road segment forecasting a tool for salt spreader control using gps viking workshop

March 15th 2007

Road segment forecasting A tool for salt spreader

control using GPSVIKING workshop

Hamburg, March 15th 2007by

Alexander Mahura, Claus Petersen and Bent SassPresented by

Torben Strunge PedersenThe Danish Meteorological Institute

March 15th 2007

Outline of the talk

• What is Road Segment Forecasting (RSF) ?

• A RSF method

• The Potential in RSF

• Quality and examples

• The future

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Road station

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Point forecasts (PF) from Road Condition Model (RCM) – Showing status

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RSF - Showing status

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Ice car – Used for thermal mapping

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Thermal mapping, Halskov - Ringsted

Left and right lane

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Mean thermal mapping profile

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GPS equipped spreaders

• GPS has opened the opportunity for automatic control of width and asymmetry of the spreading pattern

• With reliable weather forecasts for segments of the route the automation can be taken a step further – to automatically vary the amount of salt applied along the route

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New equipment for spreaders

• The price of infrared sensors determining the temperature of the road surface has come down

• Together with GPS this makes it economically possible to get thermal mapping data from spreaders in operation

• Provide data for validation

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Infra red sensor mounted on spreader

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Infra red sensor mounted on spreader

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Test route – 2005 / 2006 season

Route VA 4 - Ribe County

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Road segment forecast

• Based on PF ”near” the route forecasts for 2 km segments are obtained by interpolation

• Note this method does not use information from the infra red sensors!

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End user presentation

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Forecast quality

• Making a forecast is easy– But what is the quality ?

• Here we will look at quality through two measures– Mean Deviation (MD)– Mean Absolute Deviation (MAD)

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Forecast quality NWP

• NWP MAD – PF for road stations

MAD: Road temperature February 2006 (about 27.000 forecasts)

1.22 1.17 1.19 1.19 1.19

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1 2 3 4 5

NWP

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Forecast quality – Present system

• NWP versus RCM MAD – PF for road stations

MAD: Road temperature February 2006 (about 27.000 forecasts)

1,221,17 1,19 1,19 1,19

0,28

0,440,54

0,650,74

0,0

0,2

0,4

0,6

0,8

1,0

1,2

1,4

1 2 3 4 5

NWP RCM

March 15th 2007

Forecast quality – Present system

• The importance of road stations

MAD: Road temperature February 2006 (about 160.000 forecasts)

1.16 1.14 1.12 1.1 1.08

0.29

0.470.59

0.670.73

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1 2 3 4 5

RCM: no Obs RCM

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RSF-Potential - Hypothetical route

March 15th 2007

“RSF” potential

MAD: Road temperature February 2006 (about 160.000 forecasts)

0,690,78 0,82

0,910,97

0,38

0,58

0,710,81

0,89

0,0

0,2

0,4

0,6

0,8

1,0

1,2

1,4

1 2 3 4 5

RSF RCM

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Route VA 4 – thirty 2 km segments

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Measurements from spreaders

• 2005 – 2006 season• 102 operations available (duration

from minutes to about 4 hours)• 90.459 measurements in all• Time averaging (1 min.) and allocation

to the corresponding 2 km road segment reduces the amount available for the evaluation to 5.844 measurements

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Amount of observations by segment

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Comparison of observations

Infra red sensor versus road station

Starup

MD -0.11 degree

MAD 0.51 degree

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RSF (3 hour) versus observation I

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RSF (3 hour) versus observation II

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RSF (3 hour) versus observations MD

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RSF (3 hour) versus observation MAD

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The future

• The near future (now)– Integration of infra red sensor data in the RCM /

RSF forecasting– Increased horizontal resolution in the RCM– Include more test routes

• The not so distant future– Use of RSF for applying variable amounts of

salt along routes

• And then – eventually– Integration of RSF in spreaders for automatic

controlling of the salt amount used

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Conclusion

• The technology for developing and evaluate RSF is available

• This pilot study shows that the quality of RSF is nearly comparable to the one known from state of the art PF– Road stations are essential for a good

quality of forecasts (both PF and RSF)

March 15th 2007

The future is very near (you)!

Thank you for your attention!!!