METHOD AND APPARATUS FOR THE CLASSIFICATION OF DATA

• US 20120290198A1
• Filed: 05/09/2012
• Published: 11/15/2012
• Est. Priority Date: 05/12/2011
• Status: Active Grant

• Current Assignee: GM Global Technology Operations LLC (General Motors Company)
• Original Assignee: GM Global Technology Operations LLC (General Motors Company)
• Inventors: STUEBING, Hagen, FIRL, Jonas
• Granted Patent: US 8,897,997 B2
• Time in Patent Office: Days
• US Class Current: 701/117
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0133 for classifying traffic situation
• CPC Class Codes: G08G 1/0145 for active traffic flow control
• CPC Class Codes: G08G 1/07 Controlling traffic signals
• CPC Class Codes: G08G 1/163 involving continuous checking
• CPC Class Codes: G08G 1/166 for active traffic, e.g. moving vehicles, pedestrians, bikes
• CPC Class Codes: H04W 4/024 Guidance services
• CPC Class Codes: H04W 4/46 for vehicle-to-vehicle communication [V2V]

Abstract

A method for the classification of data includes receiving a first message that is a vehicle-to-vehicle or a vehicle-to-infrastructure message. The first message includes first mobility data of a vehicle. An expected route of the vehicle is determined based on the first mobility data. A second message that is a vehicle-to-vehicle or a vehicle-to-infrastructure message is received. The second message includes second mobility data of the vehicle. An actual route of the vehicle is determined based on the second mobility data. Whether the expected route deviates from the actual route by at least a predetermined threshold value is determined. If the expected route deviates from the actual route by at least the predetermined threshold value, a type of momentary driving maneuver of the vehicle is determined and the first mobility data and the second mobility data are classified on the basis of the type of momentary driving maneuver.

Claims

1. A method for classification of data, the method comprising the steps of:

receiving a first message that is a vehicle-to-vehicle message and a vehicle-to-infrastructure message, wherein the first message includes first mobility data of a vehicle;

determining an expected route of the vehicle based on the first mobility data;

receiving a second message that is a vehicle-to-vehicle message or a vehicle-to-infrastructure message, wherein the second message includes second mobility data of the vehicle;

determining an actual route of the vehicle based on the second mobility data;

determining whether the expected route deviates from the actual route by at least a predetermined threshold value, and

if the expected route deviates from the actual route by at least the predetermined threshold value, determining a type of momentary driving maneuver of the vehicle and classifying the first mobility data and the second mobility data on a basis of the type of momentary driving maneuver.

2. The method according to claim 1, wherein determining the type of momentary driving maneuver of the vehicle is performed on a basis of the first mobility data and the second mobility data.

3. The method according to claim 2, wherein determining the type of momentary driving maneuver of the vehicle is performed on a basis of a Hidden Markov model.

4. The method according to claim 1, wherein determining the type of momentary driving maneuver of the vehicle is performed on a basis of a Kalman filter method.

5. The method according to claim 1, wherein classifying the first mobility data and the second mobility data comprises the steps of:

adapting the predetermined threshold value to an adapted threshold value based on the type of momentary driving maneuver; and

determining whether the expected route deviates from the actual route by at least the adapted threshold value.

6. The method according to claim 5, wherein, if it is determined that the expected route deviates from the actual route by at least the adapted threshold value, the first mobility data and the second mobility data are classified as being erroneous, and wherein if it is determined that the expected route does not deviate from the actual route by at least the adapted threshold value, the first mobility data and the second mobility data are classified as being free from errors.

7. The method according to claim 5, wherein, if it is determined that the expected route does not deviate from the actual route by at least the adapted threshold value, adaptation of a Kalman Gain value is performed.

8. The method according to claim 1, wherein determining the actual route of the vehicle and/or determining the type of momentary driving maneuver of the vehicle is performed additionally on a basis of data determined from a sensor, wherein the sensor is an electromagnetic sensor, an acoustic sensor, or an optical camera.

9. The method according to claim 1, wherein the first message and/or the second message are part of periodically sent messages.

10. The method according to claim 1, wherein at least after receiving the first message a plausibility check on the first mobility data is performed and wherein determining the expected route, determining the actual route and determining whether the expected route deviates from the actual route by at least the predetermined threshold value is performed, if the first mobility data are determined as being plausible.

11. The method according to claim 1, wherein the first message additionally includes an identifier of a transmitting device sending the first message and wherein determining the expected route, determining the actual route and determining whether the expected route deviates from the actual route by at least the predetermined threshold value are performed if a further message has already been received from the transmitting device.

12. The method according to claim 1, wherein the first mobility data and/or the second mobility data, after classifying, are communicated to a driver assistance system and/or an infrastructure facility.

13. An apparatus for classification of data comprising:

a receiving device configured to receive a message that is a vehicle-to-vehicle message or a vehicle-to-infrastructure message, wherein the message includes mobility data of a vehicle;

a first determination device configured to determine an expected route of the vehicle on a basis of the mobility data;

a second determination device configured to determine an actual route of the vehicle on a basis of the mobility data;

a third determination device configured to determine whether the expected route deviates from the actual route by at least a predetermined threshold value;

a fourth determination device configured to determine a type of momentary driving maneuver of the vehicle, if it is determined that the expected route deviates from the actual route by at least the predetermined threshold value; and

a classification device configured to classify the mobility data on a basis of the type of momentary driving maneuver.

14. A computer readable medium embodying a computer program product, the computer program product comprising:

a program to classify data, the program configured to;

receive a first message that is a vehicle-to-vehicle message and a vehicle-to-infrastructure message, wherein the first message includes first mobility data of a vehicle;

determine an expected route of the vehicle based on the first mobility data;

receive a second message that is a vehicle-to-vehicle message or a vehicle-to-infrastructure message, wherein the second message includes second mobility data of the vehicle;

determine an actual route of the vehicle based on the second mobility data;

determine whether the expected route deviates from the actual route by at least a predetermined threshold value, and

if the expected route deviates from the actual route by at least the predetermined threshold value, determine a type of momentary driving maneuver of the vehicle and classifying the first mobility data and the second mobility data on a basis of the type of momentary driving maneuver.