DETERMINING A PARKING POSITION BASED ON VISUAL AND NON-VISUAL FACTORS

• US 20170236418A1
• Filed: 05/04/2017
• Published: 08/17/2017
• Est. Priority Date: 09/11/2015
• Status: Active Grant

• Current Assignee: DoorDash, Inc.
• Original Assignee: International Business Machines Corporation
• Inventors: Ganci, JR., John M., Keen, Martin G., Bostick, James E., Rakshit, Sarbajit K.
• Granted Patent: US 9,953,531 B2
• Time in Patent Office: Days
• CPC Class Codes: B62D 15/0285 Parking performed automatically
• CPC Class Codes: G06V 20/586 of parking space
• CPC Class Codes: G06V 2201/08 Detecting or categorising vehicles
• CPC Class Codes: G08G 1/0175 by photographing vehicles, e.g. when violating traffic rules
• CPC Class Codes: G08G 1/143 inside the vehicles

Abstract

A computer-implemented method includes: receiving, by a computing device, images of adjacent vehicles parked directly adjacent to an open parking space; determining, by the computing device, visual factors and non-visual factors of the adjacent vehicles based on the images; determining, by the computing device, risk scores for each of the adjacent vehicles based on the visual factor and the non-visual factors; determining, by the computing device, a parking position within the open parking space based on the risk scores; and outputting, by the computing device, information regarding the parking position.

Claims

1. A computer-implemented method comprising:

receiving, by a computing device, images of a plurality of adjacent vehicles parked directly adjacent to an open parking space;

determining, by the computing device, visual factors and non-visual factors of the plurality of adjacent vehicles based on the images by obtaining data from a dedicated database;

determining, by the computing device, a parking position within the open parking space based on the visual and non-visual factors; and

outputting, by the computing device, information regarding the parking position.

2. The method of claim 1, wherein the images are received from one or more camera devices implemented in an autonomous vehicle.

3. The method of claim 1, wherein the parking position is closer to one of the plurality of adjacent vehicles having visual factors and non-visual factors indicating a lower risk than another one of the plurality of adjacent vehicles.

4. The method of claim 1, wherein the determining the non-visual factors is based on vehicle identification information included in the images.

5. The method of claim 1, wherein the images are received from one or more camera devices associated with a parking facility.

6. The method of claim 1, wherein the visual factors include one or more of:

overall vehicle size;

door size;

door type;

condition; and

distance to another adjacent parked vehicle.

7. The method of claim 1, wherein the non-visual factors include one or more of:

vehicle history information,

driver accident history information,

driver behavior information,

driver experience information, and

published vehicle data.

8. The method of claim 1, wherein at least one of the visual and the non-visual factors are weighted.

9. The method of claim 1, further comprising:

determining a risk score for the open parking space based on the visual and non-visual factors of each adjacent vehicle of the plurality of adjacent vehicles; and

outputting the risk score for the open parking space.

10. The method of claim 1, wherein a service provider at least one of creates, maintains, deploys and supports the computing device.

11. The method of claim 1, wherein the receiving the images the determining the visual factors and the non-visual factors, the determining the parking position, and the outputting the information regarding the parking position are provided by a service provider on a subscription, advertising, and/or fee basis.

12. The method of claim 1, wherein the computing device includes software provided as a service in a cloud environment.

13. The method of claim 1, further comprising deploying a system for selecting a parking space and providing navigation direction to the selected parking space, comprising providing a computer infrastructure operable to perform the receiving the images the determining the visual factors and the non-visual factors, the determining the parking position, and the outputting the information regarding the parking position.

14. A computer program product for determining a parking position for a vehicle, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions being executable by a computing device to cause the computing device to:

receive images of a plurality of adjacent vehicles parked directly adjacent to an open parking space when a user of an autonomous vehicle instructs the autonomous vehicle to park in the open parking space;

determine visual factors and non-visual factors of the plurality of adjacent vehicles based on the images;

determine a parking position within the parking space based on the visual factors and non-visual factors; and

output information regarding the parking position to the user of the autonomous vehicle or to a vehicle interface system of the autonomous vehicle to cause the autonomous vehicle to park in the open space in accordance with the determined parking position.

15. The system of claim 14, wherein the parking position is closer to one of the plurality of adjacent vehicles having visual factors and non-visual factors indicating a lower risk than another one of the plurality of adjacent vehicles.

16. The system of claim 14, wherein the program instructions to determine the non-visual factors cause the computing device to determine the non-visual factors based on vehicle identification information included in the images.

17. The system of claim 14, wherein the visual factors include one or more of:

overall vehicle size;

vehicle door size;

vehicle door type;

vehicle condition;

driver experience information; and

distance to another adjacent parked vehicle.

18. The system of claim 14, wherein the non-visual factors include one or more of:

vehicle history information;

driver accident history information;

driver behavior information;

driver experience information; and

published vehicle data.

19. A system comprising:

a CPU, a computer readable memory and a computer readable storage medium associated with a computing device;

program instructions to receive images of adjacent vehicles parked directly adjacent to an open parking space;

program instructions to determine visual factors and non-visual factors of the adjacent vehicles based on the images;

program instructions to determine a risk score for the open parking space based on the visual factors and non-visual factors of each adjacent vehicle; and

program instructions to output the risk score for the open parking space,

wherein the program instructions are stored on the computer readable storage medium for execution by the CPU via the computer readable memory.

20. The system of claim 19, further comprising program instructions to determine a parking position within the parking space based on the visual factors and non-visual factors;

and

program instructions to output information regarding the parking position.