We developed a motion control algorithm for a social mobile robot to intuitively convey its intent via social cues to pass through aisles and avoid misunderstanding in passing interactions with people, which frequently occur when a robot navigates in narrow shared environments. Inspired by observations of human behavior, the proposed algorithm estimates the extent to which a person understands the robot's intent on the basis of the person's reactions to the oncoming robot and provides the robot with corresponding motion strategies for effective passing interactions. We implemented the proposed algorithm onto an omni-directional humanoid robot and conducted a field study over six days in a store with 75 cm wide narrow aisles. The resulting behaviors of 50 customers demonstrated that our proposed method provided people with a clearer understanding of the robot's intent in passing interactions, and thus the robot had more opportunity (73.1%) to pass through aisles compared to 16.7% if the robot moved and then waited for people to make space.