An Algorithmic Framework for Labeling Road Maps

TL;DR

This paper introduces a new algorithmic framework for labeling roads on maps that maximizes labeled sections, demonstrating efficiency and near-optimal results compared to existing methods across multiple city maps.

Contribution

The paper presents a novel, versatile framework for road map labeling that improves coverage and efficiency, outperforming standard rendering methods.

Findings

Labels 31% more road sections on average than Mapnik

Algorithm is fast and achieves near-optimal solutions

Effective across diverse city maps

Abstract

Given an unlabeled road map, we consider, from an algorithmic perspective, the cartographic problem to place non-overlapping road labels embedded in their roads. We first decompose the road network into logically coherent road sections, e.g., parts of roads between two junctions. Based on this decomposition, we present and implement a new and versatile framework for placing labels in road maps such that the number of labeled road sections is maximized. In an experimental evaluation with road maps of 11 major cities we show that our proposed labeling algorithm is both fast in practice and that it reaches near-optimal solution quality, where optimal solutions are obtained by mixed-integer linear programming. In comparison to the standard OpenStreetMap renderer Mapnik, our algorithm labels 31% more road sections in average.