Infrastructure Engineering - Research Publications

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    Imprecise Navigation
    Duckham, M ; Kulik, L ; Worboys, MF (SpringerLink, 2003)
    Conventional models of navigation commonly assume a navigation agent's location can be precisely determined. This paper examines the more general case, where an agent's actual location cannot be precisely determined. This paper develops a formal model of navigation under imprecision using a graph. Two key strategies for dealing with imprecision are identified and defined: contingency and refinement. A contingency strategy aims to find an instruction sequence that maximizes an agent's chances of reaching its destination. A refinement strategy aims to use knowledge gained as an agent moves through the network to disambiguate location. Examples of both strategies are empirically tested using a simulation with computerized navigation agents moving through a road network at different levels of locational imprecision. The results of the simulation indicate that both the strategies, contingency and refinement, applied individually can produce significant improvements in navigation performance under imprecision, at least at relatively fine granularities. Using both strategies in concert produced significant improvements in performance across all granularities.
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    "Simplest" paths: automated route selection for navigation
    DUCKHAM, MATT ; KULIK, LARS (Springer, 2003)
    Numerous cognitive studies have indicated that the form andcomplexity of route instructions may be as important to human navigatorsas the overall length of route. Most automated navigation systemsrely on computing the solution to the shortest path problem, and not theproblem of finding the “simplest” path. This paper addresses the issueof finding the “simplest” paths through a network, in terms of the instructioncomplexity. We propose a “simplest” paths algorithm that hasquadratic computation time for a planar graph. An empirical study ofthe algorithm’s performance, based on an established cognitive model ofnavigation instruction complexity, revealed that the length of a simplestpath was on average only 16% longer than the length of the correspondingshortest path. In return for marginally longer routes, the simplest pathalgorithm seems to offer considerable advantages over shortest paths interms of their ease of description and execution. The conclusions indicateseveral areas for future research: in particular cognitive studies areneeded to verify these initial computational results. Potentially, the simplestpaths algorithm could be used to replace shortest paths algorithmsin any automated system for generating human navigation instructions,including in-car navigation systems, Internet driving direction servers,and other location-based services.