Abstract

Public transport maps are typically designed in a way to support route finding tasks for passengers, while they also provide an overview about stations, metro lines, and city-specific attractions. Most of those maps are designed as a static representation, maybe placed in a metro station or printed in a travel guide. In this paper, we describe a dynamic, interactive public transport map visualization enhanced by additional views for the dynamic passenger data on different levels of temporal granularity. Moreover, we also allow extra statistical information in form of density plots, calendar-based visualizations, and line graphs. All this information is linked to the contextual metro map to give a viewer insights into the relations between time points and typical routes taken by the passengers. We also integrated a graph-based view on user-selected routes, a way to interactively compare those routes, an attribute- and property-driven automatic computation of specific routes for one map as well as for all available maps in our repertoire, and finally, also the most important sights in each city are included as extra information to include in a user-selected route. We illustrate the usefulness of our interactive visualization and map navigation system by applying it to the railway system of Hamburg in Germany while also taking into account the extra passenger data. As another indication for the usefulness of the interactively enhanced metro maps we conducted a controlled user experiment with 20 participants.Graphical abstract

Highlights

  • Traveling in a foreign city typically requires inspecting a public transport map (Netzel et al 2017b) placed at a metro station’s wall, in a travel guide, on carriage walls, on the web, or on a smart phone

  • Public transport maps are typically designed in a way to support route finding tasks for passengers, while they provide an overview about stations, metro lines, and city-specific attractions

  • We describe a dynamic, interactive public transport map visualization enhanced by additional views for the dynamic passenger data on different levels of temporal granularity

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Summary

Introduction

Traveling in a foreign city typically requires inspecting a public transport map (Netzel et al 2017b) placed at a metro station’s wall, in a travel guide, on carriage walls, on the web, or on a smart phone. The ‘old-fashioned’ maps try to focus on an uncluttered and aesthetically looking appearance by distorting the stations in a way that the exact geographic position is not given anymore, but the topology is still preserved to a high degree This layout strategy allows to reclaim space that would be wasted if the exact. There is typically no support for travelers to compute routes in a map that follow user-defined criteria and properties like passenger numbers, traveling distances, or famous sights, even for certain points in time Extending this idea to several maps instead of one can provide extra automatically generated information for planning a route somewhere that is based on users’ intentions, i.e., in scenarios in which the city to travel to is not explicitly known beforehand

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