Abstract

The majority of weather-related crashes in the U.S. occur on wet pavement, potentially due to hydroplaning. However, hydroplaning potential is often not considered in network-level pavement condition assessments. This paper provides a method for evaluating hydroplaning potential based on the actual road surface and geometric properties measured using mobile Light Detection and Ranging (lidar). The lidar measurements were placed in a grid format, and water film thickness was determined based on water depth and pavement macrotexture. A Monte Carlo simulation produced a travelling speed at which hydroplaning could occur. The developed method was applied to an in-service roadway section with historical wet weather crashes. It successfully identified the critical drainage basin and determined that the travelling speed at which hydroplaning could occur is lower than the posted speed limit. This method can be integrated into network-level pavement management systems to identify roadway sections with high risk of wet weather crashes.

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