Polynomial risk maps

• US 10,699,347 B1
• Filed: 09/19/2016
• Issued: 06/30/2020
• Est. Priority Date: 02/24/2016
• Status: Active Grant

• Current Assignee: Allstate Insurance Company (Allstate Corporation)
• Original Assignee: Allstate Insurance Company (Allstate Corporation)
• Inventors: Slusar, Mark, Madigan, Regina, Gibson, Timothy W.
• Primary Examiner(s): Apple, Kirsten S
• Application Number:
  US15/268,750
• Time in Patent Office: 1,380 Days
• Field of Search: 705 38
• CPC Class Codes: G01C 21/3461 Preferred or disfavoured areas, e.g. dangerous zones, toll or emission zones, intersections, manoeuvre types, segments such as motorways, toll roads, ferries
• CPC Class Codes: G01C 21/3667 Display of a road map G01C21/3614 takes precedence; guidance using 3D or perspective road maps G01C21/3635
• CPC Class Codes: G06Q 40/08 Insurance

Abstract

A system including a computing device may receive base map information, including attribute information associated with a plurality of road segments, and trip request information. Based on this information, a route for the user to travel may be determined. The system might further calculate a risk score for each road segment forming the route, and generate a risk map based on the risk score and the route. The risk map may then be displayed to a user. The risk map may include markers or other objects depicting potential risks along the route the driver may face. Also, the risk map may be updated based on information collected from a sensor coupled to the vehicle or located at the road segment to reflect actual, real-time risk scores calculated using an equation for providing a risk score for a particular driver driving a particular vehicle on a particular road segment.

Claims

1. A system comprising:

one or more sensors located on or alongside a specific road segment, the one or more sensors configured to;

detect sensor information indicating an attribute of the specific road segment; and

transmit the sensor information; and

a mobile computing device configured to;

receive trip request information indicating a destination of a trip to be traveled by a vehicle driven by a driver;

determine a route for the driver to travel in the vehicle based on the trip request information;

receive base map information, vehicle information, and driver information;

receive, from the one or more sensors via a wireless connection when the mobile computing device is within range of the one or more sensors, the sensor information;

assemble the sensor information, base map information, vehicle information, and driver information into one or more multivariable equations;

determine, using the one or more multivariable equations, a risk score for each road segment of a plurality of road segments forming the route to obtain a plurality of risk scores;

generate a risk map based on the plurality of risk scores; and

output, on a display, the risk map to the driver.

2. The system of claim 1,

wherein the base map information comprises volume data and accident data, and

wherein the volume data comprises information indicating a number of vehicles traveling over a particular road segment of the plurality of road segments, and the accident data comprises information indicating a number of accidents on the particular road segment.

3. The system of claim 1,

wherein the vehicle information comprises information indicating a make of the vehicle, a model of the vehicle, a year of the vehicle, a condition of brakes of the vehicle, a tire rating of a tire of the vehicle, whether the vehicle has running headlights, an engine size of the vehicle, or a type of transmission of the vehicle, and

wherein the vehicle information is received via an on-board diagnostic system.

4. The system of claim 1, wherein the driver information comprises information indicating a height of the driver, an eyesight test score associated with the driver, whether the driver wears glasses, an age of the driver, a number of years of driving experience of the driver, a number of accidents in which the driver has been involved, a number of traffic violations the driver has received, a type of traffic violation the driver has received, or a road or weather condition during an accident in which the driver has been involved.

5. The system of claim 1, wherein the mobile computing device is further configured to:

calculate, based on the plurality of risk scores, a route risk score; and

determine an insurance premium for traveling the route based on the route risk score.

6. The system of claim 1, wherein the mobile computing device is further configured to:

assemble the driver information into a driver risk score equation;

assemble the vehicle information into a vehicle risk score equation; and

assemble the one or more multivariable equations using the driver risk score equation and the vehicle risk score equation.

7. The system of claim 1, wherein the mobile computing device is further configured to:

determine that a particular risk score, of the plurality of risk scores, exceeds a threshold;

identify a particular road segment corresponding to the particular risk score;

update the risk map with a symbol that indicates the particular road segment is relatively dangerous; and

output, on the display, the updated risk map.

8. A method comprising:

receiving, by a mobile computing device, trip request information indicating a destination of a trip to be traveled by a vehicle driven by a driver;

determining, by the mobile computing device, a route for the driver to travel in the vehicle based on the trip request information;

receiving, by the mobile computing device via a wireless connection from one or more sensors located by a specific road segment, sensor information indicating an attribute of the specific road segment;

receiving, by the mobile computing device, driver information, vehicle information, and base map information;

generating, based on the sensor information, driver information, vehicle information, and base map information, one or more multivariable equations;

determining, using the one or more multivariable equations, a risk score for each road segment of a plurality of road segments forming the route to obtain a plurality of risk scores;

generating, by the mobile computing device, a risk map based on the plurality of risk scores; and

outputting, on a display, the risk map to the driver.

