In recent years, a variety of mobile road measurement equipment has emerged and become an important means of collecting spatial information. As an important part of the mobile road measurement system, a camera’s function implementation and data accuracy largely depend on its internal parameters and the rotation and translation parameters corresponding to the world coordinate system. Based on this and on the traditional camera calibration method, radial and tangential distortion for monocular camera calibration is introduced in this article to establish a calibration model, and the nonlinear least-squares Levenberg–Marquardt optimization algorithm is used in iterative calculation. The parameters provide a solution to the problem of rapid calibration of camera modules in mobile road measurement systems. The camera parameters obtained by the calibration algorithm in this study are used for visual reconstruction. Compared with two Zhang Zhengyou calibration methods optimized by the Gauss–Newton method, the former has an average pixel offset of 0.28 pixel and the latter has deviations of 0.66 and 0.38 pixel. Using a monocular camera to collect data on geometric targets on a road, the average relative error does not exceed 2.16%. Experiments show that this method can obtain calibration results quickly and accurately.