Human Factors Modeling fromWearable Sensed Data forEvacuation based Simulation Scenarios

Lucas Paletta a, Verena Wagner b, K. Wolfgang Kallus b, Helmut Schrom-Feiertag c
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引用次数: 1

Abstract

The design and the evaluation of evacuation systems are crucial to guarantee successful responses after an incident. Recent results are presented that target to significantly improve evacuation simulation by parameterizing the human agents’ behavior with information on human factors about stress, perception and decision making. In particular, the single person’s behavior in its specific situational context is investigated in the frame of its embodied decision making. For this purpose, users were equipped with wearable sensors that capture information about the environment, the psychophysiological status of the user, and its viewing (eye tracking glasses) and motion behavior. The studies take place during regularly performed evacuation exercises of large business buildings. From the correlation between the multisensory perceptual and psychophysiological data on the one hand, and the automatically sensed and interpreted situational context on the other hand, we will extract a rule base with a set of logical “pre-condition – action” pairs that will parameterize the crowd simulation model.
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基于可穿戴传感数据预测的仿真场景人为因素建模
疏散系统的设计和评估对于确保事故后的成功应对至关重要。最近的研究结果表明,通过利用人的压力、感知和决策等因素的信息来参数化人类智能体的行为,可以显著提高疏散模拟的质量。具体而言,在具体情境下的个体行为是在具体决策的框架下进行研究的。为此,用户配备了可穿戴传感器,用于捕获有关环境、用户心理生理状态、其观看(眼动追踪眼镜)和运动行为的信息。这些研究是在大型商业大楼定期进行的疏散演习中进行的。从多感官感知和心理生理数据与自动感知和解释的情景上下文之间的相关性中,我们将提取一个包含一组逻辑“先决条件-行动”对的规则库,并将其参数化人群模拟模型。
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