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Reassessing underlying spatial relations in pedestrian navigation: a comparison between sketch maps and verbal descriptions

Reassessing underlying spatial relations in pedestrian navigation: a comparison between sketch maps and verbal descriptions

Wang, Jia ORCID: 0000-0003-4379-9724 and Rui, Li (2018) Reassessing underlying spatial relations in pedestrian navigation: a comparison between sketch maps and verbal descriptions. In: Habib, Maki, (ed.) Handbook of Research on Investigations in Artificial Life Research and Development. Advances in Computational Intelligence and Robotics (ACIR) . IGI Global, pp. 49-67. ISBN 978-1522553960

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Abstract

This paper reassesses underlying spatial relations for pedestrian wayfinding by examining navigational directions given in both forms of sketch maps and verbal descriptions. An experiment was conducted to investigate characteristics of navigational directions provided by participants in the form of both sketch maps and verbal descriptions. The authors were specifically interested in the places and spatial relationships such as route topology, order relation and orientation extracted from the navigational directions. A new ontological approach to sketch and verbal interpretations was adopted for the spatial analysis of sketch maps and verbal descriptions. The results point to the advantage of including sketch components into pedestrian navigation systems over solely turn-by-turn instructions. In addition, it further showed the differences between visual and verbal directions which suggest different levels of directions necessary for giving specific types of navigational directions.

Item Type: Book Section
Uncontrolled Keywords: Sketch Maps, Verbal Descriptions, Navigation, Spatial Relations, Route, Landmark, Orientation, Linear Order, Topology
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / Department / Research Group: Faculty of Liberal Arts & Sciences
Faculty of Liberal Arts & Sciences > Greenwich GI Science Research Group
Faculty of Liberal Arts & Sciences > School of Computing & Mathematical Sciences (CAM)
Last Modified: 26 Nov 2020 22:34
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
Selected for REF2021: None
URI: http://gala.gre.ac.uk/id/eprint/19443

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