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Gesture interfaces are needed for natural intuitive communication with machine devices. Hand gesture intuitiveness is the cognitive association between a command or intent, and its physical gestural expression. Using an automated tool we quantified intuitive indices for static gesture commands for a car navigation task. A small number of gestures were selected to express most of the commands with 1/3 used only by single individuals. This followed a power function analogous to Zipf's Law for languages. We found gesture preferences to be highly individualized, providing evidence to refute the hypothesis of the universality of gestures. A mathematical program was formulated to obtain a consensus gesture vocabulary for a car navigation system with the objective of maximizing total intuitiveness. We also introduced the notion of complex consensus gesture vocabularies in which multi-gestures are associated with single commands and multi-commands are associated with single gestures. We recommend hybrid gesture vocabularies, decided by consensus with several gestures selected individually.