Entropy and a sub-group of geometric measures of paths predict the navigability of an environment

Yesiltepe, D, Fernández Velasco, P, Coutrot, A, Ozbil Torun, A, Wiener, J M, Holscher, C, Hornberger, M, Conroy Dalton, R and Spiers, H J (2023) Entropy and a sub-group of geometric measures of paths predict the navigability of an environment. Cognition, 236, 105443. (doi:10.1016/j.cognition.2023.105443).

Abstract

Despite extensive research on navigation, it remains unclear which features of an environment predict how difficult it will be to navigate. We analysed 478,170 trajectories from 10,626 participants who navigated 45 virtual environments in the research app-based game Sea Hero Quest. Virtual environments were designed to vary in a range of properties such as their layout, number of goals, visibility (varying fog) and map condition. We calculated 58 spatial measures grouped into four families: task-specific metrics, space syntax configurational metrics, space syntax geometric metrics, and general geometric metrics. We used Lasso, a variable selection method, to select the most predictive measures of navigation difficulty. Geometric features such as entropy, area of navigable space, number of rings and closeness centrality of path networks were among the most significant factors determining the navigational difficulty. By contrast a range of other measures did not predict difficulty, including measures of intelligibility. Unsurprisingly, other task-specific features (e.g. number of destinations) and fog also predicted navigation difficulty. These findings have implications for the study of spatial behaviour in ecological settings, as well as predicting human movements in different settings, such as complex buildings and transport networks and may aid the design of more navigable environments.

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Contributors

Author: M Hornberger

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