Copyright Peter Widhalm at CeDEM14

1. Mining Mobile Sensor Data for
Transportation Modelling
Peter Widhalm

2. Transportation Modelling
Goal: optimizing the transporation system by
understanding, predicting and influencing travel behavior
accurate modeling of the effects of different policies before
implementation
2
Policy decisions regarding the transportation
system have a tangible impact on many people!

3. Motivation
Traditional household surveys
expensive
limited sample size
no up-to-date data
data quality / incomplete data
last nation-wide survey conducted in 1995!
IT support for mobility surveys
goals: reduce costs, improve data quality
collect trip data automatically:
• Smartphones / GPS tracker
• Cellular network

4. IT support for collecting trip data

5. 5
ssive active
Smartphone AppNetwork Traffic
Cell Phone Data
SEMAPHORE

6. 6
assive active
Smartphone AppNetwork Traffic
Cell Phone Data
GPS
8:00 am
8:12 am
8:24 am
8:29 am
Advantages:
large sample size
no recruiting
no burden on individuals
infrastructure already in place
Challenges:
−low spatial resolution and sparse sampling
of movements
−not linked to sociodemographics
−not linked to purposes / activities

7. Extraction of activity times and locations
7

8. Traffic flows
8

9. Traffic flows (commuters)
9

10. Extraction of activity times and locations
10
0
0.1
0.2
0.3
0.4
2 0 3 4 4 4 5 4 5 5
ViennaCell Phone
ViennaSurvey
Boston Cell Phone
Boston Survey
ViennaCell Phone
ViennaSurvey
Boston Cell Phone
Boston Survey

11. Combination with other data sources
11
Shop
WorkHome
Leisure
1
2
3
45
temporal
patterns
phic context
se, POIs)
sociodemographics
census data

12. Take home message
Travel data collected with Smartphone Apps can assist traditional mobility
surveys.
Passively collected cell phone data are generated by infrastructure
already in place.
By combining cell phone data with other data sources such as
census data,
points-of-interest,
land use
they provide rich and up-to-date information about human travel behavior.
Cell phone data help us to predict the effects of policies before
implementation and to evaluate their effect after implementation
12