'''
Result of kruskals algorithm with first 8 cars in the system.
The array shows the raw output, where the index and first item in the tuple 
is the vehicles position in the sorted `closest_vehicles` array.
The dictionary is the same data, just the keys and first item in of each tuple
replaced with the vehicle_id.

test_auto_example.png shows the position of these vehicles as well as the starting point.
'''

[
    [(1, 0.0018223418998603907), (2, 0.005142119115696336)], 
    [(0, 0.0018223418998603907), (4, 0.0038434786326951562)], 
    [(0, 0.005142119115696336)], 
    [(6, 0.003218020664940648), (4, 0.004116640377786014), (5, 0.005380458066000523)], 
    [(1, 0.0038434786326951562), (3, 0.004116640377786014)], 
    [(3, 0.005380458066000523)], 
    [(3, 0.003218020664940648), (7, 0.00569171626137669)], 
    [(6, 0.00569171626137669)]
]

vehicle_ids = {
    1: [(8, 0.0018223418998603907), (2, 0.005142119115696336)], 
    8: [(1, 0.0018223418998603907), (6, 0.0038434786326951562)], 
    2: [(1, 0.005142119115696336)], 
    7: [(5, 0.003218020664940648), (6, 0.004116640377786014), (3, 0.005380458066000523)], 
    6: [(8, 0.0038434786326951562), (7, 0.004116640377786014)], 
    3: [(7, 0.005380458066000523)], 
    5: [(7, 0.003218020664940648), (4, 0.00569171626137669)], 
    4: [(5, 0.00569171626137669)]
}