Trajectory simulations and predictions
This section is inspired by Instruction-Tuning Llama-3-8B Excels in City-Scale Mobility Prediction by Tang et al. (2024). We will explore the essential background on the challenges of human mobility prediction, the paper’s key contributions, and how these ideas can be translated into practical Python implementations.
Human mobility prediction focuses on forecasting where and when individuals (or groups) will travel, and it plays a critical role in an expanding set of domains, including the following:
- Disaster response, for predicting the paths of wildfires, population movements during crises, or the impacts of earthquakes
- Urban planning, for modeling short- and long-term mobility patterns to help city planners optimize public transport and infrastructure
- Epidemic forecasting, for simulating and predicting the spread of infectious diseases in a region
In our case, we will first apply mobility prediction...
