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The influence of landmarks and urban form on cognitive maps using virtual reality
Highlights Configurations of landmark objects assist in route learning and scene recognition. Employed virtual reality to study the influence of landmarks on cognitive maps. Landmark configuration accuracy is highly correlated with route accuracy. Wide variation exists in subjects' map drawings for both route and landmark recall. Findings illuminate the importance of unique landmark configurations in cities.
Abstract To better understand the role of landmarks on cognitive maps, a framework was designed in which participants wore a virtual reality head-mounted display and traversed an unknown, hypothetical urban environment. The virtual environment featured a gridded street network measuring 5 × 5 blocks with a range of development types including residential, park, commercial and industrial districts. Participants followed navigational cues along a fixed route using a gaming controller. Along the route they were exposed to ten distinct landmarks in a unique random configuration. Following navigation, participants were administered several recall tasks which were designed to assess landmark, route, and survey knowledge. The Route and Landmark Recall tasks required participants to draw their perceived route and identify the landmark locations. Then, the Scene Recognition task required matching one of the ten landmark objects with a corresponding scene. Landmark Configuration Accuracy was found to be highly correlated with Route Recall performance and moderately correlated with scene matching scores. This suggests that, regardless of landmark type, individuals who more precisely recalled landmark locations also navigated the route and identified scenes more accurately. Landscape and urban planners can leverage these findings to advocate for the strategic inclusion of landmarks throughout an urban fabric, which we term Landmark Configuration Plans.
The influence of landmarks and urban form on cognitive maps using virtual reality
Highlights Configurations of landmark objects assist in route learning and scene recognition. Employed virtual reality to study the influence of landmarks on cognitive maps. Landmark configuration accuracy is highly correlated with route accuracy. Wide variation exists in subjects' map drawings for both route and landmark recall. Findings illuminate the importance of unique landmark configurations in cities.
Abstract To better understand the role of landmarks on cognitive maps, a framework was designed in which participants wore a virtual reality head-mounted display and traversed an unknown, hypothetical urban environment. The virtual environment featured a gridded street network measuring 5 × 5 blocks with a range of development types including residential, park, commercial and industrial districts. Participants followed navigational cues along a fixed route using a gaming controller. Along the route they were exposed to ten distinct landmarks in a unique random configuration. Following navigation, participants were administered several recall tasks which were designed to assess landmark, route, and survey knowledge. The Route and Landmark Recall tasks required participants to draw their perceived route and identify the landmark locations. Then, the Scene Recognition task required matching one of the ten landmark objects with a corresponding scene. Landmark Configuration Accuracy was found to be highly correlated with Route Recall performance and moderately correlated with scene matching scores. This suggests that, regardless of landmark type, individuals who more precisely recalled landmark locations also navigated the route and identified scenes more accurately. Landscape and urban planners can leverage these findings to advocate for the strategic inclusion of landmarks throughout an urban fabric, which we term Landmark Configuration Plans.
The influence of landmarks and urban form on cognitive maps using virtual reality
Bruns, Conner R. (author) / Chamberlain, Brent C. (author)
Landscape and Urban Planning ; 189 ; 296-306
2019-05-08
11 pages
Article (Journal)
Electronic Resource
English
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