The Patterns of Life Human Mobility Simulation

Sumamry:

The Patterns of Life (POL) Simulation demonstrated in this paper is a scalable tool designed to generate realistic human mobility data by simulating individuals’ daily activities and interactions based on social and behavioral theories. This simulation overcomes the limitations of existing datasets like GeoLife, offering customizable, region-specific data with potential applications in urban planning, epidemiology, and traffic analysis.

Methodology:

The POL Simulation uses an agent-based approach grounded in Maslow’s Hierarchy of Needs and the Theory of Planned Behavior to drive agent decisions, such as going to work, socializing, or seeking food and shelter. Improvements to the simulation include options to run it with or without a graphical interface and the ability to customize regions using OpenStreetMap data.

Results:

The simulation enables efficient large-scale data generation, with significant improvements in speed and efficiency achieved through minimal modifications to agent behavior logic and the use of parallelization accros multiple simulation instances. The generated datasets are extensive, reaching trillions of trajectory points and billions of social connections.

Conclusion:

The POL Simulation provides a versatile, scalable framework for realistic human mobility data generation. It is accessible on GitHub, allowing researchers to customize simulations for various applications and regions. The tool addresses the data scarcity challenge in human mobility studies, enabling enriched data for research in social behavior, urban mobility, and public health.

Full Paper: