'Fine-to-coarse' route planning and navigation in regionalized environments

This source preferred by Jan Wiener

Authors: Wiener, J.M. and Mallot, H.A.

Journal: Spatial Cognition and Computation

Volume: 3

Pages: 331-358

ISSN: 1387-5868

DOI: 10.1207/s15427633scc0304_5

Environments that are divided into regions lead to hierarchical encoding of space. Such memory structures are known to systematically distort estimates of distance and direction and affect spatial priming and memory recall. Here we present two navigation experiments in virtual environments that reveal an influence of environmental regions on human route planning and navigation behaviour. Following the hierarchical theories of spatial representations, it is argued that environmental regions are explicitly represented in spatial memory and that human route planning takes into account region-connectivity and is not based on place-connectivity alone. We also propose a fine-to-coarse planning heuristic that could account for the empirical data by planning in a representation that uses fine-space information for close locations and coarse-space information for distant locations simultaneously.

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Authors: Wiener, J.M. and Mallot, H.A.

Journal: Spatial Cognition and Computation

Volume: 3

Issue: 4

Pages: 331-358

eISSN: 1542-7633

ISSN: 1387-5868

DOI: 10.1207/s15427633scc0304_5

Environments that are divided into regions lead to hierarchical encoding of space. Such memory structures are known to systematically distort estimates of distance and direction and affect spatial priming and memory recall. Here we present two navigation experiments in virtual environments that reveal an influence of environmental regions on human route planning and navigation behaviour. Following the hierarchical theories of spatial representations, it is argued that environmental regions are explicitly represented in spatial memory and that human route planning takes into account region-connectivity and is not based on place-connectivity alone. We also propose a fine-to-coarse planning heuristic that could account for the empirical data by planning in a representation that uses fine-space information for close locations and coarse-space information for distant locations simultaneously. © 2003, Lawrence Erlbaum Associates, Inc.

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