
    Given the number of primary delivery routes (n) that avoid high-traffic areas, calculate the total weighted impact of traffic density by summing the squared traffic density values of these routes, considering only routes with odd identification numbers. The traffic density value of each route corresponds to its position in the sequence of odd numbers (1, 3, 5, etc.), and the square of this value represents its weighted impact on delivery times.
    

    
def square_Sum(n):
    """
    Given the number of primary delivery routes (n) that avoid high-traffic areas, calculate the total weighted impact of traffic density by summing the squared traffic density values of these routes, considering only routes with odd identification numbers. The traffic density value of each route corresponds to its position in the sequence of odd numbers (1, 3, 5, etc.), and the square of this value represents its weighted impact on delivery times.
    

    """
def square_Sum(n):
    """
    Given the number of primary delivery routes (n) that avoid high-traffic areas, calculate the total weighted impact of traffic density by summing the squared traffic density values of these routes, considering only routes with odd identification numbers. The traffic density value of each route corresponds to its position in the sequence of odd numbers (1, 3, 5, etc.), and the square of this value represents its weighted impact on delivery times.
    

    """
    return int(n * (4 * n * n - 1) / 3)