Map-matching algorithm for combining multiple evidences

A technology of map matching and evidence fusion, applied in the field of map matching, can solve problems such as inability to meet navigation requirements, increase logic complexity, and sensitivity to abnormal points

Inactive Publication Date: 2016-09-07
CHINA NONFERROUS METAL CHANGSHA SURVEY & DESIGN INST CO LTD
View PDF2 Cites 12 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this algorithm also has some disadvantages: it is sensitive to abnormal points; only the geometric information of the map is used, and other useful information is not considered; since a certain number of points need to be collected to connect a line segment, the real-time performance is poor
Compared with other algorithms, this method has higher matching accuracy due to the increased logic complexity, but it still cannot meet the needs of navigation in complex and dense road networks

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Map-matching algorithm for combining multiple evidences
  • Map-matching algorithm for combining multiple evidences
  • Map-matching algorithm for combining multiple evidences

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0075] see figure 1 , a multi-evidence fusion map matching algorithm, applied to the online mining intelligent scheduling system, the specific process is as follows figure 1 ,Details are as follows:

[0076] The first step: Determine the error area in order to extract the information of candidate matching roads from the map data; the error area refers to the area containing the real position of the vehicle, and the roads in the error area are called candidate road sections to reduce the number of identified roads. Quantity, to improve the recognition speed; the more commonly used method of determining the error area is to define the error ellipse according to the probability criterion, that is, the error ellipse is as follows figure 2 shown;

[0077] The variance and covariance matrix of the set bit system are modeled as expression 1):

[0078] Σ = σ x ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a map-matching algorithm for combining multiple evidences. The algorithm comprises the following steps: a first step, an error area is determined; a second step, first combination is carried out for a D-S evidence; an information evidence with reachability is obtained; a third step, second combination is carried out for the D-S evidence; and a forth step, an optimum matching road is selected according to the result of the second combination of the D-S evidence in the third step. The error area is definite as a matrix area, so that selection of candidate roads is simplified, the real-time property of map-matching is improved, and reliability of coupling is guaranteed; simulated analyses are carried out for parallel roads, crossroads, overpasses, and other roads with multiple forks, so that coupling precision of special roads are improved; information evidences with reachability are investigated, so that comparison factors are reduced, calculation complexity is reduced, and coupling efficiency is improved; the first combination of the D-S evidence and the second combination of the D-S evidence are carried out, results with accuracy are obtained, and accuracy and stability of matching results are further ensured.

Description

technical field [0001] The invention relates to the technical field of map matching, in particular to a multi-evidence fusion map matching algorithm. Background technique [0002] GPS satellite positioning system has been widely used in the world, but there are two kinds of errors in the combined use of GPS satellite positioning and electronic map: Due to the influence of signals, the positioning error of GPS will increase to varying degrees; (2) In the process of making electronic maps, errors will also occur due to the need for registration and vectorization of electronic maps. Due to the existence of these two errors, the real position of the vehicle will not match the corresponding electronic map. [0003] The map matching algorithm plays a vital role in correcting the accurate position of the vehicle displayed on the electronic map. There are the following four matching algorithms in the prior art: [0004] The first type: an algorithm for fitting multiple matching fa...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G01C21/30
CPCG01C21/30
Inventor 邓军郭琴粟闯
Owner CHINA NONFERROUS METAL CHANGSHA SURVEY & DESIGN INST CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products