Autopilot model for shield tunneling machines using support vector regression and its application to previously constructed tunnels

Abstract

AbstractAlthough a shield tunneling machine is intended to excavate a tunnel along its planned alignment, deviations occur between the planned alignment and the measured alignment, which must be corrected. These operations are time‐consuming, and it is difficult to correct deviations. However, related studies have been unable to automatically calculate the optimum operation parameters. Therefore, this study sought to use machine learning to develop an autopilot model, which is a method to automatically calculate optimal operation parameters of the shield machine for straight and curved sections of the planned alignment in both plan and longitudinal views using support vector regression. As a result, it could automatically calculate operation parameters that predict a shield machine that excavates with the same or better excavating accuracy of a skilled operator and contributes to the automation of shield machine operation.