Cognitively-inspired direction giving

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.Includes bibliographical references (p. 133-140).Online mapping services and portable GPS units make it easy to get very detailed driving directions. While these directions are sufficient for an automaton to follow, they do not present a big picture description of the route. As a result, while people can follow these detailed turn-by-turn directions, it can be difficult for them to actually comprehend where they are going. Our goal is to make such directions more comprehensible. Our approach is to apply findings from human spatial cognition, the study of how people conceptualize and organize their knowledge of large-scale space, to create a system that generates written route overviews. Route overviews provide a big picture description of a route, and are intended to supplement the information in turn-by-turn directions. Our route overviews are based on cognitively-inspired design criteria such as: the use of spatial hierarchy, goal-directed descriptions, selective suppression of detail, and the use of the trunk segments and cognitive anchor points along the route. In our experiments, we show that we can make directions more comprehensible independent of the particular places a person knows - by using what we know about how people think about space to structure the way we present spatial information.by Gary Wai Keung Look.Ph.D

An investigation into automated processes for generating focus maps

The use of geographic information for mobile applications such as wayfinding has increased rapidly, enabling users to view information on their current position in relation to the neighbouring environment. This is due to the ubiquity of small devices like mobile phones, coupled with location finding devices utilising global positioning system. However, such applications are still not attractive to users because of the difficulties in viewing and identifying the details of the immediate surroundings that help users to follow directions along a route. This results from a lack of presentation techniques to highlight the salient features (such as landmarks) among other unique features. Another problem is that since such applications do not provide any eye-catching distinction between information about the region of interest along the route and the background information, users are not tempted to focus and engage with wayfinding applications. Although several approaches have previously been attempted to solve these deficiencies by developing focus maps, such applications still need to be improved in order to provide users with a visually appealing presentation of information to assist them in wayfinding. The primary goal of this research is to investigate the processes involved in generating a visual representation that allows key features in an area of interest to stand out from the background in focus maps for wayfinding users. In order to achieve this, the automated processes in four key areas - spatial data structuring, spatial data enrichment, automatic map generalization and spatial data mining - have been thoroughly investigated by testing existing algorithms and tools. Having identified the gaps that need to be filled in these processes, the research has developed new algorithms and tools in each area through thorough testing and validation. Thus, a new triangulation data structure is developed to retrieve the adjacency relationship between polygon features required for data enrichment and automatic map generalization. Further, a new hierarchical clustering algorithm is developed to group polygon features under data enrichment required in the automatic generalization process. In addition, two generalization algorithms for polygon merging are developed for generating a generalized background for focus maps, and finally a decision tree algorithm - C4.5 - is customised for deriving salient features, including the development of a new framework to validate derived landmark saliency in order to improve the representation of focus maps

Recognition of Abstract Regions in Cartographic Maps

In the human interpretation of cartographic maps the areas we shall call abstract regions consist of several symbols (map objects), which are grouped to a single object. This abstraction process is an important part of human map interpretation. Abstract regions exist as mental objects in a mental map in the interpreter’s mind. In this article we describe an approach to automate the human process of recognizing abstract regions in cartographic maps by technical processes. We designed and implemented a system for defining abstract regions by hierarchical descriptions. The hierarchies are represented by attributed grammars that can be translated by a compilercompiler to yield a parser for abstract regions. With this parser, abstract region candidates that were identified by simple rules can be evaluated to check if they conform to the definition provided by the user. Our approach combines cognitive considerations on human abstraction with techniques from theoretical computer science and artificial intelligence