Route network datasets, crucial to transport models, have grown complex, leading to visualization issues and potential misinterpretations. We address this by presenting two methods for simplifying these datasets: image skeletonization and Voronoi diagram-centreline identification. We have developed two packages, the ‘parenx’ Python package (available on pip) and the ‘rnetmatch’ R package (available on GitHub) to implement these methods. The approach has applications in transportation, demonstrated by their use in the publicly available Network Planning Tool funded by Transport for Scotland.