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Enhancing wayfinding and route learning

A human-centred study of the route-defining locations algorithm

Bibliographic Data

ID21452103
AuthorsFateme Teimouri (0000-0002-5367-5322, Umeå University, corresponding author), Kai-Florian Richter (0000-0001-5629-0981, Umeå University)
Year2025
Volume44
Issue1
Pages44-60
Publication date2025-01-02
Open AccessYes
TypeARTICLE
VenueBehaviour and Information Technology (JOURNAL)
Journal identifiersISSN: 0144-929X • E-ISSN: 1362-3001
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/0144929x.2024.2308754
OpenAlexW4392017122
LanguageEN
Citations received1
References cited46

Navigation services play a crucial role in everyday wayfinding. One of their key features is the turn-by-turn guidance, enabling wayfinders to navigate efficiently between locations. However, over-reliance on turn-by-turn guidance can hinder wayfinders' ability to perceive their surroundings and develop spatial awareness, negatively impacting user experience. Previous research has addressed these issues by modifying instructions, user interaction, or both. However, the applicability of these methods beyond specific studies remains unclear. This paper presents a human-centred study by evaluating an algorithm that automatically generates navigation instructions. The instructions are generated by adding route-defining locations to ‘standard’ turn-by-turn instructions to enhance wayfinder's spatial knowledge acquisition, and improve user experience. Route-defining locations, identified using a previously proposed algorithm, serve as anchors for the wayfinder to form a spatial understanding of the environment. The study involved 36 participants divided into two groups: one received ‘standard’ turn-by-turn (TBT) instructions, while the other received instructions that included route-defining locations (RDL). Participants navigated in an unfamiliar virtual environment, and their wayfinding and route learning were compared between the two groups. Results show that RDL instructions led to better wayfinding and route learning performance compared to TBT instructions, suggesting the potential to improve navigation systems and user experiences

Algorithm · Human–computer interaction · Transport engineering · Artificial Intelligence · Computer Science · Engineering · Geographic Information Systems Studies · Geography Education and Pedagogy · Spatial Cognition and Navigation

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Citations per year1
Citation span2026 - 2026 (1)
Highly citedNo

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