• Journal of Korea Multimedia Society
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• v.24 no.5
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• pp.629-641
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• 2021

Crowd behavior simulations have been studied to further accelerated and refined by parallelism by inducing agent-interacting forces into the image field representing the forces of attraction and repulsion. However, it was difficult to consider rapidly changing environments such as fire situations in buildings because texture images must be generated in advance simulation starts and simulations can only be performed in 2D spaces. In this paper, we propose a crowd agent behavior simulation method based on agent's 3D affordance field for flexible agent behavior in variable geomorphological environments in 3D space. The proposed method generates 3D affordance field related to agents and sensors in 3D space and defines the agent behavior in 3D space for the crowd behavior simulation based on an image-inducing field to a 3D space. Experimental results verified that our method enables the development of large-scale crowd behavior simulations that are flexible to various fire evacuation situations in 3D virtual spaces.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.5
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• pp.136-145
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• 2004

In companion paper, the composition and structure of the traffic environment is derived. Rules to regulate agent behaviors and the frameworks to communicate between the agents are proposed. In this paper, the model of a driver agent which controls a vehicle agent is constructed. The driver agent is capable of having different driving styles. That is, each driver agent has individual behavior settings of the yielding index and the passing index. The yielding index can be defined as how often the agent yields in case of lane changes, and the passing index can be defined as how often the agent passes ahead. According to these indices, the agents overtake or make their lanes for other vehicles. Similarly, the vehicle agents can have various vehicle dynamic models. According to their dynamic characteristics, the vehicle agent shows its own behavior. The vehicle model of the vehicle agent contains the nonlinear subcomponents of engine, torque converter, automatic transmission, and wheels. The simulation has proceeded for an interrupted flow model. The result has shown that it is possible to express the characteristics of each vehicle and its driver in a traffic flow, and that the change of the traffic state is closely related with the distance and the signal delay between intersections. The system developed in this paper shows the effectiveness and the practical usefulness of the traffic simulation.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.354-356
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• 2003

The study of pedestrian behavior covers wide topics, including way finding, choice and decision make, as well as spatial cognition and environmental perception. To address the problem, simulation is now put forward as suitable technique and method for analyzing human spatial behavior. In the paper we present a development architecture for simulating tracking pedestrian in a distributed environment. We introduce and explore the potential of using mobile agent-enabled distributed implementation model as a tool for development and implementation of the simulation. Three kinds of mobile agents are designed for implementation of managing and querying data of pedestrian. Finally, simulation result of JR 10,000 passengers’ movement is developed and implemented as a case study.

• International Journal of Automotive Technology
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• v.7 no.2
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• pp.145-154
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• 2006

In the companion paper, the composition and structure of the MATDYMO (Multi-Agent for Traffic Simulation with Vehicle Dynamic Model) were proposed. MATDYMO consists of the road management system, the vehicle motion control system, the driver management system, and the integration control system. Among these systems, the road management system and the integration control system were discussed In the companion paper. In this paper, the vehicle motion control system and the driver management system are discussed. The driver management system constructs the driver agent capable of having different driving styles ranging from slow and careful driving to fast and aggressive driving through the yielding index and passing index. According to these indices, the agents pass or yield their lane for other vehicles; the driver management system constructs the vehicle agents capable of representing the physical vehicle itself. A vehicle agent shows its behavior according to its dynamic characteristics. The vehicle agent contains the nonlinear subcomponents of engine, torque converter, automatic transmission, and wheels. The simulation is conducted for an interrupted flow model and its results are verified by comparison with the results from a commercial software, TRANSYT-7F. The interrupted flow model simulation is implemented for three cases. The first case analyzes the agents' behaviors in the interrupted flow model and it confirms that the agent's behavior could characterize the diversity of human behavior and vehicle well through every rule and communication frameworks. The second case analyzes the traffic signals changed at different intervals and as the acceleration rate changed. The third case analyzes the effects of the traffic signals and traffic volume. The results of these analyses showed that the change of the traffic state was closely related with the vehicle acceleration rate, traffic volume, and the traffic signal interval between intersections. These simulations confirmed that MATDYMO can represent the real traffic condition of the interrupted flow model. At the current stage of development, MATDYMO shows great promise and has significant implications on future traffic state forecasting research.

