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MDS S

MDS S. Paul Bridge. Vaisala’s MDSS Experience. IceMan - Developed in 1994 to take RWIS a step further. Vaisala’s MDSS Experience. Planning and communications tool:. Manual Propose Default Propose Auto Propose. Vaisala’s MDSS Experience. Planning and communications tool:.

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MDS S

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  1. MDSS Paul Bridge

  2. Vaisala’s MDSS Experience • IceMan - Developed in 1994 to take RWIS a step further

  3. Vaisala’s MDSS Experience • Planning and communications tool: • Manual Propose • Default Propose • Auto Propose

  4. Vaisala’s MDSS Experience • Planning and communications tool: • Treatment monitoring • Audit Trail

  5. Vaisala’s MDSS Experience • Planning and communications tool: • Capture the knowledge of experienced decision makers • Support the Introduction of new treatment procedures

  6. Vaisala’s MDSS Experience • Planning and communications tool: • Web based • Can utilize forecasts from any forecast provider

  7. Some of the Key Lessons Learnt: • User configurable • Must obtain buy-in from users • Face to face training is crucial • End user needs confidence………….

  8. Confidence in forecasts • Forecasts prone to errors • Especially during developmental weather events • How can we convey forecast confidence?

  9. Confidence Factors 24 hour ahead site specific pavement temperature forecasts

  10. Requirement for observations • In order to verify forecasts, observations are necessary…….. There are many reasons to consider Vaisala’s non-invasive sensors……

  11. Simple to understand data…. RST & State 30ºF Slush Atmos 32ºF F 30ºF Grip & Thickness F 30% 0.07mm 0.2mm

  12. A few other reasons…….. • No requirement to slot-cut the surface or close the road. • Existing structures such as Poles, Lamp columns and Overhead Gantries can be used • No need to replace sensor when pavement is resurfaced • Less data downtime when sensors eventually require replacement • Measure a much larger footprint of the road surface compared to embedded sensors Pole Mounted Tower Mounted

  13. For MDSS • Friction Measurement • Potentially the Holy Grail of winter maintenance Can be used as a key performance indicator: • To assess and record how successful maintenance operations have been. • Provide a baseline from where to improve maintenance planning and operations.

  14. DSC111 (Road State) Performance – snow Aim of DSC111 The graph shows 24 hours of operational data from a Spectro sensor in Washington State. The green line shows ‘Grip’ or ‘friction’ which drops when snow showers occur in the early morning and again at around 0800 when general snow levels (purple line) start to build. The camera images confirm the surface state. Location of DRS (embedded road sensor) is approximately 2ft away from DSC111 & DST111 aim and in same wheel track.

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