Hydroplaning on Sloping Pavements Based on Inertial Measurement Unit (IMU) and 1mm 3D Laser Imaging Data

Abstract

The hydroplaning risk would increase on sloping pavements due to the fact that the presence of longitudinal and cross slopes would decrease the wheel load of vehicles perpendicular to the pavement surface. In previous studies, the effects of pavement slope on vertical wheel load and relevant hydroplaning speed prediction are ignored. To address this potential problem, the paper presents two improved models based on the existing Gallaway and University of South Florida (USF) models. Firstly, 1mm 3D laser imaging data is continuously collected at highway speed with the 1mm 3D PaveVision3D Ultra system, and simultaneously cross slope is acquired with an Inertial Measurement Unit (IMU) system and calibrated with1mm 3D data. A 4.35 km pavement section with five horizontal curves is selected to investigate hydroplaning speed predicted from Gallawayand USF models, and the two improved models. 1mm 3D pavement surface data is used to estimate texture information for the models in lieu of traditional spot-laser based texture measurement devices. Findings show that hydroplaning speeds at pavement segments with large slopes are lower than that at pavement segments with no grades. Moreover, pavement segments with potential hydroplaning risk are identified by comparing predicted hydroplaning speeds with posted speed limit. The significance of this paper is integrating the real-time 1mm 3D texture data and IMU data into the improved models for potential hydroplaning prediction of sloping pavement in network level survey.