Using the Landmark–Route–Survey Framework to Evaluate Spatial Knowledge Obtained From Synthetic Vision Systems

Abstract

Objective: Using the landmark–route–survey frame-work, this research investigated the effect of synthetic vision systems (SVS) in either low or high visibility conditions on performance in wayfinding and spatial-knowledge-based tasks that probed spatial awareness. Background: SVS are cockpit displays that depict computer-generated views of the terrain surrounding an aircraft and have been developed to support flight efficiency through improved spatial awareness. No studies have directly measured SVS impact on the three levels of spatial knowledge (landmark, route, and survey). Method: A total of 55 nonpilots learned a route in four different experimental conditions (high or low visibility, either with or without SVS). Subsequently, they underwent four recall tasks: wayfinding, scene recognition, scene classification, and sketch map. Six dependent measures were used to probe the three levels of spatial knowledge (selection errors, sorting errors, number of landmarks depicted, bidimensional regression) and their use in the wayfinding task (direction errors, designated landmark errors, and wayfinding verbalized hesitations). Results: SVS produced higher performance in all four tasks. The low visibility condition lowered the wayfinding and scene-recognition performance. Conclusion: The overall results indicated that visibility mostly affected the first level of spatial knowledge (landmark) inducing a decreased wayfinding performance, whereas the use of SVS influenced the three levels of spatial knowledge (route and survey) inducing an increased wayfinding performance. Application: Potential applications of this work include spatial knowledge-based measures to evaluate SVS prototypes as well as to assess the relationship between spatial knowledge and spatial awareness.