Vehicle classification system

• US 10,810,871 B2
• Filed: 06/29/2018
• Issued: 10/20/2020
• Est. Priority Date: 06/29/2018
• Status: Active Grant

• Current Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Original Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Inventors: Visintainer, Randal Henry, Rao, Rajendra, Lockwood, John A
• Primary Examiner(s): Dunn, Alex C
• Application Number:
  US16/023,255
• Publication Number:
  US 20200005631A1
• Time in Patent Office: 844 Days
• CPC Class Codes: B60W 2420/403 Image sensing, e.g. optical camera
• CPC Class Codes: B60W 2420/408 Radar; Laser, e.g. lidar
• CPC Class Codes: B60W 2554/402 Type
• CPC Class Codes: B60W 2554/404 Characteristics
• CPC Class Codes: B60W 2554/4045 Intention, e.g. lane change or imminent movement
• CPC Class Codes: B60W 2556/45 External transmission of data to or from the vehicle
• CPC Class Codes: B60W 30/09 Taking automatic action to avoid collision, e.g. braking and steering
• CPC Class Codes: B60W 30/0956 the prediction being responsive to traffic or environmental parameters
• CPC Class Codes: B60W 40/04 Traffic conditions
• CPC Class Codes: B60W 60/0015 specially adapted for safety
• CPC Class Codes: G06F 2218/12 Classification; Matching
• CPC Class Codes: G06K 19/06037 multi-dimensional coding
• CPC Class Codes: G06V 10/143 Sensing or illuminating at different wavelengths
• CPC Class Codes: G06V 20/58 Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
• CPC Class Codes: G06V 2201/08 Detecting or categorising vehicles
• CPC Class Codes: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C
• CPC Class Codes: G08G 1/017 identifying vehicles G08G1/015, G08G1/054 take precedence
• CPC Class Codes: G08G 1/04 using optical or ultrasonic detectors

Abstract

A vehicle bears labels describing handling characteristics of the vehicle for the benefit of autonomous vehicles in proximity to the vehicle. The labels may be nonvisible, such as through use of UV or IR inks. The labels may be present such that they are visible regardless of view direction and may be affixed using a vehicle wrap applied to panels of the vehicle. Autonomous vehicles detect the labels and retrieve handling characteristics from a local database or a remote server. The autonomous vehicles are therefore relieved from the processing required to predict or infer the handling characteristics of the vehicle.

Claims

1. A vehicle comprising:

a vehicle body;

a power source, wheels, and a drive train; and

a covering on the outside of the vehicle body having a plurality of encoded labels distributed over front, rear, left, and right sides of the vehicle body, the encoded labels encoding data describing a handling characteristic of the vehicle.

2. The vehicle of claim 1, wherein the covering is a wrap covering a plurality of panels of the body.

3. The vehicle of claim 1, wherein the handling characteristic of the vehicle is a classification of the vehicle.

4. The vehicle of claim 1, wherein the handling characteristic of the vehicle is a usage of the vehicle.

5. The vehicle of claim 1, wherein the encoded labels are non-visible to a human eye.

6. The vehicle of claim 5, wherein the encoded labels are only visible at wavelengths larger than 700 nanometers.

7. The vehicle of claim 5, wherein the encoded labels are only visible at wavelengths smaller than 400 nanometers.

8. A method comprising:

receiving, by a vehicle controller of a first vehicle, sensor data from exterior sensors mounted to the first vehicle, the exterior sensors including a camera;

evaluating, by the vehicle controller, an image included in the sensor data;

identifying, by the vehicle controller, a second vehicle having an encoded label in the image;

decoding, by the vehicle controller, the encoded label to obtain a handling characteristic of the second vehicle; and

performing obstacle avoidance with respect to the second vehicle based on the sensor data and the handling characteristic.

9. The method of claim 8, wherein the sensor data includes outputs from at least one of a light detection and ranging (LIDAR) sensor and a radio detection and ranging (RADAR) sensor.

10. The method of claim 8, further comprising capturing the image by the camera by detecting light with wavelengths not visible to a human eye.

11. The method of claim 8, further comprising capturing the image by the camera by detecting wavelengths larger than 700 nanometers.

12. The method of claim 8, further capturing the image by the camera by detecting wavelengths smaller than 400 nanometers.

13. The method of claim 8, wherein decoding the encoded label comprises:

extracting, by the vehicle controller, an identifier from the encoded label;

transmitting, by the vehicle controller, the identifier to a remote server; and

receiving, by the vehicle controller, the handling characteristic from the remote server.

14. The method of claim 8, wherein decoding the encoded label comprises:

extracting, by the vehicle controller, an identifier from the encoded label;

retrieving, by the vehicle controller, the handling characteristic from an entry in a database stored in the vehicle, the entry corresponding to the identifier.

15. The method of claim 8, wherein the handling characteristic of the vehicle is a classification of the vehicle.

16. The method of claim 8, wherein the handling characteristic of the vehicle is a usage of the vehicle.

17. A method comprising:

providing a vehicle including a plurality of body panels, a power source, wheels, and a drive train;

encoding a handling characteristic of the vehicle in a label; and

applying a wrap to the plurality of body panels such that the wrap completely covers the plurality of body panels, the wrap having copies of the label distributed throughout the wrap such that copies of the label are located on front, rear, left, and right sides of the vehicle body, the encoded labels encoding data describing a handling characteristic of the vehicle.

18. The method of claim 17, wherein the handling characteristic includes at least one of a classification and usage of the vehicle.

19. The method of claim 17, wherein the copies of the label are only visible at wavelengths larger than 700 nanometers.

20. The method of claim 17, wherein the copies of the label are only visible at wavelengths smaller than 400 nanometers.