Shape‐Guided Mixed Metro Map Layout

Author:

Batik T.1ORCID,Terziadis S.1ORCID,Wang Y.‐S.2ORCID,Nöllenburg M.1ORCID,Wu H.‐Y.13ORCID

Affiliation:

1. TU Wien Austria

2. National Yang Ming Chiao Tung University Taiwan

3. St. Pölten University of Applied Sciences Austria

Abstract

AbstractMetro or transit maps, are schematic representations of transit networks to facilitate effective route‐finding. These maps are often advertised on a web page or pamphlet highlighting routes from source to destination stations. To visually support such route‐finding, designers often distort the layout by embedding symbolic shapes (e.g., circular routes) in order to guide readers' attention (e.g., Moscow map and Japan railway map). However, manually producing such maps is labor‐intensive and the effect of shapes remains unclear. In this paper, we propose an approach to generalize such mixed metro maps that take user‐defined shapes as an input. In this mixed design, lines that are used to approximate the shapes are arranged symbolically, while the remaining lines follow classical layout convention. A three‐step algorithm, including (1) detecting and selecting routes for shape approximation, (2) shape and layout deformation, and (3) aligning lines on a grid, is integrated to guarantee good visual quality. Our contribution lies in the definition of the mixed metro map problem and the formulation of design criteria so that the problem can be resolved systematically using the optimization paradigm. Finally, we evaluate the performance of our approach and perform a user study to test if the embedded shapes are recognizable or reduce the map quality.

Funder

Austrian Science Fund

Publisher

Wiley

Subject

Computer Graphics and Computer-Aided Design

Reference55 articles.

1. Convergence Analysis and Quality Criteria for an Iterative Schematization of Networks

2. Metro Maps on Octilinear Grid Graphs

3. Metro Maps on Flexible Base Grids

4. BrosiP.: A toolchain for generating transit maps from schedule data. InSchematic Mapping Workshop(2022). 10

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2. On the Perception of Small Sub-graphs;Lecture Notes in Computer Science;2023

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