Development of the Pedestrian Awareness model for mobile robots^*

Abstract

Autonomous mobile robots are now being perceived as natural objects in real environments such as warehouses or restaurants. Naturally, These robots must consider the indeterminate behaviors of people, especially those unaware of their surroundings, such as those texting while walking (awareness). Although the risk of nonawareness has been studied extensively, much less work has been done on developing the pedestrian awareness model for an autonomous mobile robot. This study uses three factors: viewing angle, distance, and updating cycle to replicate the pedestrian awareness model mathematically. We collect data from five participants with high and low-workload texting tasks to identify their parameters. In this data collection, one pedestrian is walking freely in a $6-\mathrm{m}^{2}$ room with three walking experimenters. Meanwhile, they carry out a task that requires repeating a given sentence, and gazing information and head position are measured. In consequence, the distance probability of pedestrian awareness can be approximated by the sigmoid. Other parameters are estimated by the time ratio of awareness time to the overall time from the gazing information. Due to the difficulty of producing the generic parameters, we verified the proposed method using the calculated parameters of each participant. The simulation evaluation result indicates that our model leads to fewer errors than the simple social force model by comparing it with the collected walking trajectories. The result indicates that the proposed model could reproduce nonawareness pedestrians with higher accuracy, and our proposed model contributes to the mobile robot and the more realistic pedestrian simulation.