SYSTEM AND METHOD FOR PRECISION VEHICLE POSITIONING

• US 20180239032A1
• Filed: 08/11/2016
• Published: 08/23/2018
• Est. Priority Date: 08/11/2015
• Status: Abandoned Application

• Current Assignee: Continental Automotive GmbH (Continental AG)
• Original Assignee: Continental Automotive GmbH (Continental AG)
• Inventors: THIEL, Christian, BARNARD, Paul, HERBST, James, LENNINGER, Ralf Johannes, FOERSTERLING, Frank
• Application Number:
  US15/751,418
• Publication Number:
  US 20180239032A1
• Time in Patent Office: Days
• CPC Class Codes: G01C 21/28 with correlation of data from several navigational instruments
• CPC Class Codes: G01C 21/30 Map- or contour-matching
• CPC Class Codes: G01C 21/3602 Input other than that of destination using image analysis, e.g. detection of road signs, lanes, buildings, real preceding vehicles using a camera
• CPC Class Codes: G01S 19/40 Correcting position, velocity or attitude
• CPC Class Codes: G01S 19/42 Determining position

Abstract

A method and a system for precision vehicle positioning based on a digital road description database containing fourth data sets with object-based information about at least one of a road object, a road furniture object and a geographic object is disclosed. First data sets based on the fourth data sets are forwarded to a vehicle. The vehicle is collecting ambient data like images along its path, generating second data sets comprising at least location information and detailed object-based information. During driving and after generating second data sets, the vehicle tries to identify in the second data sets the same driving-relevant objects and/or object reference points and/or groups of driving-relevant objects and/or object reference points as are contained in the first data sets. Furthermore, the vehicle aligns the same driving-relevant objects and/or object reference points and/or groups of driving-relevant objects and/or object reference points between the second data sets and the first data sets, and derives a position value for its own position.

Claims

1. A method for precision vehicle positioning by using data received from a database and data collected by the vehicle while traveling along a path comprising the steps of

a) the vehicle receiving, from the database and in an object-based 3D vector format, first data sets comprising driving-relevant object data for a current position of the vehicle, such driving-relevant object data comprising at least location information, an optional object reference point and detailed object-based information about at least one driving-relevant object like a road object, a road furniture object, a geographic object or a further object related to driving,

b) the vehicle generating, while driving, a plurality of ambient data sets along at least sections of its path by at least one sensor of the vehicle, the ambient data sets relating to at least one of driving-relevant objects, road furniture and geographic objects,

c) the vehicle performing object data processing by evaluating the at least one ambient data sets and generating, in an object-based 3D vector format, at least one second data set of driving-relevant object data based on the evaluation results,

d) while driving and after generating second data sets, the vehicle trying to identify in the second data sets the same driving-relevant objects and/or object reference points and/or groups of driving-relevant objects and/or groups of object reference points that are comprised in the first data sets, and

e) the vehicle aligning the same driving-relevant objects and/or object reference points and/or groups of driving-relevant objects and/or object reference points between the second data sets and the first data sets in object-based 3D vector format, for deriving a position value for its own position.

2. The method according to claim 1,

characterized in, that

the position value comprises an offset to a value measured by a GNSS system of the vehicle.

3. The method according to claim 1,

characterized in, that

the position value comprises a position within the positions world of the first data sets, relative to driving-relevant objects and/or groups of driving-relevant objects as contained in the first data sets.

4. The method according to claim 3, characterized in, that

the vehicle uses the first data sets in order to simplify and/or speed up object processing and/or the generation of the second data sets and/or the identification of the same driving-relevant objects and/or object reference points and/or groups of driving-relevant objects and/or object reference points in the second data sets as are contained in the first data sets.

5. The method according to claim 4, characterized in, that

the vehicle collects at least one ambient data set by using at least one of an image sensor like a CCD sensor, an infrared sensor, a laser scanner, an ultrasound transducer, a radar sensor and an RF channel sensor.

6. The method according to claim 5, characterized in, that

the database is hosted by at least one stationary server external to the vehicle.

7. The method according to claim 6, characterized in, that

at least one group of objects comprises a road object and at least one of a road furniture object and a geographic object.

8. The method according to claim 7, characterized in, that

at least one second data set of driving-relevant objects comprises location information based at least on the vehicle'"'"'s GNSS.

9. A vehicle having means for precision vehicle positioning by using data from a database, the database storing data sets comprising driving-relevant object data, such driving-relevant object data comprising at least location information, an optional object reference point and detailed object-based information about at least one driving-relevant object like a road object, a road furniture object, a geographic object or a further object related to driving,

the vehicle having means for receiving, in an object-based 3D vector format, first data sets from the database for a current position of the vehicle,

the vehicle having means for generating, while driving, at least one ambient data set along at least sections of its path by at least one sensor of the vehicle, the at least one ambient data set relating to at least one of driving-relevant objects, road furniture and geographic objects,

means for performing object data processing by evaluating the at least one ambient data set and generating, in an object-based 3D vector format, at least one second data set of driving-relevant object data based on the evaluation results,

means for identifying a plurality of object reference points in the at least one second data set,

means for generating at least one group of object reference points in the at least one second data set,

means for trying to identify while driving and after generating second data sets, in the at least one second data set the same driving-relevant objects and/or object reference points and/or groups of driving-relevant objects and/or groups of object reference points as are contained in the first data sets, and

means for aligning the same driving-relevant objects and/or object reference points and/or groups of driving-relevant objects and/or object reference points between the at least one second data set and the first data sets, in object-based 3D vector format, and for deriving a position value for its own position.

10. The vehicle according to claim 9,

characterized in, that

the at least one sensor of the vehicle is a CCD image sensor, an infrared sensor, a laser scanner, an ultrasound transducer, a radar sensor or an RF channel sensor to collect at least one ambient data set.