The visual complexity of bike maps

Abstract

Abstract. More and more cities try to encourage residents to cycle more. Therefore, governments are developing comprehensive bike maps to facilitate trip planning and increase the popularity of cycling. However, research on the topic of bike maps is rare and the versatility of possible features shown on a bike map makes these visually more complex than others. To understand how base maps and the display of cycling related features affect the visual complexity of bike maps and thus their effectiveness, we used different metrics (GMLMT, Subband Entropy, Edge Density, Feature Congestion, and Distinct Object-Type Counts) on four bike maps with four different visual complexity levels. We ran an eye-tracking experiment with 35 participants solving four different everyday tasks with these four bike maps. The findings suggest that adding more detail to base maps and displaying more cycling related features on a map resulted in a visually more complex bike map. Size, shape, and colour were found to have the biggest influence on the applied metrics. The analysis of eye-tracking data revealed that the display of cycling related features can affect the time needed for successfully completing a task. To deepen the gained understanding, further research should in more detail investigate how base maps influence bike maps efficiency.