High Speed Real-time Embedded System For Pavement Texture Measurements

Abstract

The Texas Department of Transportation (TxDOT) collects road profile data from the state highway network and processes the same in order to determine the various anomalies on the road surface. These factors can adversely affect the characteristics and performance of the vehicle such as skid, fuel consumption, ride comfort, safety and tire wear. The International Roughness Index (IRI) and Mean Profile Depth (MPD) are the statistics used for quantifying ride and texture. Pavement texture is of particular importance as it can affect skidding in wet weather conditions. This thesis mainly focuses on the development and implementation of a real-time embedded system which measures macro and mega texture and computes MPD at highway speeds. The system is based around Intel's multi-core NUC, permitting the use of parallel processing for the simultaneous measurements and calculation of the MPD. The texture module includes a 78 KHz LMI laser and a distance encoder. MPD section locations are maintained by GPS position data. The research is funded in part by Intel Corporation.