%0 Journal Article
%T Enhancing a Commercial Game Engine to Support Research on Route Realism for Synthetic Human Characters
%A Gregg T. Hanold
%A Mikel D. Petty
%J International Journal of Computer Games Technology
%D 2011
%I Hindawi Publishing Corporation
%R 10.1155/2011/819746
%X Generating routes for entities in virtual environments, such as simulated vehicles or synthetic human characters, is a long-standing problem, and route planning algorithms have been developed and studied for some time. Existing route planning algorithms, including the widely used A* algorithm, are generally intended to achieve optimality in some metric, such as minimum length or minimum time. Comparatively little attention has been given to route realism, defined as the similarity of the algorithm-generated route to the route followed by real humans in the same terrain with the same constraints and goals. Commercial game engines have seen increasing use as a context for research. To study route realism in a game engine, two developments were needed: a quantitative metric for measuring route realism and a game engine able to capture route data needed to compute the realism metric. Enhancements for recording route data for both synthetic characters and human players were implemented within the Unreal Tournament 2004 game engine. A methodology for assessing the realism of routes and other behaviors using a quantitative metric was developed. The enhanced Unreal Tournament 2004 game engine and the realism assessment methodology were tested by capturing data required to calculate a metric of route realism. 1. Introduction Entities in virtual environments, such as simulated vehicles or synthetic humans, move from place to place in the virtual environment. Algorithms to automatically generate those routes have been developed and studied for some time. The A* graph search algorithm, because of its simplicity and effectiveness, has been applied in a range of simulation environments, including Close Combat Tactical Trainer, Combat XXI, and OneSAF Objective System, and games such as Warcraft and Civilization; some of these applications use variants of the basic A* algorithm [4]. Most route planning algorithms, including A*, are designed to produce or approximate optimum routes, where optimality is measured in terms of some application-specific metric; examples include minimum distance for individual humans moving in urban terrain [5], minimum distance for vehicles moving in a road network [6], minimum exposure to threats for combatants moving in a battle area [7], or maximum sensor coverage for search platforms surveying a target area [8]. In contrast, very little attention has been given to producing realistic routes, where realism is defined as the similarity of the generated route to a route that would be followed by a real human in the same terrain with the
%U http://www.hindawi.com/journals/ijcgt/2011/819746/