Agent-based Simulation Modeling to Measure the Effectiveness of UGV with Communication Repeater

CHONGMAN, KIM and JAEYEONG, LEE and SUNWOO, SHIN (2017) Agent-based Simulation Modeling to Measure the Effectiveness of UGV with Communication Repeater. In: Sixth International Conference on Advances in Social Science, Management and Human Behaviour - SMHB 2017, 09-10 December, 2017, Rome, Italy.

20180215_113926.pdf - Published Version

Download (1MB) | Preview
Official URL:


Since the future warfare is getting more network centric rather than platform centric, its environment is getting more difficult and complex to estimate future system’s operational effectiveness. Therefore it is challenging task to develop a methodology or approach to show the efficiency during a ground battle of the network centric warfare. In order to describe the reality of network environment, we are considering communication error effects depending upon terrain condition near each platform. The terrain condition is defined based on a small cell and its altitude in each cell. In this paper, we propose a simulation framework for how to measure the operational effectiveness of unmanned ground vehicle with considering communication repeater to compensate whenever communication error occurs in a ground battle scenario. The framework is processed with following three phases. At first, we consider all relational factors for input and output variables in communication network environment of all platforms. Secondly, build a simulation model and select a measure of effectiveness based on purpose of the system performance. Thirdly, execute a simulation model and produce MOE do the output analysis. We compared the results and showed how the effectiveness varies depending upon different scenario.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Operational effectiveness, Modeling & Simulation, Communication error, Communication repeater
Depositing User: Mr. John Steve
Date Deposited: 10 Mar 2019 09:20
Last Modified: 10 Mar 2019 09:20

Actions (login required)

View Item View Item