@article{ref1,
title="Optimization of Shared Autonomy Vehicle Control Architectures for Swarm Operations",
journal="IEEE transactions on systems, man, and cybernetics. Part B, cybernetics",
year="2010",
author="Sengstacken, Aaron J. and Delaurentis, D. A. and Akbarzadeh-T, Mohammad R.",
volume="40",
number="4",
pages="1145-1157",
abstract="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 &quot;swarm&quot; concept of operations. The swarm, which is a collection of vehicles traveling at high speeds and in close proximity, will require technology and management techniques to ensure safe, efficient, and reliable vehicle interactions. We propose a shared autonomy control approach, in which the strengths of both human drivers and machines are employed in concert for this management. Building from a fuzzy logic control implementation, optimal architectures for shared autonomy addressing differing classes of drivers (represented by the driver's response time) are developed through a genetic-algorithm-based search for preferred fuzzy rules. Additionally, a form of &quot;phase transition&quot; from a safe to an unsafe swarm architecture as the amount of sensor capability is varied uncovers key insights on the required technology to enable successful shared autonomy for swarm operations.<p /> <p>Language: en</p>",
language="en",
issn="1083-4419",
doi="10.1109/TSMCB.2009.2035099",
url="http://dx.doi.org/10.1109/TSMCB.2009.2035099"
}