Road Geometric Detection Methodbased On Inertial Reference

Road geometry parameters are important indicators reflect road safety factor. Linear detection of road geometry throughout the highway design, construction, completion and acceptance of the whole process of assessment and maintenance. Highway industry after a massive pre-construction phase, slowly into the curing stage. Road maintenance road detection provides data to support decision-making, and its importance is self-evident. With the rapid growth of the number of miles, the traditional manual inspection pavement geometric linear way data can not meet the requirements. With the rapid development of automation, communications and computer technology to achieve rapid detection of road geometric alignment parameters, more and more scholars began to study a method and apparatus capable of pavement geometric alignment parameters automatically check.Road geometry is linear three-dimensional shape by the cross-section profile and alignment of the road plane composed, including the parameter cross-fall, slope and curvature of horizontal curve and vertical curve curvature. Road geometry in cross-fall and slope value is small; it is difficult to accurately measure. Traditional manual detection methods slow, poor accuracy, low efficiency, and the need to control traffic, there is a serious deficiency in real time, flexibility and security aspects. This paper presents a method for detecting linear path geometry based inertial reference, using four laser range finders(LRFs) forming an array of laser ranging, combining GPS and inertial navigation unit(IMU) Construction inertial reference measuring surface to achieve road geometry automatic detection of linear parameters. To improve the measurement accuracy, the influence of laser measurement plane and measured pavement opposite stance on the measurement accuracy, and designed a calibration method based on the relative movement by getting laser ranging array of pre-bias angle correction calibration measurement data, thus effectively improving the measurement accuracy.Finally, detected on Wuhan, Hidden Dragon Avenue and Avenue Tianzishan actually two sections, can meet the Subgrade Pavement field testing procedures required. The results showed that after calibration measurement accuracy is improved by about 5%, cross-fall data measurement repeatability than 95% correlation parameters have reached 99.9%. Experiments show that the proposed detection method feasible and efficient, safe and reliable system operation.