9. The method of claim 8,

wherein the base map information comprises volume data and accident data, and

wherein the volume data comprises information indicating a number of vehicles traveling over a particular road segment of the plurality of road segments, and the accident data comprises information indicating a number of accidents on the particular road segment.

10. The method of claim 8,

wherein the vehicle information comprises information indicating a make of the vehicle, a model of the vehicle, a year of the vehicle, a condition of brakes of the vehicle, a tire rating of a tire of the vehicle, whether the vehicle has running headlights, an engine size of the vehicle, or a type of transmission of the vehicle, and

wherein the vehicle information is received via an on-board diagnostic system.

11. The method of claim 8, wherein the driver information comprises information indicating a height of the driver, an eyesight test score associated with the driver, whether the driver wears glasses, an age of the driver, a number of years of driving experience of the driver, a number of accidents in which the driver has been involved, a number of traffic violations the driver has received, a type of traffic violation the driver has received, or a road or weather condition during an accident in which the driver has been involved.

12. The method of claim 8, further comprising:

calculating, based on the plurality of risk scores, a route risk score; and

determining, based on the route risk score, an insurance premium for traveling the route.

13. The method of claim 8, further comprising:

generating, based on the driver information, a driver risk score equation; and

generating, based on the vehicle information, a vehicle risk score equation,

wherein the one or more multivariable equations are generated using the driver risk score equation and the vehicle risk score equation.

14. The method of claim 8, further comprising:

determining whether any of the plurality of risk scores forming the route exceed a threshold;

in response to determining that a particular risk score exceeds the threshold, identifying a particular road segment corresponding to the particular risk score;

updating the risk map with an indicator highlighting the particular road segment; and

outputting, on the display, the updated risk map.

15. A non-transitory computer-readable storage medium storing computer-executable instructions that, when executed by a mobile computing device, cause the mobile computing device to:

receive trip request information indicating a destination of a trip to be traveled by a vehicle driven by a driver;

determine a route for the driver to travel in the vehicle based on the trip request information;

receive, via a wireless connection from one or more sensors located by a specific road segment, sensor information indicating an attribute of the specific road segment;

receive driver information, vehicle information, and base map information;

generate, based on the sensor information, driver information, vehicle information, and base map information, one or more multivariable equations;

determine, using the one or more multivariable equations, a risk score for each road segment of a plurality of road segments forming the route to obtain a plurality of risk scores;

generate a risk map based on the plurality of risk scores; and

output, on a display, the risk map to the driver.

16. The non-transitory computer-readable storage medium of claim 15,

wherein the sensor information indicates a slope of the specific road segment, a surface type of the specific road segment, that a pothole exists on the specific road segment, that the specific road segment is uneven, that the specific road segment is wet, a number of lanes of the specific road segment, a speed limit of the specific road segment, or that the specific road segment is under construction.

17. The non-transitory computer-readable storage medium of claim 15, wherein the driver information comprises information indicating a height of the driver, an eyesight test score associated with the driver, whether the driver wears glasses, an age of the driver, a number of years of driving experience of the driver, a number of accidents in which the driver has been involved, a number of traffic violations the driver has received, a type of traffic violation the driver has received, or a road or weather condition during an accident in which the driver has been involved.

18. The non-transitory computer-readable storage medium of claim 15, wherein the computer-executable instructions, when executed, further cause the mobile computing device to:

determine a driver risk score equation based on the driver information; and

determine a vehicle risk score equation based on the vehicle information;

determine a preliminary road segment risk score equation for the specific road segment based on the base map information and the sensor information;

determine a road segment risk score equation based on the driver risk score equation, the vehicle risk score equation, and the preliminary road segment risk score equation; and

execute the road segment risk score equation to determine a particular risk score for the specific road segment, wherein the particular risk score is one of the plurality of risk scores.

19. The non-transitory computer-readable storage medium of claim 15, wherein the computer-executable instructions, when executed, cause the mobile computing device to:

dynamically update the risk map based on the sensor information to add or remove a risk object overlaying a portion of the risk map corresponding to the specific road segment.

20. The non-transitory computer-readable storage medium of claim 15,

wherein the one or more sensors comprise a transceiver, and

wherein the sensor information comprises information obtained from another vehicle that passed by the one or more sensors at a time prior to the vehicle passing by the one or more sensors.