Week 8
Mobility models for urban behavior
This week, we will start modeling human behavior in cities, in particular, individual and aggregated mobility. Those models not only allow us to describe human behavior with more detail, but also to predict it using an integrative modelling framework
We have two practicals this week:
- One to analyze your own mobility data and privacy-preserved enhanced mobility data from Cuebiq of 10000 anonymized individuals in the city of Boston and use individual models to predict their behavior.
- The second one to analyze aggregated mobility flows during COVID19 to fit gravity and radiation models.
Prepare
📖 Read some papers about models for human mobility in urban areas:
- Human mobility: Models and Applications by Barbosa [1]
- Modelling the scaling properties of human mobility by Song et al @
- The scales of human mobility by Alessandretti et al [2]
- The universal visitation law of human mobility by Simini et al [3]
Participate
Perform
⌨️ Lab 8-1 - Individual mobility models
⌨️ Lab 8-2 - Population Mobility Models
Back to course schedule ⏎
References
[1]
H. Barbosa et al., “Human mobility: Models and applications,” Physics Reports, vol. 734, pp. 1–74, Mar. 2018, doi: 10.1016/j.physrep.2018.01.001.
[2]
L. Alessandretti, U. Aslak, and S. Lehmann, “The scales of human mobility,” Nature, vol. 587, no. 7834, pp. 402–407, Nov. 2020, doi: 10.1038/s41586-020-2909-1.
[3]
F. Simini, M. C. González, A. Maritan, and A.-L. Barabási, “A universal model for mobility and migration patterns,” Nature, vol. 484, no. 7392, pp. 96–100, Apr. 2012, doi: 10.1038/nature10856.