    Title :

    Self-adaptive parking lot changeable entrance and exit control method


    Publication date :

    2024-12-11


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English



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