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Proceedings Paper

Incremental learning in trust-based vehicle control
Author(s): Robert E. Karlsen; Dariusz G. Mikulski
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Paper Abstract

In many multi-agent teams, entities fully trust their teammates and the information that they provide. But we know that this can be a false assumption in many cases, which can lead to sub-optimal performance of the team. In this paper, we build off of prior work in developing a simple model of estimating and responding to different levels of trust between team members. We have chosen to use a vehicle convoy application to generate data and test the operation of the trust estimation algorithm and its evolution. We build on prior work, where a cruise control algorithm to maintain following distance was implemented, as were algorithms to adjust follow distance based on trust in the leader and the capability for a lead vehicle to “look back” and adjust its speed based on the follow distance of the vehicle behind. In this paper we introduce a mechanism, based on trust, which negotiates between two follow behaviors, either follow the vehicle ahead or drive towards a set of fixed waypoints. We also add a nonlinear relationship between trust and follow distance to provide a knob to adjust convoy performance and the paper shows that it does adjust performance, somewhat as expected.

Paper Details

Date Published: 13 May 2016
PDF: 11 pages
Proc. SPIE 9837, Unmanned Systems Technology XVIII, 983704 (13 May 2016); doi: 10.1117/12.2223168
Show Author Affiliations
Robert E. Karlsen, U.S. Army Tank Automotive Research, Development and Engineering Ctr. (United States)
Dariusz G. Mikulski, U.S. Army Tank Automotive Research, Development and Engineering Ctr. (United States)

Published in SPIE Proceedings Vol. 9837:
Unmanned Systems Technology XVIII
Robert E. Karlsen; Douglas W. Gage; Charles M. Shoemaker; Grant R. Gerhart, Editor(s)

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