Accident Calculus

• US 20190027038A1
• Filed: 02/15/2017
• Published: 01/24/2019
• Est. Priority Date: 02/15/2016
• Status: Active Grant

• Current Assignee: Allstate Insurance Company (Allstate Corporation)
• Original Assignee: Allstate Insurance Company (Allstate Corporation)
• Inventors: Chintakindi, Sunil, Madigan, Regina, Slusar, Mark V., Gibson, Timothy W.
• Granted Patent: US 11,138,884 B2
• Time in Patent Office: Days
• CPC Class Codes: B60R 21/0134 responsive to imminent contact with an obstacle , e.g. using radar systems
• CPC Class Codes: B60W 30/08 Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
• CPC Class Codes: B60W 30/09 Taking automatic action to avoid collision, e.g. braking and steering
• CPC Class Codes: B62D 6/001 the torque NOT being among the input parameters
• CPC Class Codes: G01S 19/42 Determining position
• CPC Class Codes: G08G 1/164 Centralised systems, e.g. external to vehicles
• CPC Class Codes: G08G 1/165 for passive traffic, e.g. including static obstacles, trees
• CPC Class Codes: G08G 1/166 for active traffic, e.g. moving vehicles, pedestrians, bikes

Abstract

Systems and methods are disclosed for determining that an adverse driving event is likely to occur and utilizing accident calculus algorithms to determine and cause vehicle driving actions necessary to mitigate consequences of the adverse driving event. After determining that an adverse driving event is likely to occur, a computing device my forecast consequences of the driving event. The computing device may determine potential evasive maneuvers that may be taken responsive to the adverse driving event. Additionally, the computing device may determine consequences associated with the potential evasive maneuvers and assign a weight relative to the consequence. The computing device may compare the potential driving maneuvers based on the weighted consequences to determine a driving maneuver to take.

Claims

1. A method comprising:

receiving surroundings and conditions data signifying an impending driving event;

forecasting one or more consequences of the impending driving event using an accident calculus algorithm;

determining a plurality of potential evasive maneuvers, wherein each of the plurality of potential evasive maneuvers is associated with one or more consequences;

comparing, based on a weight associated with each of the one or more consequences of the impending driving event, the potential evasive maneuvers;

determining, based on the comparison, a first evasive maneuver of the plurality of potential evasive maneuvers to perform; and

causing the first evasive maneuver to occur.

2. The method of claim 1, further comprising:

responsive to causing the first evasive maneuver to occur, receiving additional surroundings and conditions data;

determining if the additional surroundings and conditions data signifies an additional impending driving event; and

in response to determining that the additional surroundings and conditions data signifies an additional impending driving event;

forecasting one or more additional consequences of the additional impending driving event using the accident calculus algorithm;

determining a plurality of additional potential evasive maneuvers, wherein each of the plurality of additional potential evasive maneuvers is associated with one or more additional consequences;

comparing, based on a weight associated with each of the one or more additional consequences of the additional impending driving, the additional potential evasive maneuvers;

determining, based on the comparison, a second evasive maneuver of the plurality of potential evasive maneuvers to perform; and

causing the second evasive maneuver to occur.

3. The method of claim 1, further comprising:

responsive to causing the first evasive maneuver to occur, receiving additional surroundings and conditions data;

determining if the additional surroundings and conditions data signifies an additional impending driving event; and

in response to determining that the additional surroundings and conditions data does not signifies an additional impending driving event, performing debriefing functions.

4. The method of claim 1, wherein determining a plurality of potential evasive maneuvers further includes:

determining safety response measures associated with each evasive maneuver of the plurality of evasive maneuvers.

5. The method of claim 1, wherein the surroundings and conditions data are provided by one or more sensors of a vehicle associated with the impending driving event.

6. The method of claim 1, further comprising:

receiving ancillary data regarding one or more peripheral entities involved in the impending driving event; and

forecasting, based on the surroundings and conditions data and ancillary data, the one or more consequences of the impending driving event using the accident calculus algorithm.

7. The method of claim 6, wherein forecasting the one or more consequences comprises:

determining initial effects caused by the impending driving event; and

determining cascading effects caused to the one or more peripheral entities responsive to the initial effects.

8. An apparatus comprising:

a processor; and

memory storing computer-executable instructions that, when executed by the processor, cause the apparatus to;

receive surroundings and conditions data signifying an impending driving event;

forecast one or more consequences of the impending driving event using an accident calculus algorithm;

determine a plurality of potential evasive maneuvers, wherein the each of the plurality of potential evasive maneuvers is associated with one or more consequences;

compare, based a weight associated with each of the one or more consequences of the impending driving event, the potential evasive maneuvers;

determine, based on the comparison, a first evasive maneuver of the plurality of potential evasive maneuvers to perform; and

cause the first evasive maneuver to occur.

