This study proposes a method for qualitatively evaluating and designing human-like driver models for autonomous vehicles. While most existing research on human-likeness has been focused on quantitative evaluation, it is crucial to consider qualitative measures to accurately capture human perception. To this end, we conducted surveys utilizing both video study and human experience-based study. The findings of this research can significantly contribute to the development of naturalistic and human-like driver models for autonomous vehicles, enabling them to safely and efficiently coexist with human-driven vehicles in diverse driving scenarios.

翻译：本研究提出了一种用于定性评估和设计自动驾驶车辆人类相似驾驶模型的方法。尽管现有关于人类相似性的研究大多集中于定量评估，但为了准确捕捉人类感知，考虑定性指标至关重要。为此，我们结合视频研究与基于人类体验的研究进行了问卷调查。本研究的发现将显著促进自动驾驶车辆自然且具有人类相似性的驾驶模型的开发，使其能够在各种驾驶场景中与人类驾驶车辆安全高效地共存。