  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.
