HD-GEN: A High-Performance Software System for Human Mobility Data Generation Based on Patterns of Life
Hossein Amiri, Joon-Seok Kim, Hamdi Kavak, Andrew Crooks, Dieter Pfoser, Carola Wenk, Andreas Z\"ufle

TL;DR
HD-GEN is a comprehensive software system that generates realistic human mobility datasets by combining empirical data with pattern-based simulations, calibrated and processed for various analytical applications.
Contribution
It introduces an integrated pipeline that generates, calibrates, processes, and visualizes large-scale human mobility data with high realism and flexibility.
Findings
Produces diverse, geographically grounded mobility logs
Calibrates simulation parameters to real-world data
Provides structured datasets and visual analytics tools
Abstract
Understanding individual-level human mobility is critical for a wide range of applications. As such, real-world trajectory datasets provide valuable insights into actual movement behaviors and patterns of life but are often constrained by data sparsity and participant bias. Synthetic data, by contrast, offers scalability and flexibility but frequently lacks realism. To address this gap, we introduce a comprehensive software pipeline for, generating, calibrating, processing, and visualizing large-scale individual-level human mobility datasets that combine the realism of empirical data with the control and extensibility of Patterns-of-Life simulations. Our system consists of four integrated components. (1) a data generation engine which constructs geographically grounded simulations using OpenStreetMap data to produce diverse mobility logs. (2) a genetic algorithm-based calibration module…
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Taxonomy
TopicsHuman Mobility and Location-Based Analysis · Data Visualization and Analytics · Data Management and Algorithms
