CAIT project no.: CAIT-UTC-NC46
Fiscal Year: 2015/2016
Rutgers-CAIT Author(s): Hao Wang, Ph.D., Gerardo Flintsch, Ph.D., Patrick Szary, Ph.D
External Author(s): Susan Gresavage
Sponsor(s): USDOT-FHWA, New Jersey Department of Transportation
Accident data records have shown that wet pavement surface is a significant factor causing car and truck accidents. The vehicle operation, roadway geometric design, and pavement surface and drainage condition are critical factors affecting skid resistance on wet surface and hydroplaning risk. The current models of predicting hydroplaning risk are mainly based on regression analysis of the limited experiment data. These empirical models are difficult to capture the physic-based principle and thus cannot be applied outside the range of data that were used to develop the models. In addition, the current models are focused more on passenger car tires and did not consider water flow characteristics on rough pavement surface. The hydroplaning potential of truck tires at different conditions has not been thoroughly investigated. The research aims to develop an integrated hydroplaning model for trucks that can be used by transportation agencies to design safer roadways.