COLLISION PREDICTION SYSTEM

• US 20170101093A1
• Filed: 10/13/2015
• Published: 04/13/2017
• Est. Priority Date: 10/13/2015
• Status: Active Grant

• Current Assignee: Verizon Patent and Licensing Incorporated (Verizon Communications Inc.)
• Original Assignee: Verizon Patent and Licensing Incorporated (Verizon Communications Inc.)
• Inventors: Barfield, Jr., James Ronald, Welch, Stephen Christopher
• Granted Patent: US 9,718,468 B2
• Time in Patent Office: Days
• CPC Class Codes: B60W 2400/00 Indexing codes relating to detected, measured or calculated conditions or factors
• CPC Class Codes: B60W 2420/40 Photo, light or radio wave sensitive means, e.g. infrared sensors
• CPC Class Codes: B60W 2420/403 Image sensing, e.g. optical camera
• CPC Class Codes: B60W 2420/54 Audio sensitive means, e.g. ultrasound
• CPC Class Codes: B60W 2540/10 Accelerator pedal position
• CPC Class Codes: B60W 2540/12 Brake pedal position
• CPC Class Codes: B60W 2540/18 Steering angle
• CPC Class Codes: B60W 2554/801 Lateral distance
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 2556/55 using telemetry
• CPC Class Codes: B60W 30/09 Taking automatic action to avoid collision, e.g. braking and steering
• CPC Class Codes: B60W 30/095 Predicting travel path or likelihood of collision
• CPC Class Codes: B60W 50/0097 Predicting future conditions
• CPC Class Codes: B60W 50/14 Means for informing the driver, warning the driver or prompting a driver intervention
• CPC Class Codes: G08G 1/096725 where the received information generates an automatic action on the vehicle control
• CPC Class Codes: G08G 1/09675 where a selection from the received information takes place in the vehicle
• CPC Class Codes: G08G 1/096775 where the origin of the information is a central station
• CPC Class Codes: G08G 1/16 Anti-collision systems road vehicle drive control systems for predicting or avoiding probable or impending collision otherwise than by control of a particular sub-unit B60W30/08
• CPC Class Codes: G08G 1/164 Centralised systems, e.g. external to vehicles
• CPC Class Codes: G08G 1/166 for active traffic, e.g. moving vehicles, pedestrians, bikes

Abstract

Information identifying one or more conditions associated with a vehicle is collected. This information may include first data associated with the vehicle, second data associated with a driver of the vehicle, and third data associated with an environment around the vehicle. The information may be collected from a vehicle sensor, a telematics unit, a user device associated with the driver or a passenger, or a remote server. A likelihood of a collision involving the vehicle, a likelihood of avoiding the collision, and a risk associated with the collision may be determined based on the collected data. An appropriate response may be selected based on the likelihood of the collision, the likelihood of avoiding the collision, and the risk associated with the collision.

Claims

1. A method comprising:

collecting, by a processor, information identifying one or more conditions associated with a vehicle, wherein the information includes first data associated with the vehicle, second data associated with a driver of the vehicle, and third data associated with an environment associated with the vehicle;

determining, by the processor and based on the collected information, a likelihood of a collision involving the vehicle;

determining, by the processor and based on the collected information, a likelihood of avoiding the collision;

determining, by the processor and based on the collected information, a risk associated with the collision;

selecting, by the processor, an action to perform based on at least one of the likelihood of the collision, the likelihood of avoiding the collision, and the risk associated with the collision; and

causing, by the processor, the action to be performed.

2. The method of claim 1, wherein collecting the information includes:

acquiring at least a portion of the first data from a telematics unit associated with the vehicle.

3. The method of claim 1, wherein collecting the information includes:

acquiring at least a portion of the second data from a user device associated with at least one of the driver or a passenger in the vehicle.

4. The method of claim 1, wherein collecting the information includes

acquiring the third data from at least one of:

an optical proximity sensor,

sonic proximity sensor,

a rangefinder, a 3D-scanner,

a microphone,

a video camera,

a speed sensor,

a steering wheel orientation sensor,

a break or accelerator application sensor,

a humidity sensor,

an accelerometer,

a gyroscope,

a geographic location sensor,

a turn signal sensors, or

a trailer attachment sensor.

5. The method of claim 1, wherein determining the likelihood of the collision includes:

identifying one or more events associated with other collisions or near-collisions; and

determining the likelihood of the collision based on frequencies that the one or more conditions occur in the identified one or more events.

6. The method of claim 5, wherein determining the likelihood of the collision further includes:

identifying a plurality of conditions associated with the one or more events;

generating a binary classification tree (BCT) based on the identified conditions, wherein the BCT includes nodes associated with the plurality of conditions and decisions associated with each of the nodes; and

determining the likelihood of the collision based on the BCT.

