Vehicle position information prediction method based on Online-WSVR algorithm

Abstract

The invention discloses a vehicle position information prediction method based on the Online-WSVR algorithm. The method includes the steps that 1, driving state information of a vehicle is collected in real time through an integrated navigation system in the vehicle; 2, modeling is carried out with the Online-WSVR algorithm according to the driving state information, in a previous period of time, of the vehicle, and weights are distributed to data at all time points so that the data can make different contributions to the modeling coefficient and accuracy can be improved; 3, position information, at the next moment, of the vehicle is predicted in real time with an Online-WSVR modeling function according to the current driving state information, wherein if current GPS signals are valid, the predicted longitude and latitude information at the next moment is erased, and if the current GPS signals are invalid, the longitude and latitude information, at the next moment, of the vehicle is predicted with the Online-WSVR algorithm and written into a training set for modeling to serve as a modeling sample for subsequent prediction. The method has the advantages that the principle is simple, the application range is wide, the positioning and prediction precision is high, the cost is low, portability is achieve, and reliability is good.

Description

technical field [0001] The present invention mainly relates to the field of vehicle position information prediction, in particular to a vehicle positioning method based on the Online-WSVR (Online Weight Support Vector Machine for Regression) algorithm when the GPS signal fails briefly. Background technique [0002] In recent decades, intelligent transportation system ITS has been very popular. It can be said that it is the development direction of the future transportation system, and the use of multi-source data, data fusion, online learning and other algorithms to achieve the best performance of the system is the current application of ITS. A trend of research. Vehicle positioning is a very important part of intelligent transportation. At present, many vehicle navigation systems use GPS receivers as the main source of information, which can provide all-round accurate and continuous position information. However, in complex urban traffic environments, GPS also has some prob...

AI Technical Summary

Problems solved by technology

One is multi-path: a place may receive multiple GPS information at the same time, especially in urban areas with many tall buildings, it is prone to multi-channel effects and clock bias errors, resulting in potential errors in vehicle position data

Second, the problem of data loss

Usually occurs when the vehicle passes through the tunnel, because the satellite signal is blocked, causing the entire system communication to be interrupted

Third, there are too few visible satellites

The extreme conditions here include car crashes, bad weather, rush hours or holidays, etc. The sensor error fluctuates greatly, the data may have large noise errors, and data modeling is more difficult

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