• Journal of the Korea Society for Simulation
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• v.20 no.3
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• pp.111-117
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• 2011

This paper suggests the passenger model considered evacuation behavioral characteristics on the passenger ship fire using a rules-based agent technique. The existing evacuation simulation system was modeled only passenger speed. The speed-based model considered passenger's physical characteristics, so it couldn't consider evacuation behavioral characteristics. For solving this problem, we modeled the passenger model using a rule-based agent applied evacuation behavioral characteristics. The rule-based agent consists of knowledge base and inference engine. In knowledge base, we represented evacuation behavioral characteristics, and chose the examples of the evacuation behavioral characteristics to show various patterns of behavior. And we simulated in the IMO MSC/Circ.1238 example 8 and we proved the simulation results could represent variety patterns of human behavior.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.5
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• pp.125-135
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• 2004

The validity of simulation has been well-established for decades in areas such as computer and communication system. Recently, the technique has become entrenched in specific areas such as transportation and traffic forecasting. Several methods have been proposed for investigating complex traffic flows. However, the dynamics of vehicles and their driver's characteristics, even though it is known that they are important factors for any traffic flow analysis, have never been considered sufficiently. In this paper, the traffic simulation using a multi-agent approach with considering vehicle dynamics is proposed. The multi-agent system is constructed with the traffic environment and the agents of vehicle and driver. The traffic environment consists of multi-lane roads, nodes, virtual lanes, and signals. To ensure the fast calculation, the agents are performed on the based of the rules to regulate their behaviors. The communication frameworks are proposed for the agents to share the information of vehicles' velocity and position. The model of a driver agent which controls a vehicle agent is described in the companion paper. The vehicle model contains the nonlinear subcomponents of engine, torque converter, automatic transmission, and wheels. The simulation has proceeded for an interrupted and uninterrupted flow model. The result has shown that the driver agent performs human-like behavior ranging from slow and careful to fast and aggressive driving behavior, and that the change of the traffic state is closely related with the distance and the signal delay between intersections. The system developed shows the effectiveness and the practical usefulness of the traffic simulation.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1359-1363
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• 2009

The object of this research is to develop a simulation system for earthmoving operations in consideration of the impact of congestion in-between equipment and existing traffic flow around the site. The congestion in-between equipment and traffic flow affect work productivity. The conventional discrete event simulation, however, has limitations in simulating the flow of construction equipment. To consider the impact of congestion in-between equipment and existing traffic flow, in this paper, a multi-agent based simulation model that can realize characteristics of truck behavior more accurately to consider the impact of congestion was proposed. In this simulation model, multiple agents can identify environmental changes and adapt themselves to the new environment. This modeling approach is a better choice for this problem since it describes behavioral characteristics of each agent by sensing changes in dynamic surroundings. This study suggests a detailed system design of the multi-agent based simulation system.

• The Journal of Society for e-Business Studies
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• v.17 no.1
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• pp.91-110
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• 2012

Recently the effort of retailers improving the efficiency of store operations by using the information technology (IT) is increasing. Among them, the analysis of the shoppers' flow in retail stores is one of the critical tasks since it is an essential part in optimizing store layout and item grouping, and in developing the customized services specialized to shoppers' classification. Agent-Based Modeling and Simulation (ABMS) is one of the most promising methods which support analyzing the shoppers' flow. In this paper, we suggested a shopper's behavior model and developed an agent-based simulator for optimizing the operations of retail stores. In order to model the shoppers' behavior, we analyzed the behavioral characteristics of shoppers based on their shopping lists, suggesting BDI-based agent models of the shoppers' behavior. The shopping agent model were suggested, which has an additional mental state, the shopper's behavioral characteristic, as well as the original mental states of the BDI theory which has beliefs, desires and Intentions. The result of this study can be used in as a preliminary study for modeling and simulation of retail stores congestion and in the end the optimization of item grouping and store layout.

• Journal of KIISE
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• v.42 no.12
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• pp.1503-1521
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• 2015

Agent-based modeling and simulation (ABMS) is used to model of market and social phenomena by utilizing agents' fine-grained behaviors and interactions that cannot be implemented in a conventional simulation. However, ABMS represents irrational agents and hinders the achievement of individual or overall goals since ABMS is based on agent-based software, which follows the principle of rationality at the knowledge level [1]. This problem was solved in the agent-based software engineering (ABSE) field by using behavior laws for the social level [2]. However, they still do not propose the specific development methodology for how to develop the social level in a systematic way. Therefore, in order to propose agent-based modeling and simulation methods that reflect the behavior laws of social level characteristics, our study used the Tropos that can combine ABSE and social behavior laws for the presentation of concrete tasks and deliverables for each development step by step. In addition, the proposed method will be specified through experiments with specific application examples and case studies on the self-adaptive smart grid and the military domain system.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.12
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• pp.984-990
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• 2005

The aim of this paper is to investigate a control framework for mobile robots, operating in shared environment with humans. The Intelligent Space (iSpace) can sense the whole space and evaluate the situations in the space by distributing sensors. The mobile agents serve the inhabitants in the space utilizes the evaluated information by iSpace. The iSpace evaluates the situations in the space and learns the walking behavior of the inhabitants. The human intelligence manifests in the space as a behavior, as a response to the situation in the space. The iSpace learns the behavior and applies to mobile agent motion planning and control. This paper introduces the application of fuzzy-neural network to describe the obstacle avoidance behavior teamed from humans. Simulation results are introduced to demonstrate the efficiency of this method.