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Study on Korean Variable Message Format Construction for Battlefield Visualization (전장가시화를 위한 한국형 지상전술데이터링크 구축 연구)

  • Kim, Seung-Chun;Lee, Hyung-Keun
    • Journal of IKEEE
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    • v.15 no.1
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    • pp.104-112
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    • 2011
  • During the ground operation of Korean army, the voice message is mainly used for exchanging informations related to the surveillance and reconnaissance, command and control, and precision strike. However, in order to the battlefield visualization among fighting powers participating in the ground force operation, automatic situational awareness and variable message format (VMF) for command and control are required. For securing core technologies necessary for the battlefield visualization, message standard and message handler are established through several applied researches. Besides, the VMF for equipping a weapon system is in development. In this paper, a study on the Korean variable message format (KVMF), where interoperability of integrated battle management system (BMS) is guaranteed due to performing joint, ground, and combined operations so that the situation awareness and strike system can be automated in almost real time, is presented. From the modeling and simulation (M&S) results of the message processor, delay time is varied in accordance with the number of nodes in unit platoon network, message length, and generation interval of routine messages. Therefore, it is shown that the system performance can be optimized by establishing proper network protocol for each situation.

A new approach on Traffic Flow model using Random Trajectory Theory (확률경로 기반의 교통류 분석 방법론)

  • PARK, Young Wook
    • Journal of Korean Society of Transportation
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    • v.20 no.5
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    • pp.67-79
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    • 2002
  • In this paper, observed trajectories of a vehicle platoon are viewed as one realization of a finite sequence of random trajectories. In this point of view, we develop novel and mathematically rigorous concept of traffic flow variables such as local traffic density, instantaneous traffic flow, and velocity field and investigate their nature on a general probability space of a sequence of random trajectories which represent vehicle trajectories. We present a simple model of random trajectories as an illustrative example and, derive the values of traffic flow variables based on the new definitions in this model. In particular, we construct the model for the sequence of random vehicle trajectories with a system of stochastic differential equations. Each equation of the system nay represent microscopic random maneuvering behavior of each vehicle with properly designed drift coefficient functions and diffusion coefficient functions. The system of stochastic differential equations nay generate a well-defined probability space of a sequence of random vehicle trajectories. We derive the partial differential equation for the expected cumulative plot with appropriate initial conditions. By solving the equation with numerical methods, we obtain the values of expected cumulative plot, local traffic density, and instantaneous traffic flow. In addition, we derive the partial differential equation for the expected travel time to a certain location with appropriate initial and/or boundary conditions, which is solvable numerically. We apply this model to a case of single vehicle trajectory.

AR based Field Training System Algorithm for Small Units (증강현실 기반의 소부대 야외 전술훈련체계 알고리즘)

  • Park, Sangjun;Kim, Jee Won;Kim, Kyoung Min;Kim, Hoedong
    • Convergence Security Journal
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    • v.18 no.4
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    • pp.81-87
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    • 2018
  • Military training is being carried out to win the combats through the quick and accurate response exercise for changeable engagement situations on battle fields. However, practically, it is really difficult to do actual fight training. Even though ROK Army is doing effort for practical training in KCTC(Korea army advanced Combat Training Center) supplying such as MILES equipments but a single platoon is able to use KCTC facilities or MILES equipments only 10 days a year. In order to find solution on this problem many researches suggesting AR or VR technology are still on the way. Nevertheless these are not fully covered the training done in the real field. In this regard, this paper proposes how the AR technology algorithm to apply on small units during field training exercise.

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Monte Carlo Simulation based Optimal Aiming Point Computation Against Multiple Soft Targets on Ground (몬테칼로 시뮬레이션 기반의 다수 지상 연성표적에 대한 최적 조준점 산출)

  • Kim, Jong-Hwan;Ahn, Nam-Su
    • Journal of the Korea Society for Simulation
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    • v.29 no.1
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    • pp.47-55
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    • 2020
  • This paper presents a real-time autonomous computation of shot numbers and aiming points against multiple soft targets on grounds by applying an unsupervised learning, k-mean clustering and Monte carlo simulation. For this computation, a 100 × 200 square meters size of virtual battlefield is created where an augmented enemy infantry platoon unit attacks, defences, and is scatted, and a virtual weapon with a lethal range of 15m is modeled. In order to determine damage types of the enemy unit: no damage, light wound, heavy wound and death, Monte carlo simulation is performed to apply the Carlton damage function for the damage effect of the soft targets. In addition, in order to achieve the damage effectiveness of the enemy units in line with the commander's intention, the optimal shot numbers and aiming point locations are calculated in less than 0.4 seconds by applying the k-mean clustering and repetitive Monte carlo simulation. It is hoped that this study will help to develop a system that reduces the decision time for 'detection-decision-shoot' process in battalion-scaled combat units operating Dronebot combat system.

Development of Two-Lane Car-Following Model to Generate More Realistic Headway Behavior (보다 현실적인 차두시간 행태 구현을 위한 2차로 차량추종모형 개발)

  • Yoon, Byoung Jo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.33 no.5
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    • pp.1999-2007
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    • 2013
  • The key characteristics of two-lane-and-two-way traffic flow are platoon and overtaking caused by low-speed vehicle such as truck. In order to develop two-way traffic flow model comprised of CF(car-following) and overtaking model, it is essential to develop a car-following model which is suitable to two-way traffic flow. Short distance between vehicles is caused when a high-speed vehicle tailgates and overtakes foregoing low-speed vehicle on two-way road system. And a vehicle following low-speed vehicle decides to overtake the front low-speed vehicle using suitable space within the headway distribution of opposite traffic flow. For this reason, a two-way CF model should describes not only running within short gap but also headway distribution. Additionally considering domestic two-way-road size, there is a on-going need for large-network simulation, but there are few studies for two-way CF model. In this paper, a two-way CA model is developed, which explains two-way CF behavior more realistic and can be applied for large road network. The experimental results show that the developed model mimics stop-and-go phenomenon, one of features of congested traffic flow, and efficiently generates the distribution of headway. When the CF model is integrated with overtaking model, it is, therefore, expected that two-way traffic flow can be explained more realistically than before.