Identifying factors that contribute to collision avoidance behaviours while walking in a natural environment.

ABSTRACT: Busy walking paths, like in a park, city centre, or shopping mall, frequently necessitate collision avoidance behaviour. Lab-based research has shown how different situation- and person-specific factors, typically studied independently, affect avoidance behaviour. What happens in the real world is unclear. Thus, we filmed unscripted pedestrian walking behaviours on a busy urban path. We leveraged deep learning algorithms to identify and extract pedestrian walking trajectories and had unbiased raters characterize situations where two pedestrians approached each other from opposite ends. We found that smaller medial-lateral distance between approaching pedestrians and smaller crowd size predicted an increased likelihood of a subsequent path deviation. Furthermore, we found that whether a ped

SUBMITTER: Nikmanesh M 

PROVIDER: S-EPMC11775279 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature