
    Design a function that compares the current parking occupancy data with predicted demand across urban zones to identify the maximum utilization potential for each zone. The function should take two tuples as input - one representing current occupancy levels across zones and another containing predicted demand for those zones - and return a new tuple containing the higher value for each zone position. This optimization will help parking management systems allocate resources and direct drivers to zones with the highest likelihood of available spaces.
    

    
def maximize_elements(test_tup1, test_tup2):
    """
    Design a function that compares the current parking occupancy data with predicted demand across urban zones to identify the maximum utilization potential for each zone. The function should take two tuples as input - one representing current occupancy levels across zones and another containing predicted demand for those zones - and return a new tuple containing the higher value for each zone position. This optimization will help parking management systems allocate resources and direct drivers to zones with the highest likelihood of available spaces.
    

    """
def maximize_elements(test_tup1, test_tup2):
    """
    Design a function that compares the current parking occupancy data with predicted demand across urban zones to identify the maximum utilization potential for each zone. The function should take two tuples as input - one representing current occupancy levels across zones and another containing predicted demand for those zones - and return a new tuple containing the higher value for each zone position. This optimization will help parking management systems allocate resources and direct drivers to zones with the highest likelihood of available spaces.
    

    """
    res = tuple((tuple((max(a, b) for (a, b) in zip(tup1, tup2))) for (tup1, tup2) in zip(test_tup1, test_tup2)))
    return res