Investigating pedestrian stepping characteristics via intrinsic trajectory

Abstract

Investigating pedestrian stepping is essential for pedestrian dynamics research, aiding in understanding pedestrian behavior and crowd modeling. However, how to calculate the basic step metrics is still controversial, and the differences between straight walking and turning steps are often overlooked in past studies. In this work, we proposed the trajectory-based measurement to more accurately calculate the step metrics and further analyze the differences between the straight walking and turning steps. The trajectory-based measurement takes the intrinsic trajectory of the pedestrian as the reference frame to guide a more universal measurement for stepping characteristics. By applying the proposed trajectory-based measurement to revisit the dataset of a single-file experiment, we identify differences between the straight walking step and the turning step from multiple perspectives. The results show that when density is low, straight walking steps exhibit larger step velocity and length, whereas turning steps display more unbalanced lateral motion. As density increases, both types of steps demonstrate greater forward motion imbalance, while pedestrians prefer to take the step on the outer side of the turn to propel their forward motion when taking turning steps. These findings deepen our understanding of pedestrian stepping behavior and provide valuable insights for future studies of pedestrian dynamics.