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Abstracting routes to their route-defining locations
Umeå University, Faculty of Science and Technology, Department of Computing Science.ORCID iD: 0000-0002-5367-5322
Umeå University, Faculty of Science and Technology, Department of Computing Science.ORCID iD: 0000-0001-5629-0981
2022 (English)In: Computers, Environment and Urban Systems, ISSN 0198-9715, E-ISSN 1873-7587, Vol. 91, article id 101732Article in journal (Refereed) Published
Abstract [en]

Today's navigation assistance systems provide turn-by-turn instructions, which only focus on the next decision to take without offering any larger context. Information presentation is uniform and disconnected, i.e., any local instruction is equally important and not linked to any other decisions or the overall route context. This differs from how people usually give instructions and hinders spatial learning. In order to (re-)establish this larger context, we present an approach to identifying those locations along a route that define its characteristics, termed route-defining locations. These are prominent, easily recognized locations, which help relating the route to an environment's overall structure and a navigator's existing knowledge about the environment. The approach allows for determining route-defining locations on different levels of detail. Thus, at the same time it offers a mechanism for simplifying (or abstracting) a route. In this paper, we particularly focus on the latter aspect, presenting in detail the approach for identifying route-defining locations. For a given route, we, first, simplify its shape to extract those turns along the route that characterize its overall shape. Then, we rank landmarks and streets along the route based on their prominence. Finally, we include in the simplified route those turns that correspond to the locations of the most prominent landmarks and streets. The result is a set of route-defining locations extracted from the route shape, and prominent landmarks and streets along the route. In an agent-based simulation, we then evaluate the approach's ability to abstract a route to its characteristics, i.e., the defining locations. Results show that, indeed, our approach is effective in that respect, but success depends on ‘matching’ abstraction to an agent's knowledge about the environment.

Place, publisher, year, edition, pages
Elsevier, 2022. Vol. 91, article id 101732
Keywords [en]
Urban Studies, General Environmental Science, Ecological Modelling, Geography, Planning and Development
National Category
Transport Systems and Logistics
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:umu:diva-189958DOI: 10.1016/j.compenvurbsys.2021.101732ISI: 000721118900005Scopus ID: 2-s2.0-85119435388OAI: oai:DiVA.org:umu-189958DiVA, id: diva2:1614912
Funder
Swedish Research Council, 2018-05318Available from: 2021-11-28 Created: 2021-11-28 Last updated: 2023-04-17Bibliographically approved
In thesis
1. Escaping 'death by GPS': foundations for adaptive navigation assistance
Open this publication in new window or tab >>Escaping 'death by GPS': foundations for adaptive navigation assistance
2023 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Att undkomma "döden med GPS" : grunderna för adaptiv navigeringshjälp
Abstract [en]

Navigating through physical environments has evolved over time from using stars and maps to support the wayfinding, to employing Global Positioning Systems and navigation services. Turn-by-turn guidance of navigation services is an effective way to support wayfinding, but it may not align with the way humans naturally navigate. Over-reliance on navigation services can lead to confusion, frustration, and even dangerous situations. Humans use environmental cues to support their navigation decisions and understand their position, orientation, and surroundings. Navigation services prioritize efficient route planning and may not consider factors, such as complexity, that can impact travel. This discrepancy between navigation services and human navigation highlights the importance of incorporating principles of human wayfinding into navigation systems to enhance the overall wayfinding experience.

This thesis aims to improve navigation services by exploring their adaptive capabilities and addressing the discrepancies between navigation services and human wayfinding. The research focuses on identifying difficult-to-navigate intersections and prominent locations along a route that are important for successful navigation, and developing automated ways to identify them. The thesis also explores adapting instruction giving to the route and its surrounding.

The research included in this thesis analyzed geographic data, developed models and measures that extended existing research, and conducted empirical human subject studies. This work developed models that optimize route search for specific criteria, including traffic and social costs. It also proposes approaches to identifying and simplifying prominent locations along a route that define the relationship between the route and the environment. Results show that people tend to prefer less complex routes with fewer prominent locations. Results also indicate that incorporating route-defining locations in route directions can aid wayfinders in forming useful spatial memory of the environment. Additionally, the studies identified the language used and spatial reasoning mechanisms as sources of mismatches between navigation instructions and human understanding of a given wayfinding situation, which may provide insights into improving the generation of instructions.

Place, publisher, year, edition, pages
Umeå: Umeå University, 2023. p. 54
Series
UMINF, ISSN 0348-0542 ; 23.03
Keywords
wayfinding, navigation systems, navigation complexity, prominent locations, route generalization, spatial cognition, mental models, route learning, direction giving, Human-centered study.
National Category
Computer Sciences
Identifiers
urn:nbn:se:umu:diva-206805 (URN)978-91-8070-025-2 (ISBN)978-91-8070-024-5 (ISBN)
Public defence
2023-05-11, MIT.A.121, Umeå, 09:00 (English)
Opponent
Supervisors
Available from: 2023-04-20 Created: 2023-04-17 Last updated: 2023-04-17Bibliographically approved

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Teimouri, FatemeRichter, Kai-Florian

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