9. The apparatus of claim 8, the memory storing further computer-executable instructions that, when executed by the processor, cause the apparatus to:

responsive to causing the first evasive maneuver to occur, receive additional surroundings and conditions data;

determine if the additional surroundings and conditions data signifies an additional impending driving event;

in response to determining that the additional surroundings and conditions data signifies an additional impending driving event;

forecast one or more additional consequences of the additional impending driving event using the accident calculus algorithm;

determine a plurality of additional potential evasive maneuvers, wherein each of the plurality of additional potential evasive maneuvers is associated with one or more additional consequences;

compare, based on a weight associated with each of the one or more additional consequences of the additional impending driving event, the additional potential evasive maneuvers;

determine, based on the comparison, a second evasive maneuver of the plurality of potential evasive maneuvers to perform; and

cause the second evasive maneuver to occur.

10. The apparatus of claim 8, the memory storing further computer-executable instructions that, when executed by the processor, cause the apparatus to:

responsive to causing the first evasive maneuver to occur, receive additional surroundings and conditions data;

determine if the additional surroundings and conditions data signifies an additional impending driving event; and

in response to determining that the additional surroundings and conditions data does not signifies an additional impending driving event, perform debriefing functions.

11. The apparatus of claim 8, the memory storing further computer-executable instructions that, when executed by the processor, cause the apparatus to:

determine safety response measures associated with each evasive maneuver of the plurality of evasive maneuvers.

12. The apparatus of claim 8, wherein the surroundings and conditions data are provided by one or more sensors of a vehicle associated with the impending driving event.

13. The apparatus of claim 8, the memory storing further computer-executable instructions that, when executed by the processor, cause the apparatus to:

receive ancillary data regarding one or more peripheral entities involved in the impending driving event; and

forecast, based on the surroundings and conditions data and ancillary data, the one or more consequences of the impending driving event using the accident calculus algorithm.

14. The apparatus of claim 13, the memory storing further computer-executable instructions that, when executed by the processor, cause the apparatus to:

determine initial effects caused by the impending driving event; and

determine cascading effects caused to the one or more peripheral entities responsive to the initial effects.

15. One or more non-transitory computer readable storage media storing computer readable instructions that, when executed, cause a computer to perform:

receiving surroundings and conditions data signifying an impending driving event;

forecasting one or more consequences of the impending driving event using an accident calculus algorithm;

determining a plurality of potential evasive maneuvers, wherein each of the plurality of potential evasive maneuvers is associated with one or more consequences;

comparing, based on a weight associated with each of one or more consequences of the impending driving event, the potential evasive maneuvers;

determining, based on the comparison, a first evasive maneuver of the plurality of potential evasive maneuvers to perform; and

causing the first evasive maneuver to occur.

16. The one or more non-transitory computer readable storage media of claim 15, storing further instructions that, when executed, cause the computer to perform:

responsive to causing the first evasive maneuver to occur, receiving additional surroundings and conditions data;

determining if the additional surroundings and conditions data signifies an additional impending driving event;

in response to determining that the additional surroundings and conditions data signifies an additional impending driving event;

forecasting one or more additional consequences of the additional impending driving event using the accident calculus algorithm;

determining a plurality of additional potential evasive maneuvers, wherein each of the plurality of additional potential evasive maneuvers is associated with one or more additional consequences;

comparing, based on a weight associated with each of the one or more additional consequences of the additional impending driving event, the additional potential evasive maneuvers;

determining, based on the comparison, a second evasive maneuver of the plurality of potential evasive maneuvers to perform; and

causing the second evasive maneuver to occur.

17. The one or more non-transitory computer readable storage media of claim 15, storing further instructions that, when executed, cause the computer to perform:

responsive to causing the first evasive maneuver to occur, receiving additional surroundings and conditions data;

determining if the additional surroundings and conditions data signifies an additional impending driving event; and

in response to determining that the additional surroundings and conditions data does not signifies an additional impending driving event, performing debriefing functions.

18. The one or more non-transitory computer readable storage media of claim 15, storing further instructions that, when executed, cause the computer to perform:

determining safety response measures associated with each evasive maneuver of the plurality of evasive maneuvers.

19. The one or more non-transitory computer readable storage media of claim 15, wherein the surroundings and conditions data are provided by one or more sensors of a vehicle associated with the impending driving event.

20. The one or more non-transitory computer readable storage media of claim 15, storing further instructions that, when executed, cause the computer to perform:

receiving ancillary data regarding one or more peripheral entities involved in the impending driving event; and

forecasting, based on the surroundings and conditions data and ancillary data, the one or more consequences of the impending driving event using the accident calculus algorithm.