Screening Hydroplaning Risk Area by HSD Data

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Screening Hydroplaning Risk Area by HSD Data

• Dr Wei Liu
• Senior Engineer
• Fugro PMS Ltd

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Introduction

• According to road safety reports from various
  road controlling authorities in New Zealand,
  about 30-40 of road crashes occurred in wet
  conditions.
• To reduce the number of crashes in wet weather, a
  lot of effort in the last 20 years has been put
  into studying and improving the skid resistance
  performance of the road pavement surfacing by the
  selection of polish resistant surfacing
  aggregates and the appropriate maintenance
  methods.

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Introduction

• However, as another type of wet weather risk,
  hydroplaning, is often only considered and
  handled in the design phase of road and highway
  engineering by providing sufficient drainage and
  proper selection of surface materials.
• During the operation and maintenance of roads and
  highways, there is still no direct and practical
  method to quantify hydroplaning risk on existing
  roads and highways.
• Moreover, when hydroplaning occurs (which can be
  either full or partial hydroplaning), it often
  results in a serious injury or fatal accident.

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Introduction

• For any set of driver inputs, tyre conditions and
  surfacing material, hydroplaning is only a
  function of water depth and vehicle speed.
• A general rule of thumb for highways is that
  hydroplaning can be expected for speeds above
  70kph where water ponds to a depth of 2.5mm or
  greater over a distance of 10m or greater.

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Introduction

• Pavement transverse profile is normally measured
  by HSD equipment such as laser profiler to
  calculate rut depth in the wheelpath.
• On the other side, water depth can be measured
  perpendicular to the water surface as the largest
  of the measured depths from a mean transverse
  profile.
• In this research, a methodology for identifying
  and screening of hydroplaning risk area through
  calculation of water depth from pavement profile
  measurement will be introduced.

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Methodology

• Assumptions
• Rainfall intensity and duration is enough to
  cause the maximum possible water depth on the
  road surface.
• Surface drainage is conducted on transverse
  direction only through the crossfall of road.
• The influence of tyre characteristics such as
  tread pattern and depth is ignored.
• The risk of hydroplaning exposed to all kinds of
  vehicles and drivers with the same travel speed
  by the road is similar.

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Methodology

• Methodology
• Compute the maximum water depth for each
  transverse profile measurement along the road
  section.
• Calculate the minimum water depth that can cause
  hydroplaning of vehicle at specific travel speed
• Find the hydroplaning risk area of road section
  for those areas with the actual maximum water
  depth exceeding the minimum water depth that can
  cause the hydroplaning of vehicle at specific
  travel speed with a length more than 10m.

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Methodology

• Minimum water depth that can cause the
  hydroplaning of vehicle
• Where, WDmin is the minimum water depth in mm
  that can cause the hydroplaning of vehicle and S
  is the vehicle speed in kph.

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Implementation Example

• A road section of 5.7km long from SH003/RS0057
  was selected to carry out the hydroplaning risk
  analysis.
• This section was selected because there were 15
  accidents happened in this section of road under
  wet surface condition during the last 5 years.

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Implementation Example

• Maximum water depth calculation results for
  decreasing lane of SH003/RS057

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Implementation Example

• Maximum water depth calculation results for
  increasing lane of SH003/RS057

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Implementation Example

• Hydroplaning risk area identification results for
  decreasing lane of SH003/RS057
• Analysis speed 100 km/h
• Minimum water depth for hydroplaning 0.89mm
• Minimum length of water pond 10m

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Implementation Example

• Hydroplaning risk area identification results for
  increasing lane of SH003/RS057
• Analysis speed 100 km/h
• Minimum water depth for hydroplaning 0.89mm
• Minimum length of water pond 10m

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Summary and Conclusion

• A computer based analysis methodology and
  procedure for screening hydroplaning risk on the
  network level has been developed.
• This procedure takes the pavement profile data
  from HSD survey as input and calculates the
  maximum water depth occurring on the road.
• The maximum water depth results were then used to
  compare the minimum water depth that can cause
  the hydroplaning of vehicle at a specific speed
  to identify the potential hydroplaning risk area.
  
• An implementation example has demonstrated that
  the proposed methodology can provide meaningful
  results by comparing the wet accident records
  from CAS database.
• It is recommended that the proposed method should
  be applied as a supplement to the skid resistance
  method for the selection of safety improvement
  project.

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Thank you! If any question or comment, please
feel free to contact us wei.liu_at_pmsnz.co.nz Bryce
.tinkler_at_pmsnz.co.nz Phone [phone]