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Modeling individual human mobility patterns by travel
purpose
Maxime Lenormand
To cite this version:
Maxime Lenormand. Modeling individual human mobility patterns by travel purpose. Conference on Complex Systems, Sep 2016, Amsterdam, Netherlands. pp.25. �hal-02604647�
Maxime Lenormand | Irstea, France
19 September 2016
CCS 2016 | Amsterdam, Netherlands
Modeling individual human mobility patterns
by travel purpose
Juan Murillo Arias | BBVA, Spain Maxi San Miguel | IFISC, Spain
Brockmann et al. (2006) The scaling laws of human travel.
Nature 439, 462-465.
Continuous-Time Random Walks
Individual human mobility patterns
Gonzalez et al. (2008) Understanding individual human mobility patterns.Nature 453, 779-782. < rg (t) > (k m ) 1 10 100 0 1,000 2,000 3,000 4,000 t (h) RW LF rg≤ 3 km 20 <rg≤ 30 km rg> 100 km Users Models (h) Fpt (t) 0 24 48 72 96 120144 168192216 240 0 0.01 0.02 t (h) Users RW
Individual human mobility patterns
Song et al. (2010) Limits of predictability in human mobility.Science 327, 1018-1021. 52% 5% 6% 27% Time: t Time: t +Δt S= 4 S= 5 S= 4 Pnew= S¬ Pret= 1¬ Sρ¬γ γ ρ Δr f1 f2 f3 Πi=fi an Exploration Preferential return
Song et al. (2010) Modelling the scaling properties of human mobility
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INFOCOM 2008. an
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Is there a link between the amount of "energy" invested into a travel and the value attached to the purpose/objectif of this travel?
d
How to integrate the importance of trip destination into an individual human mobility model?
d
d
Model
Transaction • Customer ID • Business ID • Amount • TIme Customer • Customer ID • Gender • Age • Occupation • Marital Status • Study
• ZipCode (Lon/Lat)
Business • Business ID • Category • Coordinates • ZipCode (Lon/Lat) Customer • Customer ID • Country BBVA? No Yes
13 M of transactions made by 300,000 users in Barcelona in 2011
Results
Results
v< 50 v∈[50,75[ v∈[75,100[ v∈[100,200[ v∈[200,500[d (km)
Results
2.0 2.5 3.0 3.5 4.0 4.5 101 102 v (euro) d v< 50 v∈[50,75[ v∈[75,100[ v∈[100,200[ v∈[200,500[ d d PDF 10−1 100 101 10−2 10−1 100Results
Data Modeld (km)
Results
d (km) PDF 10−1 100 101 102 10−6 10−5 10−4 10−3 10−2 10−1 100 Pv= 0.2 Pv= 0.4 Pv= 0.6 Pv= 0.8 0.10 0.15 0.20 0.25 0.30 101 102 v (euro) PvMen Women
