This article studies fuzzy rules that were used to model autonomous entities and discusses the development of a metamodel to describe the traffic flow of autonomous agents over a spatial area. The agents deliver goods (and themselves) to prespecified locations on the given spatial area. The metamodel is defined as a set of equations, obtained through regression analysis, that are functions of several variables that affect the agent system. The performance measures are effective speed and collision probability. The fuzziest rule set consistently gave the best results in terms of collision avoidance for this study. The improved collision avoidance is gained at the cost of a lower effective speed. A "traffic control" policy may be desirable when congestion reaches a limit. The flow metamodel equations describe the emergent behavior of the system, or system-level behavior resulting from interactions at the level of the parts of the system. The equations can be used to determine whether congestion will be a problem before designing a system containing entities that navigate among themselves. The flow metamodel curves suggest combinations of system parameters that will alleviate congestion. The results have implications for several practical applications.
|Original language||English (US)|
|Number of pages||11|
|Journal||IIE Transactions (Institute of Industrial Engineers)|
|State||Published - Nov 2004|
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering