Recent advances in network science and the development of volunteered geographic information (VGI) have created new research opportunities in the topological analysis of road networks. The degree correlation of road networks is rarely studied. This study applied four measures, including the average degree of nearest neighbor, correlation profile, Newman's assortativity coefficient, and Litvak–Hofstad's assortativity coefficient, to measure the degree correlations of road networks represented as dual graphs of strokes, axial lines, and named roads. After investigating 100 road networks worldwide obtained from OpenStreetMap, it has been found that road networks are mostly disassortative or uncorrelated in stroke and named road representations, but assortative when represented as axial lines. Inconsistency in different measures persists regardless of method of representation; therefore, qualitative dichotomy or trichotomy is insufficient to describe the actual connection pattern in road networks. A taxonomy of road network assortativity is proposed. Two of the proposed disassortative types are associated with the absence of a grid pattern and are less robust than the typical disassortative type.