Recent technological advances have introduced autonomous mobile robots into public areas that were previously occupied only by pedestrians. When pedestrians and mobile robots coexist, the collision avoidance algorithm in which the robots can reach their goals without causing collisions or significant delays is important. One approach is to incorporate human sensation into the avoidance algorithm, and the braking index representing human braking sensation in two-dimensional environments was developed. The goal of this study was to verify whether the collision avoidance algorithm based on the braking index could work efficiently in a congested environment using agent simulations. The results showed that agents using the avoidance algorithm with the braking index achieved smoother and safer movement than those without it in a congested environment. Additionally, we found a traditional traffic density-flow relationship between congestion and movement smoothness. This finding implies that this relationship could be applied to two-dimensional environments, such as shopping malls or airports.

Smooth and safe interactions between pedestrians and Autonomous Mobile Robots (AMRs) are crucial for integrating robotic systems into shared environments. Previous studies on external Human-Machine Interfaces (eHMIs) often employed static information presentation, neglecting dynamic interaction contexts. This study investigates the effectiveness of gaze-based nudge-intuitive and unconscious communication via gaze behavior—in facilitating pedestrian role selection (leader or follower) during perpendicular crossing interactions with AMRs. Virtual reality (VR) experiments using Unity and Cybershoes are conducted to evaluate two gaze patterns generated by the AMR: ‘Leader’s gaze’, a brief gaze directed toward pedestrians in the early stages of interactions, and ‘Follower’s gaze’, a gaze keeping track of pedestrians throughout the interaction until crossing completion. The impact of gaze timing (Early/Late) and initial positional relationships between pedestrians and AMRs (initial ∆TTCP) are systematically analyzed. The results indicate that gaze nudging significantly enhances pedestrians’ subjective ratings of safety, smoothness, and understanding of the robot’s intention compared to no-gaze conditions. Leader’s gaze effectively encourages pedestrians to adopt the follower role under conditions favoring AMR priority (small or negative ∆TTCP), whereas Follower’s gaze promotes pedestrians to adopt the leader role under conditions naturally favoring pedestrian priority (larger ∆TTCP). Additionally, the effectiveness of gaze nudging strongly depends on interaction timing, with early-stage gaze presentations exhibiting greater influence. These findings confirm the potential of gaze-based nudging as a non-intrusive, context-sensitive strategy for pedestrian-AMR interactions, emphasizing the importance of precisely timed gaze presentations for facilitating pedestrians’ natural and intuitive role selection.

This study examines the effects of self and other's intentions on their moving performance in crossing interactions with multiple agents. An experimental task paradigm was developed to verify self and other's effects simultaneously. Different intentions were assigned to self and other in the 2-person crossing situation and to the minority and majority in the 4-person crossing situation. Further, performance was assessed based on completion time, amount of operations, and interruptions. The results show that the effects of self-intention on self-performance were generally found, but the minority's intention does not affect its interruption. For completion time and operation, the effect of other's intention decreased in the order of the self in the 2-person crossing situation, minority, and majority in the 4-person crossing situation. Noteworthy, for the interruption, the other's intention affected the majority's interruption, but it did not affect the minority's interruption. These findings emphasize the significance of simultaneously considering self and other's intentions simultaneously when analyzing crossing interactions in shared space.