Browsing by Author "Chou, Yi-Hung"

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A Framework for Simulating Agent-Based Cooperative Tasks in Crowd Simulation
(2018-01-01)
Wong, Sai-Keung
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Chou, Yi-Hung
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Yang, Hsiang-Yu
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資訊工程學系
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Department of Computer Science
This paper presents a novel agent-based approach to simulate cooperative tasks in crowd simulation. Our framework consists of two kinds of agents: pedestrians and workers. A cooperative task requires two or more workers to simultaneously perform actions on objects. The workers should cooperate with each other to finish tasks. This framework considers several basic cooperative behaviors including pushing obstacles away from blocked exits, lifting cargos and carrying them to a destination, and pulling objects using ropes. A complex task can be decomposed into several simple tasks and the simple tasks are finished either in a sequential or parallel order. Our framework also simulates crowd behaviors such as workers joining and leaving cooperative tasks, moving objects around obstacles, collision avoidance for agents, and way giving. We demonstrate examples for simulating different cooperative behaviors. Our framework can be applied to movies, crowd evacuation, narrative systems, task planning simulation, and games.
Directing virtual crowds based on dynamic adjustment of navigation fields
(2018-01-01)
Tsai, Tsung-Yu
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Wong, Sai-Keung
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Chou, Yi-Hung
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Lin, Guan-Wen
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交大名義發表
Navigation fields are a popular data structure for directing the movement of virtual crowds. However, the congestion problem may occur at the corners of objects in using a navigation field because the agents move quite closely to each other. The agents may congest at the corners even though there is room for the agents to move away from the congested regions. In this paper, we propose to place crowd monitors at the corners to collect the data such as the movement direction of crowds and crowd densities. Then the navigation field is adjusted dynamically so that the crowds are led to move away from the congested regions. We also propose a simple data structure for speeding up the collision detection process between agents and objects. Experimental results show that our approach successfully alleviates the congestion problem at the corners.