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
By: Saleh Albeaik, Mohamad Alrished, Faisal Alsallum
Potential Business Impact:
Helps robots understand how people walk together.
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.
Similar Papers
Modellierung und Simulation der Dynamik von Fussgängerströmen
Multiagent Systems
Helps design better walking paths for crowds.
Preliminary Study on Space Utilization and Emergent Behaviors of Group vs. Single Pedestrians in Real-World Trajectories
CV and Pattern Recognition
Tells if people walk alone or in groups.
Emergent Crowds Dynamics from Language-Driven Multi-Agent Interactions
Artificial Intelligence
Makes computer crowds talk and move realistically.