Recent research has examined the possibility of using robots to guide evacuees to safe exits during emergencies. Yet, there are many factors that can impact a person's decision to follow a robot. Being able to model how an evacuee follows an emergency robot guide could be crucial for designing robots that effectively guide evacuees during an emergency. This paper presents a method for developing realistic and predictive human evacuee models from physical human evacuation experiments. The paper analyzes the behavior of 14 human subjects during physical robot-guided evacuation. We then use the video data to create evacuee motion models that predict the person's future positions during the emergency. Finally, we validate the resulting models by running a k-fold cross-validation on the data collected during physical human subject experiments. We also present performance results of the model using data from a similar simulated emergency evacuation experiment demonstrating that these models can serve as a tool to predict evacuee behavior in novel evacuation simulations.

翻译：近期研究探讨了在紧急情况下利用机器人引导疏散者安全前往出口的可能性。然而，影响个体跟随机器人决策的因素众多。能够建模疏散者如何跟随紧急机器人引导者，对于设计在紧急情况下有效引导疏散者的机器人至关重要。本文提出了一种基于实体人类疏散实验开发逼真且可预测的人类疏散者模型的方法。论文分析了14名人类受试者在物理机器人引导疏散中的行为。随后，我们利用视频数据创建了疏散者运动模型，用于预测个体在紧急情况下的未来位置。最后，我们通过对实体人类受试者实验中收集的数据进行k折交叉验证，验证了所得模型的有效性。我们还展示了模型在类似模拟紧急疏散实验数据上的性能结果，表明这些模型可作为预测新型疏散模拟中疏散者行为的工具。