Contextual priority signal in autonomous environment

• US 10,363,866 B2
• Filed: 12/09/2016
• Issued: 07/30/2019
• Est. Priority Date: 12/09/2016
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Kline, Eric V., Rakshit, Sarbajit K., Shetty, Shilpa S.
• Primary Examiner(s): McPherson, James M
• Application Number:
  US15/374,103
• Publication Number:
  US 20180162267A1
• Time in Patent Office: 963 Days
• Field of Search: 701 23
• CPC Class Codes: B60Q 1/52 for indicating emergencies
• CPC Class Codes: B60Q 5/005 automatically actuated
• CPC Class Codes: B60W 2050/143 Alarm means
• CPC Class Codes: B60W 2050/146 Display means
• CPC Class Codes: B60W 2540/043 Identity of occupants
• CPC Class Codes: B60W 2540/221 Physiology, e.g. weight, heartbeat, health or special needs
• CPC Class Codes: B60W 2540/26 Incapacity
• CPC Class Codes: B60W 50/14 Means for informing the driver, warning the driver or prompting a driver intervention

Abstract

Determining contextual priority of an autonomous vehicle and whether the passengers have a genuine event based on priority input, which is greater than a threshold and is classified as an emergency, activating the notification system to alert other vehicles.

Claims

1. A method for determining contextual priority of an autonomous vehicle comprising a computer in communication with sensors and a notification system of the autonomous vehicle, the autonomous vehicle having at least one passenger, the method comprising the steps of:

the computer receiving one or more inputs regarding the at least one passenger in the autonomous vehicle to define an event, wherein at least one of the one or more inputs comprises manual input from the at least one passenger of a scan of a ticket of the at least one passenger, a pass of the at least one passenger, credentials of the at least one passenger or a badge of the at least one passenger;

the computer analyzing the input to determine whether the event is genuine;

for each event determined to be genuine, the computer calculating a score for the event; and

for each event with a calculated score greater than a threshold, the computer classifying the event as an emergency and activating the notification system to alert other vehicles.

2. The method of claim 1, wherein at least one of the one or more inputs comprises input gathered from the sensors within the autonomous vehicle.

3. The method of claim 1, wherein sensors within the autonomous vehicle are selected from a group consisting of:

cameras, speakers, microphones, seat belts, seat, wearable devices, global positioning system, and mobile devices of the at least one passenger.

4. The method of claim 3, wherein the sensors detect information regarding a passenger'"'"'s health.

5. The method of claim 1, wherein the notification system comprises an audible notification and a visible notification to other vehicles.

6. The method of claim 1, wherein the calculated score is based on data selected from a group consisting of:

a number of passengers impacted within the autonomous vehicle;

importance of a targeted activity of the event, distance between a current location of the autonomous vehicle and destination;

available time to reach a destination, and predicted time to reach the destination.

7. The method of claim 1, further comprising a step of:

the computer calculating a priority of the event classified as the emergency based on at least a number of people impacted, distance between the autonomous vehicle'"'"'s current location and a destination, importance of the emergency and a comparison between available time and predicted time to reach a destination, being based on the calculated priority, clustering and ranking other vehicles with a priority of an event classified as an emergency and assigning a rank of importance to the autonomous vehicle relative to the other vehicles.

8. A computer program product for determining contextual priority of an autonomous vehicle comprising a computer comprising at least one processor, one or more memories, one or more computer readable storage media, in communication with sensors and a notification system of the autonomous vehicle, the autonomous vehicle having at least one passenger, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by the computer to perform a method comprising:

receiving, by the computer, one or more inputs regarding the at least one passenger in the autonomous vehicle to define an event, wherein at least one of the one or more inputs comprises manual input from the at least one passenger of a scan of the ticket of the at least one passenger, a pass of the at least one passenger, credentials of the at least one passenger or a badge of the at least one passenger;

analyzing, by the computer, the input to determine whether the event is genuine;

for each event determined to be genuine, calculating, by the computer, a score for the event; and

for each event with a calculated score is greater than a threshold, classifying, by the computer, the event as an emergency and activating the notification system to alert other vehicles.

9. The computer program product of claim 8, wherein at least one of the one or more inputs comprises input gathered from the sensors within the autonomous vehicle.

10. The computer program product of claim 8, wherein sensors within the autonomous vehicle are selected from a group consisting of:

cameras, speakers, microphones, seat belts, seat, wearable devices, global positioning system, and mobile devices of the at least one passenger.

11. The computer program product of claim 8, wherein the notification system comprises an audible notification and a visible notification to other vehicles.

12. The computer program product of claim 8, wherein the calculated score is based on data selected from a group consisting of:

a number of passengers impacted within the autonomous vehicle;

importance of a targeted activity of the event, distance between a current location of the autonomous vehicle and destination;

available time to reach a destination, and predicted time to reach the destination.

13. A computer system for determining contextual priority of an autonomous vehicle comprising a computer in communication with sensors and a notification system of the autonomous vehicle, the autonomous vehicle having at least one passenger, the computer comprising at least one processor, one or more memories, one or more computer readable storage media having program instructions executable by the computer to perform the program instructions comprising:

receiving, by the computer, one or more inputs regarding the at least one passenger in the autonomous vehicle to define an event, wherein at least one of the one or more inputs comprises manual input from the at least one passenger of a scan of ticket of the at least one passenger, a pass of the at least one passenger, credentials of the at least one passenger or a badge of the at least one passenger;

analyzing, by the computer, the input to determine whether the event is genuine;

for each event determined to be genuine, calculating, by the computer, a score for the event; and

for each event with a calculated score is greater than a threshold, classifying, by the computer, the event as an emergency and activating the notification system to alert other vehicles.

14. The computer system of claim 13, wherein the at least one of the one or more inputs comprises input gathered from the sensors within the autonomous vehicle.

15. The computer system of claim 13, wherein sensors within the autonomous vehicle are selected from a group consisting of:

cameras, speakers, microphones, seat belts, seat, wearable devices, global positioning system, and mobile devices of the at least one passenger.

16. The computer system of claim 13, wherein the notification system comprises an audible notification and a visible notification to other vehicles.

17. The computer system of claim 13, wherein the calculated score is based on data selected from a group consisting of:

a number of passengers impacted within the autonomous vehicle;

importance of a targeted activity of the event, distance between a current location of the autonomous vehicle and destination;

available time to reach a destination, and predicted time to reach the destination.