7. The method of claim 1, wherein determining the likelihood of avoiding the collision includes:

identifying one or more events associated with other collisions or near-collisions;

identifying a modification to the one or more conditions to form a modified set of conditions; and

determining the likelihood of avoiding the collision based on frequencies that the modified set of conditions occur in the identified one or more events.

8. The method of claim 1, wherein selecting the action includes:

determining a response score based on a weighted sum of the likelihood of the collision, the likelihood of avoiding the collision, and the risk associated with the collision;

selecting the action from a plurality of actions based on the response score.

9. The method of claim 8, wherein the plurality of actions includes:

storing at least a portion of the collected data when the response score is less than a first threshold;

presenting a warning to the driver when the response score is greater than the first threshold and less than a second threshold that is greater than the first threshold;

assuming partial control of the vehicle when the response score is greater than the second threshold and less than a third threshold that is greater than the first threshold and the second threshold; and

assuming total control of the vehicle when the response score is greater than the third threshold.

10. The method of claim 1, wherein the action includes preparing the vehicle for the collision, wherein preparing the vehicle for the collision includes modifying an operation of the vehicle to reduce the risk associated with the collision.

11. A device comprising:

a memory configured to store instructions; and

a processor configured to execute one or more of the instructions to

collect information identifying one or more conditions associated with a vehicle, wherein the information includes first data associated with the vehicle, second data associated with a driver of the vehicle, and third data associated with an environment associated with the vehicle;

determine, based on the collected information, a likelihood of a collision involving the vehicle;

determine, based on the collected information, a likelihood of avoiding the collision;

determine, based on the collected information, a risk associated with the collision;

select an action to perform based on at least one of the likelihood of the collision, the likelihood of avoiding the collision, and the risk associated with the collision.

12. The device of claim 11, wherein the processor, when collecting the information, is further configured to execute the one or more instructions to:

acquire at least a portion of the first data from a telematics unit associated with the vehicle.

13. The device of claim 11, wherein the processor, when collecting the information, is further configured to execute the one or more instructions to:

acquire at least a portion of the second data from a user device associated with at least one of the driver or a passenger in the vehicle.

14. The device of claim 11, wherein the processor, when collecting the information, is further configured to execute the one or more instructions to:

acquire at least a portion of the third data from a data server that is remote from the vehicle, wherein the third data relates to conditions regarding a route being traversed by the vehicle.

15. The device of claim 11, wherein the processor, when determining the likelihood of the collision, is further configured to execute the one or more instructions to:

identify one or more events associated with other collisions or near-collisions; and

determine the likelihood of the collision based on frequencies that the one or more conditions occur in the one or more events.

16. The device of claim 11, wherein the processor, when determining the likelihood of avoiding the collision, is further configured to execute the one or more instructions to:

identify one or more events associated with other collisions or near-collisions;

identify a modification to the one or more conditions to form a modified set of conditions; and

determine the likelihood of avoiding the collision based on occurrences of the modified set of conditions in the identified one or more events.

17. A non-transitory computer readable medium to store instruction, the instructions comprising:

one or more instructions that, when executed by a processor, cause the processor to;

collect information identifying one or more conditions associated with a vehicle, wherein the information includes first data associated with the vehicle, second data associated with a driver of the vehicle, and third data associated with an environment associated with the vehicle;

determine, based on the collected information, a likelihood of a collision involving the vehicle;

determine, based on the collected information, a likelihood of avoiding the collision;

determine, based on the collected information, a risk associated with the collision;

select an action to perform based on at least one of the likelihood of the collision, the likelihood of avoiding the collision, and the risk associated with the collision.

18. The non-transitory computer readable medium of claim 17, wherein the first data is collected from a telematics unit, and wherein the first data includes at least one of a vehicle speed, a fuel level, an engine temperature, intake manifold pressure, tire pressure, or coolant temperature.

19. The non-transitory computer readable medium of claim 17, wherein the second data is collected from a user device associated with at least one of the driver or a passenger in the vehicle, and wherein the second data includes at least one of:

an attention level of the driver,

a gender of the driver,

an age of the driver,

an amount of time the driver has driven during a time period,

a time of day when the second data is collected,

a vehicle type associated with the driver,

a driving experience level of the driver,

a historical driving pattern of the driver,

a familiarity of the driver with a geographic location associated with the vehicle, or

a medical condition associated with the driver.

20. The non-transitory computer readable medium of claim 17, wherein the third data is acquired from at least one of:

an optical proximity sensor,

sonic proximity sensor,

a rangefinder, a 3D-scanner,

a microphone,

a video camera,

a speed sensor,

a steering wheel orientation sensor,

a break or accelerator application sensor,

a humidity sensor,

an accelerometer,

a gyroscope,

a geographic location sensor,

a turn signal sensors, or

a trailer attachment sensor.