The analysis of performance gains arising from cueing in cooperative search
systems with autonomous vehicles has been studied using Continuous Time Markov
Chains; where the search time distributions are assumed to follow the exponential
distributions. This work proposes the use of Petri Nets to model and analyze these
systems. The Petri Net model considers two types of autonomous vehicles: a search-only
vehicle and n search-engage vehicles. Specific performance metrics are defined to
measure system’s performance. Through simulation, it is shown that the search time with
stationary targets and cues that provide exact target location follows a triangular
distribution. A methodology for approximating general distributions and incorporating
them into the Petri Net model for performance analysis is presented.
| Identifer | oai:union.ndltd.org:USF/oai:scholarcommons.usf.edu:etd-4839 |
| Date | 08 July 2010 |
| Creators | Portilla, Carlos A. |
| Publisher | Scholar Commons |
| Source Sets | University of South Flordia |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate Theses and Dissertations |
| Rights | default |
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