High-definition maps (HDM) for autonomous driving (AD) are an important component of AD systems. HDM can provide highly accurate prior data of lane lines and road support facilities for AD systems, but the accuracy evaluation of HDM has been troubled by the development of the industry, so it is an important task to evaluate the accuracy of HDM reasonably. The current methods for relative accuracy evaluation of general maps in the field of mapping are not fully applicable to HDMs. In this study, a method based on point set alignment and resampling is used to evaluate the relative accuracy of lane lines, and experiments are conducted based on relevant real HDM data. That is, the points on the verification curve are fitted and sampled first, then the aligned point pairs are registered, and then resampling is carried out after registration. On this basis, the relative accuracy is calculated. The relative limit error of the verified first group of lane lines is 15.9cm, which is less than 20cm and meets the relative accuracy requirements; the relative limit error of the other three groups of lane lines also meets this requirement. This results show that the relative accuracy of the calculated lane lines based on this method is more accurate and reliable than that of the traditional method, especially the lane lines containing obvious curves. This has a certain influence on the quality control of HDM products, and also provides a theoretical basis and reference for the accuracy evaluation of HDM.