Projection of road sensors to the Dutch road network...Projection of road sensors to the Dutch road...
Transcript of Projection of road sensors to the Dutch road network...Projection of road sensors to the Dutch road...
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Projection of road sensors to the
Dutch road network
Martijn Tennekes, Marco Puts
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Road sensors
– 60,000 road sensors in the
Netherlands
– Vehicle counts every minute
Aim: production of traffic statistics Output: vehicle-kilometres (= # passing vehicles * trip length) per highway per direction per NUTS3 region.
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Dutch highways
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Dutch highways with road sensors
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A closer look…
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A closer look…
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Sensor data
Time [minutes]
Vehicle count
Raw data
Filtered data
Data from a single sensor:
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Traffic statistics
Roads (unit=km)
Road sensors
Sensor data
Based on location …
Weighting method
Survey statistics
Target population (unit=person)
Sample of respondents
Questionnaire
Based on demographics
Frame
Selection
Measurements
Weights
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Road selection
– Dutch Highways
– Main routes (no interchange, entrance and exit ramps)
The plots were created with the R-package tmap
(recently published on CRAN).
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Metadata input
– ESRI shape file of Dutch roads
– Road sensor metadata
Road Direction Type Lat Long
A79 West Main 50.8779 5.7502
A79 West Main 50.8772 5.7625
A79 West Main 50.8768 5.7737
A79 West Main 50.8747 5.8082
A79 West Main 50.8828 5.8650
… … … … …
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Map projection
‐ Dutch National Grid (Rijksdriehoekstelsel)
‐ Preserves real-world distances
53ºN
52ºN
51ºN
4ºE 5ºE 6ºE 7ºE
Amersfoort: projection centre
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Main routes
Simplify
Main routes Raw shape
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Metadata inconsistencies
No road sensors?
Where is the road?
Possible causes: • Errors in metadata • Different time references • Different definitions
Solutions: • Shape is leading: • Sensors are leading:
Impute empty part Cut off empty part
Remove loose road sensors Extrapolate main route
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– Project road sensors on main routes
– Determine points of bifurcation for all entrance and exit
ramps
Projections
Entrance ramp
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Road segments
Main route
Road sensors
Road segments (=weights)
3000 2000 2500
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Weighting
3000 2000 2500
20 7
Traffic flow
Count 3000 3000 2000 2000 2500
Length 10 5 5
5*3000 + 5*3000 + 10*2000 + 20*2000 + 7*2500 = 107,500 vehicle-km
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Conclusion remarks
– A proper frame is often required for big data driven statistics.
– For traffic statistics, the road segment lengths are used as
weights; vehicle counts are weighted to the road network.
– Further development at Statistics Netherlands:
‐ Embedding into regular production
‐ Extension with provincial roads.