System and method for recognizing position of vehicle

Patent metadata

Field	Value
Publication number	US-2018267172-A1
Application number	US-201715717064-A
Country	US
Kind code	A1
Filing date	Sep 27, 2017
Priority date	Mar 20, 2017
Publication date	Sep 20, 2018
Grant date	—

Abstract

The present disclosure provides a system for recognizing a position of a vehicle including: a lane-based position recognition device configured to extract correction information about a heading angle and a lateral position of the vehicle by comparing measured lane information with lane information on an accurate map; a LiDAR-based position recognition device that extracts correction information about a position of the vehicle by detecting an area in consideration of surrounding vehicles and obstacles measured through a LiDAR sensor; and a position assemble device configured to assemble a position based on the correction information about the heading angle and the lateral position of the vehicle, correction information about a heading angle, a longitudinal position and a lateral position of the vehicle from the LiDAR sensor, and correction information about a heading angle, a longitudinal position and a lateral position of the vehicle from GPS.

First claim

What is claimed is:

1 . A system for recognizing a position of a vehicle, the system comprising:
a lane-based position recognition device configured to extract first correction information and second correction information by comparing measured lane information with lane information on an accurate map, wherein the first correction information is correction information regarding a heading angle of the vehicle and the second correction information is correction information regarding a lateral position of the vehicle; a Light Detection And Ranging (LiDAR)-based position recognition device configured to extract correction information regarding a position of the vehicle by detecting an area, wherein a LiDAR sensor measures surrounding vehicles and obstacles to detect the area; and a position assembly device configured to assemble a position based on:
the first and second correction information;
LiDAR sensor-based correction information comprising the first, second, and third correction information obtained by the LiDAR sensor, wherein the third correction information is correction information regarding a longitudinal position of the vehicle; and
GPS-based correction information comprising the first, second, and third correction information obtained by a GPS.

2 . A method of recognizing a position of a vehicle, the method comprising:
extracting first correction information and second correction information by comparing measured lane information with lane information on an accurate map, wherein the first correction information is correction information regarding a heading angle of the vehicle and the second correction information is correction information regarding a lateral position of the vehicle; extracting correction information regarding a position of the vehicle by detecting an area, wherein a Light Detection And Ranging (LiDAR) sensor measures surrounding vehicles and obstacles to detect the area; and assembling a position based on:
the first and second correction information;
LiDAR sensor-based correction information comprising the first, second, and third correction information obtained by the LiDAR sensor, wherein the third correction information is correction information regarding a longitudinal position of the vehicle; and
GPS-based correction information comprising the first, second, and third correction information obtained by a GPS.

3 . The method of claim 2 , further comprising:
predicting a moving route of the vehicle from a previous position to a current position before extracting the first and second correction information.

4 . The method of claim 2 , wherein extracting the first and second correction information comprises:
dividing a measured lane and a lane on the accurate map into a plurality of matching sections based on a longitudinal direction of the vehicle; and matching the measured lane with the lane on the accurate map.

5 . The method of claim 2 , wherein assembling the position comprises:
converting a final position for any sensor of the plurality of sensors into a vehicle position-based coordinate system; extracting the first correction information; extracting the second correction information; extracting the third correction information; and converting the first, second, and third information into global coordinates.

6 . The method of claim 2 , wherein extracting the correction information regarding the position of the vehicle comprises:
extracting, with a LiDAR signal, an outline; calculating a region of interest (ROI) of a matchable area from the outline; classifying feature lines in longitudinal, lateral, and diagonal directions; setting the matchable area based on the feature lines; extracting the first, second, and third correction information for any outline of the plurality of outlines; and calculating a weight for any outline of the plurality of outlines.

7 . The method of claim 6 , wherein classifying the feature line in the longitudinal direction comprises:
matching the feature line with the outline based on a lateral position error prediction value (E_LAT).

8 . The method of claim 6 , wherein classifying the feature line in the lateral direction comprises:
matching the feature line with the outline based on a longitudinal position error prediction value (E_LONG).

9 . The method of claim 6 , wherein classifying the feature line in the diagonal direction comprises:
when the second correction information exists, matching the feature line with the outline based on the longitudinal position error prediction value; and when the second correction information does not exist, matching the feature line with the outline based on the lateral position error prediction value and the longitudinal position error prediction value.

Assignees

• Hyundai Motor Co Ltd
• Kia Motors Corp

Inventors

• Oh Young Chul
• Shin Ki Cheol
• You Byung Yong
• Heo Myung Seon
• Woo Ha Yong

Classifications

• G01C21/3602

  Input other than that of destination using image analysis, e.g. detection of road signs, lanes, buildings, real preceding vehicles using a camera · CPC title

• G01S19/45 Primary

  by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement · CPC title

• G01S17/86 Primary

  Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders · CPC title

• G01C21/30 Primary

  Map- or contour-matching · CPC title

• G01C21/3658 Primary

  Lane guidance · CPC title