Determining Natural Pathway for Side-by-Side Robotic Wheelchair in Passing Pedestrian Flows Using Dynamic Density

Abstract Side-by-side is the preferred mode of walking for pairs compared to Leader-Follower mode in which one follows the other. Yet, in passing, this walking mode tends to occupy more space on the pathway and reduces the travel space of pedestrians in the opposite direction. Therefore, humans often intuitively consider solutions to optimize the balance between side-by-side walking mode and moving space for others in passing. This is also a problem that designers of side-by-side robotic wheelchairs often have to solve. This paper proposes a novel model to determine natural navigation pathways for side-by-side robotic wheelchairs to pass multiple pedestrians walking in the opposite directions, mimicking human passing behaviors by taking into account the habit of moving with the flow and density in moving (called dynamic density). Based on an experimental observation and data collection, the model was developed and then validated by comparing the pathways generated by the model and the natural moving plans of the pairs in the same situations in a corridor. The simulation results show that they are highly similar.