This paper analyzes honks directed at autonomous vehicles (AVs) by other drivers. As honks often mark problems, this focus allows us to better understand the challenges that AVs face in real traffic. Performing a sequential video analysis of 63 honk incidents uploaded by Tesla beta testers on YouTube, we identify how problematic situations emerge as honkable Traffic Gestalts. We identify four types of situated problems with AV driving performance marked by other drivers’ honks: they may wait too long, steer inconsistently, stop instead of going, and go too fast. We further show how a honk may be understandable as a warning, a nudge or a reprimand. Our work suggests designing honks for AVs to focus on relevant contexts, supported by developing bidirectional interfaces and audio analysis methods that consider the interplay of auditory and visual information in traffic.