Life-cycle Modeling and the Walking Behavior of the Pedestrian-Group as an Emergent Agent: With Empirical Data on the Cohesion of the Group Formation

TL;DR

This paper models pedestrian group behavior as an emergent agent using empirical data, revealing patterns of formation, transitions, and collective intentions to inform simulation and system design.

Contribution

It introduces a novel life-cycle model of pedestrian groups based on empirical observations, capturing formation states and behavioral transitions.

Findings

Identified recurring patterns in pedestrian group walking behavior.

Modeled transitions between independent and collective states.

Provided a framework for simulating group dynamics in engineering systems.

Abstract

This article investigates the pedestrian group as an emergent agent. The article explores empirical data to derive emergent agency and formation state spaces and outline recurring patterns of walking behavior. In this analysis, pedestrian trajectories extracted from surveillance videos are used along with manually annotated pedestrian group memberships. We conducted manual expert evaluation of observed groups, produced new manual annotations for relevant events pertaining to group behavior and extracted metrics relevant group formation. This information along with quantitative analysis was used to model the life-cycle and formation of the group agent. Those models give structure to expectations around walking behavior of groups; from pedestrian walking independently to the emergence of a collective intention where group members tended to maintain bounded distance between each other. Disturbances to this bounded distance often happened in association with changes in either their agency or their formation states. We summarized the patterns of behavior along with the sequences of state transitions into abstract patterns, which can aid in the development of more detailed group agents in simulation and in the design of engineering systems to interact with such groups.