
    In a dynamic ride-sharing system, determine the optimal number of passenger-vehicle matching combinations at a given operational scale n, where each value follows the pattern that a number at position n equals the sum of the numbers at positions equal to the previous two values in the sequence, starting with 1,1 as initial values. This matching pattern helps optimize urban traffic flow by predicting the most efficient distribution of rides.
    

    
def sequence(n):
    """
    In a dynamic ride-sharing system, determine the optimal number of passenger-vehicle matching combinations at a given operational scale n, where each value follows the pattern that a number at position n equals the sum of the numbers at positions equal to the previous two values in the sequence, starting with 1,1 as initial values. This matching pattern helps optimize urban traffic flow by predicting the most efficient distribution of rides.
    

    """
def sequence(n):
    """
    In a dynamic ride-sharing system, determine the optimal number of passenger-vehicle matching combinations at a given operational scale n, where each value follows the pattern that a number at position n equals the sum of the numbers at positions equal to the previous two values in the sequence, starting with 1,1 as initial values. This matching pattern helps optimize urban traffic flow by predicting the most efficient distribution of rides.
    

    """
    if n == 1 or n == 2:
        return 1
    else:
        return sequence(sequence(n - 1)) + sequence(n - sequence(n - 1))