  Interacting with pedestrians understandably and efficiently is one of the
toughest challenges faced by autonomous vehicles (AVs) due to the limitations
of current algorithms and external human-machine interfaces (eHMIs). In this
paper, we design eHMIs based on gestures inspired by the most popular method of
interaction between pedestrians and human drivers. Eight common gestures were
selected to convey AVs' yielding or non-yielding intentions at uncontrolled
crosswalks from previous literature. Through a VR experiment (N1 = 31) and a
following online survey (N2 = 394), we discovered significant differences in
the usability of gesture-based eHMIs compared to current eHMIs. Good
gesture-based eHMIs increase the efficiency of pedestrian-AV interaction while
ensuring safety. Poor gestures, however, cause misinterpretation. The
underlying reasons were explored: ambiguity regarding the recipient of the
signal and whether the gestures are precise, polite, and familiar to
pedestrians. Based on this empirical evidence, we discuss potential
opportunities and provide valuable insights into developing comprehensible
gesture-based eHMIs in the future to support better interaction between AVs and
other road users.
