Abstract
Abstract. Knowledge about real-life user behaviour is an important factor for the design of navigation systems. Prompted by the observation that users tend to use our campus navigation app in unexpected ways, we present a naturalistic study of navigation logs. The data set consists of sensor and interaction data from over 4600 sessions, collected over a span of several months from hundreds of users. In our analysis, we demonstrate how the core concepts from navigation literature, i. e. wayfinding and locomotion, can be observed, but also point out differences to previous studies and assumptions. One of our main findings is that the application is mostly used to plan routes in advance, and not to navigate along them. Furthermore, detailed case-studies of actual navigation sessions provide a unique insight into user behaviour and show that persons are often not focused on their navigation task but engaged otherwise. Based on these results, we formulate design implications that do not only apply to future iterations of our application, but can be seen as best practices for pedestrian navigation apps in general.
Highlights
Information about a user’s context is an essential requirement for any system that aims to provide targeted assistance
As a step towards this goal, in the present study we explore what insights can be gained based on naturalistic log data of our campus navigation app
Looking at the log files we noticed that usage patterns differed from what we had expected based on previous studies, e. g. causing worse positioning performance and aborted navigation sessions
Summary
Information about a user’s context is an essential requirement for any system that aims to provide targeted assistance. As a step towards this goal, in the present study we explore what insights can be gained based on naturalistic log data of our campus navigation app. For the past 4 years, we have been providing a web-based navigation system for our university campus, with about 50-100 daily visits leading to 15-30 navigation sessions during weekdays, and up to 500 visits during large conferences or when a new semester begins. This underlines the necessity for such a system and indicates that many people are — at least partly — unfamiliar with the environment. After a gaining an overview of the data set, we highlight several aspects in more detail by means of illustrative examples, followed by a discussion of the results and possibilities for future work
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