A PSO-based method for road rut measurement with line-structured light

Road rut depth is a vital metric for evaluating pavement quality, traditionally measured manually but now assessed using automatic laser-based devices for the efficient data collection. This technique faces challenges due to the complex and variable nature of rut profiles and road conditions, leading to inconsistencies and interference from lane edges and debris. This study presents a novel method for rapid and precise rut depth measurement by employing line-structured light technology integrated with the inertial measurement unit (IMU) and global position system (GPS) sensors. The device undergoes meticulous calibration for accurate 3D road surface data acquisition, involving both line-structured light and positioning sensor calibrations. The collected high-resolution data is then refined using particle swarm optimisation (PSO) algorithms to enhance the accuracy of rut depth estimates. Experimental results demonstrate that this method not only improves the measurement accuracy and efficiency but also shows strong adaptability, making it a reliable tool for the road quality assessment.