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The need for greater capacity in automotive transportation (in the midst of constrained resources) and the convergence of key technologies from multiple domains may eventually produce the emergence of a “swarm” concept of operations. The swarm, a collection of vehicles traveling at high speeds and in close proximity, will require management techniques to ensure safe, efficient, and reliable vehicle interactions. We propose a shared-autonomy approach in which the strengths of both human drivers and machines are employed in concert for this management. A fuzzy logic-based control implementation is combined with a genetic algorithm to select the shared-autonomy architecture and sensor capabilities that optimize swarm operations.

An evolving aircraft synthesis simulation environment which offers improvements to existing methods at multiple levels of a design process is described in this paper. As design databases become obsolete due to the introduction of new technologies and classes of vehicles and as sophisticated analysis codes are often too computationally expensive for iterative applications, the design engineer may find a lack of usable information needed for decision making. Within the environment developed in this paper, rapid sensitivity analysis is possible through a unique representation of the relationship between fundamental design variables and system objectives. The combined use of the Design of Experiments and Response Surface techniques provides the ability to form this design relationship among system variables and target values, which is termed design-oriented in nature.