The calibration of highly integrated special vehicles directly affects their performance and is a crucial step in vehicle development. Traditional calibration methods use instruments such as theodolites and spirit levels to measure the vehicle, which involve complex operations and have low levels of automation and efficiency. This paper proposes a general automatic calibration method for highly integrated special vehicles based on multi-view vision measurement technology to address this issue. The method employs multiple cameras to capture images of ground control fields and measurement fixtures fixed to the vehicle's surface under test. By acquiring encoded point information and applying the spatial coordinate transformation principle based on the least squares method and common point transformation techniques, the spatial pose relationships between the objects under test are calculated, thereby deriving various accuracy indicators of the vehicle. Validation tests show that, compared to traditional calibration methods, the proposed vision-based automatic calibration method can reduce the calibration time to 25% of the original duration while maintaining comparable accuracy, significantly improving calibration efficiency.