In logical terms, a 2D map is a polymorphic form of linear objects made from practical features like roads, cartos (geometrical representation of a collection of buildings or specific features), roundabouts, highways, and many more. As autonomous vehicle disrupts transportation and navigation, there is a need to detect and identify map features at a granular level with no human intervention. This paper focuses on one of the practical problems, i.e. determining whether a junction is part of roundabouts using the Map domain, which is a novel approach to the best of the knowledge of an author. In a roundabout, the junction is the node having entry or exit of roads in or away from it. Closed loops in roads are extracted by traversing each link and checking for the common junctions using a deterministic algorithm. Loops can be formed not only by roundabouts it can be present at any intersection of roads, from all the universal sets of junctions; identifying the pattern and finding the right junctions of a roundabout is a very challenging and exciting problem. The authors have solved this problem in two parts; data extraction is done by collecting all the roads of America and Europe and then features are extracted, which depend on logical and domain knowledge. Finally, for the fuzzy part of features, a machine model that provides an efficient accuracy of 81% is created as it reduces lots of manual effort for verifying and correcting junctions. This applied methodology is easy to implement.