Abstract: A method includes obtaining first traveling information of a vehicle from a sensor associated with the vehicle, and determining, based on the first traveling information, first location information of the vehicle and a first intermediate variable that is used in the determining the first location information. The method also includes determining a target precision estimation model from a plurality of pre-trained precision estimation models based on the first traveling information and the first intermediate variable. The plurality of pre-trained precision estimation models are obtained by training a machine learning model based on a training sample set. The method also includes inputting the first location information and the first intermediate variable into the target precision estimation model to obtain second location information of the vehicle and a precision error of the first location information relative to the second location information.

Abstract: A mobile device positioning method and a mobile device positioning apparatus (900) are disclosed. Perception vector elements (301 and 302) are associated with projection vector elements (303 and 304) based on horizontal positions of the perception vector elements (301 and 302) extracted from an image and horizontal positions of the projection vector elements (303 and 304) obtained through projection of vector elements in a map. In this way, when the horizontal positions of the associated perception vector elements (301 and 302) and the horizontal positions of the associated projection vector elements (303 and 304) are separately arranged in a same order, horizontal position distribution of all the arranged perception vector elements (301 and 302) is consistent with that of corresponding projection vector elements (303 and 304) in the arranged projection vector elements (303 and 304), and pose estimation is performed on a mobile device based on an association result.