Pedestrians base their street-crossing decisions on vehicle-centric as well as driver-centric cues. In the future, however, drivers of autonomous vehicles will be preoccupied with non-driving related activities and will thus be unable to provide pedestrians with relevant communicative cues. External human–machine interfaces (eHMIs) hold promise for filling the expected communication gap by providing information about a vehicle’s situational awareness and intention. In this paper, we present an eHMI concept that employs a virtual human character (VHC) to communicate pedestrian acknowledgement and vehicle intention (non-yielding; cruising; yielding). Pedestrian acknowledgement is communicated via gaze direction while vehicle intention is communicated via facial expression. The effectiveness of the proposed anthropomorphic eHMI concept was evaluated in the context of a monitor-based laboratory experiment where the participants performed a crossing intention task (self-paced, two-alternative forced choice) and their accuracy in making appropriate street-crossing decisions was measured. In each trial, they were first presented with a 3D animated sequence of a VHC (male; female) that either looked directly at them or clearly to their right while producing either an emotional (smile; angry expression; surprised expression), a conversational (nod; head shake), or a neutral (neutral expression; cheek puff) facial expression. Then, the participants were asked to imagine they were pedestrians intending to cross a one-way street at a random uncontrolled location when they saw an autonomous vehicle equipped with the eHMI approaching from the right and indicate via mouse click whether they would cross the street in front of the oncoming vehicle or not. An implementation of the proposed concept where non-yielding intention is communicated via the VHC producing either an angry expression, a surprised expression, or a head shake; cruising intention is communicated via the VHC puffing its cheeks; and yielding intention is communicated via the VHC nodding, was shown to be highly effective in ensuring the safety of a single pedestrian or even two co-located pedestrians without compromising traffic flow in either case. The implications for the development of intuitive, culture-transcending eHMIs that can support multiple pedestrians in parallel are discussed.