Visual complexity of bike maps

Abstract

More and more cities try to encourage residents to cycle more. Therefore, governments are developing comprehensive bike maps to facilitate bicycle trip planning and, as a result, increase the popularity of cycling in general (Pucher and Buehler, 2008). 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. It is critical to understand how maps are perceived and understood to improve their overall design and efficiency (Castner and Eastman, 1984). The purpose of this thesis is understand how base maps and the display of various cycling related features a↵ect the visual complexity of bike maps. Different metrics (GMLMT, Subband Entropy, Edge Density, Feature Congestion, and Distinct Object-Type Counts) are applied on bike maps to measure visual map complexity. Following that, an eye-tracking experiment with 35 participants is carried out. Five different everyday tasks have to be solved on bike maps with four complexity levels. The experiment aims to find out how base maps and cycling related features influence the effectiveness of a map. 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 color were found to have the biggest influence on the applied metrics. The eye-tracking study discovered that the display of cycling related features can affect the time needed for successful task completion. To deepen the gained understanding, further research should in more detail investigate how base maps influence bike maps efficiency. To gain maximal learning from such studies, large and representative test groups should be examined in a fully randomized manner