A discrete event simulation model for unstructured supervisory control of unmanned vehicles

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2010.

Bibliographic Details
Main Author: McDonald, Anthony D. (Anthony Douglas)
Other Authors: Mary L. Cummings.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2010
Subjects:
Online Access:http://hdl.handle.net/1721.1/59947
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author McDonald, Anthony D. (Anthony Douglas)
author2 Mary L. Cummings.
author_facet Mary L. Cummings.
McDonald, Anthony D. (Anthony Douglas)
author_sort McDonald, Anthony D. (Anthony Douglas)
collection MIT
description Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2010.
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spelling mit-1721.1/599472019-04-12T11:36:28Z A discrete event simulation model for unstructured supervisory control of unmanned vehicles McDonald, Anthony D. (Anthony Douglas) Mary L. Cummings. Massachusetts Institute of Technology. Dept. of Mechanical Engineering. Massachusetts Institute of Technology. Dept. of Mechanical Engineering. Mechanical Engineering. Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2010. Cataloged from PDF version of thesis. Includes bibliographical references (p. 33). Most current Unmanned Vehicle (UV) systems consist of teams of operators controlling a single UV. Technological advances will likely lead to the inversion of this ratio, and automation of low level tasking. These advances will also lead to a growth in UV use in large-scale applications such as urban search and rescue, which will require the use of both teams of operators and teams of UVs. This growth will in turn require research and development in the area of team supervisory control of multiple UVs. Human-in-the- loop experimentation is often used during this research but can be time consuming and expensive. The time and cost of experimentation can often be drastically reduced by using predictive models. However there is a lack of such models in the area of multiple-operator supervisory control of multiple- UVs. This problem is addressed in this thesis through the following method: First, current predictive models of human supervisory control of UVs are analyzed, and attributes of systems related to this modeling space are identified. Second, a queuing-based multiple-operator multiple-vehicle discrete event simulation model (MO-MUVDES) is developed which captures these attributes, including the ability to predict performance in situations with low observable exogenous event arrivals. MO-MUVDES also incorporates traditional system variables such as level of vehicle autonomy, vehicle and operator team structure, and operator switching strategy. The accuracy and robustness of the MO-MUVDES model were measured by a two-stage validation process using data from a human-in-the-loop supervisory control experiment, and a Monte Carlo simulation. The first stage of the validation process used data from the experiment as input for the MOMUVDES model which was then used to generate predictions of operator performance. In the second stage of validation, a sensitivity analysis was performed on the MO-MUVDES model. This validation process achieved confidence in the model's ability to predict operator performance and a measurement of the robustness of the model under varying input conditions. Additionally, the process indicated that discrete event simulation is an effective technique for modeling team supervisory control of UVs in a situation where exogenous event arrivals are not clearly observable. As a result, the MO-MUVDES model could be used to reduce development time for systems within its modeled space. by Anthony D. McDonald. S.B. 2010-11-08T17:50:17Z 2010-11-08T17:50:17Z 2010 2010 Thesis http://hdl.handle.net/1721.1/59947 676921452 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 37 p. application/pdf Massachusetts Institute of Technology
spellingShingle Mechanical Engineering.
McDonald, Anthony D. (Anthony Douglas)
A discrete event simulation model for unstructured supervisory control of unmanned vehicles
title A discrete event simulation model for unstructured supervisory control of unmanned vehicles
title_full A discrete event simulation model for unstructured supervisory control of unmanned vehicles
title_fullStr A discrete event simulation model for unstructured supervisory control of unmanned vehicles
title_full_unstemmed A discrete event simulation model for unstructured supervisory control of unmanned vehicles
title_short A discrete event simulation model for unstructured supervisory control of unmanned vehicles
title_sort discrete event simulation model for unstructured supervisory control of unmanned vehicles
topic Mechanical Engineering.
url http://hdl.handle.net/1721.1/59947
work_keys_str_mv AT mcdonaldanthonydanthonydouglas adiscreteeventsimulationmodelforunstructuredsupervisorycontrolofunmannedvehicles
AT mcdonaldanthonydanthonydouglas discreteeventsimulationmodelforunstructuredsupervisorycontrolofunmannedvehicles