A method and system for predicting the position of a lost vehicle based on historical information

Abstract

The invention relates to a historical information-based lost vehicle position prediction method and system. The method comprises the steps of obtaining a plurality of pieces of historical track information of a lost vehicle; Preprocessing the plurality of pieces of historical track information; Carrying out clustering analysis on track starting points in the plurality of pieces of preprocessed historical track information to obtain a similar track information set and a different track information set; Extracting bifurcation points in the similar track information set, and updating the extracted bifurcation points into a bifurcation point data set; Predicting the position of the lost vehicle according to the lost position of the vehicle and the bifurcation point probability model; Accordingto the prediction method disclosed by the invention, the elimination of abnormal track points and the preprocessing operation of an insertion algorithm are added, and the accuracy of bifurcation point statistics is improved by correcting the abnormal track points in the historical track; And meanwhile, the bifurcation point is extracted, and a minimum distance algorithm is newly added for judgment, so that the positioning accuracy can be improved, and the accurate positioning requirement of a user can be more fully met.

Description

technical field [0001] The present invention relates to the technical field of information processing, in particular to a method and system for predicting the position of a lost vehicle based on historical information. Background technique [0002] As a convenient means of transportation, automobiles have become an indispensable way of travel in people's daily life. In real life, whether it is driving a private car, renting a car or taking a taxi, it has become very common. At present, most automobiles are equipped with a positioning device, through which the user can track the location of the vehicle in real time. Private car owners and car rental merchants can know the location of the vehicle through the positioning device in the vehicle, and find the lost vehicle in time; for taxi users, they can know their own location through the positioning device in the vehicle, and share the location with family and friends , to better ensure the personal safety of taxi users. [...

AI Technical Summary

Problems solved by technology

[0005] 1) The trajectory information recorded by GPS is too rough, and a large number of possible prediction results are often lost;

[0006] 2) There is a large error between the probability model statistics related to position prediction and the real situation;

[0007] 3) The prediction method only relies on the historical trajectory of the vehicle and lacks the analysis of other factors, resulting in low positioning accuracy;

[0008] It can be seen that the existing position prediction methods for lost vehicles cannot fully meet the precise positioning needs of users.

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