Systems and Methods for Determining a Vehicle is at an Elevated Risk for an Animal Collision

• US 20150343947A1
• Filed: 12/09/2014
• Published: 12/03/2015
• Est. Priority Date: 05/30/2014
• Status: Active Grant

• Current Assignee: State Farm Mutual Automobile Insurance Company (State Farm)
• Original Assignee: State Farm Mutual Automobile Insurance Company (State Farm)
• Inventors: Bernico, Michael, Sanidas, Tim G., Mowery, Milton, Zimmer, Christopher
• Granted Patent: US 10,166,916 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: B60Q 9/00 Arrangement or adaptation of signal devices not provided for in one of main groups B60Q1/00 - B60Q7/00 , e.g. haptic signalling
• CPC Class Codes: G06Q 40/08 Insurance
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0129 for creating historical data or processing based on historical data
• CPC Class Codes: G08G 1/0141 for traffic information dissemination
• CPC Class Codes: G08G 1/096716 where the received information does not generate an automatic action on the vehicle control
• CPC Class Codes: G08G 1/096741 where the source of the transmitted information selects which information to transmit to each vehicle
• CPC Class Codes: G08G 1/096775 where the origin of the information is a central station

Abstract

Methods and systems for analyzing environment data to determine whether a vehicle operator is at an elevated risk for an animal collision are provided. According to certain aspects, an insurance provider may assess elevated risk according to various factors and, if it is determined that the vehicle operator is at an elevated risk for an animal collision, the insurance provider may generate a warning and wirelessly communicate the warning to the vehicle operator. The factors analyzed may include past accident, driver characteristic, weather, calendar, time of day, animal, seasonal, and/or other information. The vehicle operator may be notified of the risk and optionally presented with tips to mitigate the risk. The vehicle operator may be notified of the risk by a mobile device and/or the vehicle, such as from a vehicle communication and control system. Animal collision avoidance functionality may be used to adjust insurance premiums, rates, or rewards.

Claims

1. A computer-implemented method of processing vehicle collision risk information, the method comprising:

receiving, at a hardware server, vehicle data indicating at least a location of a vehicle;

accessing, by a processor, environment data associated with the location of the vehicle;

based on the environment data, determining, by the processor, that the vehicle is at an elevated risk for an animal collision;

generating, by the processor, a notification indicating the elevated risk; and

communicating, via a communications network, the notification to the vehicle.

2. The computer-implemented method of claim 1, wherein communicating the notification to the vehicle comprises:

communicating the notification to at least one of an onboard computer of the vehicle and an electronic device associated with an operator of the vehicle.

3. The computer-implemented method of claim 1, wherein receiving the vehicle data comprises:

receiving at least one of a speed of the vehicle, vehicle characteristics, and demographic information associated with an operator of the vehicle.

4. The computer-implemented method of claim 1, wherein accessing the environment data comprises:

accessing at least one of;

a historical record of accidents, ecological characteristics, and roadway characteristics.

5. The computer-implemented method of claim 1, wherein determining that the vehicle is at the elevated risk comprises:

determining, from the environment data, that a previous accident has occurred at or near the location of the vehicle.

6. The computer-implemented method of claim 1, wherein the environment data includes a first environment factor having a first specific weight and a second environment factor having a second specific weight, and wherein determining that the vehicle is at an elevated risk comprises:

calculating an overall risk based on combining the first environment factor and the second environment factor.

7. The computer-implemented method of claim 1, wherein determining that the vehicle is at the elevated risk comprises:

identifying at least one of a time of day and a time of year; and

determining, from a portion of the environment data corresponding to the at least one of the time of day and the time of year, that the vehicle is at the elevated risk.

8. The computer-implemented method of claim 1, further comprising:

receiving, at the hardware server, an animal collision report indicating that the vehicle collided with an animal.

9. The computer-implemented method of claim 8, wherein determining that the vehicle is at the elevated risk includes executing a machine learning algorithm.

10. The computer-implemented method of claim 8, further comprising:

updating the machine learning algorithm according to the animal collision report.

12. The system of claim 1, wherein to communicate the notification to the vehicle, the communication module is configured to:

communicate the notification to at least one of an onboard computer of the vehicle and an electronic device associated with an operator of the vehicle.

11. A system for processing vehicle collision risk information, comprising:

a communication module adapted to communicate data;

a memory adapted to store non-transitory computer executable instructions;

a hardware server to store environment data; and

a processor adapted to interface with the communication module, wherein the processor is configured to execute the non-transitory computer executable instructions to cause the processor to;

receive, via the communication module, vehicle data indicating at least a location of a vehicle,

access, via the processor, at least a portion of the environment data associated with the location of the vehicle,

based on the environment data, determine, via the processor, that the vehicle is at an elevated risk for an animal collision,

generate, via the processor, a notification indicating the elevated risk, and

communicate, via the communication module, the notification to the vehicle.

13. The system of claim 11, wherein to receive the vehicle data, the hardware server is configured to:

receive at least one of a speed of the vehicle, vehicle characteristics, and demographic information associated with an operator of the vehicle.

14. The system of claim 11, wherein to facilitate accessing the environment data, the processor is configured to execute the non-transitory computer executable instructions to cause the processor to:

access at least one of;

a historical record of accidents, ecological characteristics, and roadway characteristics.

15. A computer-implemented method of issuing an alert associated with a vehicle-animal collision, the method comprising:

predicting (1) a geographical scope, (2) a temporal scope, and (3) a seasonal scope of an area at high risk of being associated with a vehicle-animal collision;

monitoring or identifying a current location of a mobile device via a processor;

monitoring or identifying a current time of day via the processor;

monitoring or identifying a current time of year via the processor; and

when, as determined by the processor, that (a) the current location of the mobile device matches or falls within the geographical scope of the area at high risk, (b) the current time of day matches, falls within, or coincides with the temporal scope of the area at high risk, and (c) the current time of year matches, falls within, or coincides with the seasonal scope of the area at high risk causing the mobile device to issue an alert to the user.

16. The computer-implemented method of claim 15, wherein the alert or warning is an audible, visual, or haptic alert or warning.

17. The computer-implemented method of claim 15, the method further comprising the processor determining whether or not the vehicle is moving before issuing the alert or warning.

18. The computer-implemented method of claim 15, wherein predicting (1) the geographical scope, (2) the temporal scope, and (3) the seasonal scope of the area at high risk of being associated with a vehicle-animal collision comprises analyzing a database of actual vehicle collisions involving vehicles and animals.

19. The computer-implemented method of claim 15, wherein predicting the area at high risk of being associated with a vehicle-animal collision further comprises analyzing automobile accidents, driver characteristics, animal tendencies, weather, calendar, time of day, geographical information.

20. The computer-implemented method of claim 15, the method further comprising adjusting an insurance premium, discounts, or reward based upon animal collision avoidance functionality.