System and method for adverse vehicle event determination
A method for determining an adverse vehicle event, including: sampling sensor data an onboard vehicle system coupled to an ego-vehicle; at the onboard vehicle system, extracting a set of event parameters from the sensor data, wherein the vehicle event data is associated with a vehicle event occurring within the time interval; computing a loss probability based on the set of event parameters in response to the loss probability exceeding a threshold probability, transforming the set of event parameters into insurance claim data; and automatically transmitting the insurance claim data to an endpoint, wherein the endpoint is determined based on the participant identifier.
1. A method for automatically determining insurance claim data, comprising:
sampling interior image data over a time interval using an interior-facing camera of an onboard vehicle system rigidly coupled to an ego-vehicle;
sampling exterior image data over the time interval using an exterior-facing camera of the onboard vehicle system;
at a processor of the onboard vehicle system, determining a set of event parameters based on the interior image data and the exterior image data, wherein the set of event parameters comprises:
a first event parameter; and
a second event parameter comprising an acceleration associated with the ego-vehicle during the time interval, wherein the acceleration associated with the ego-vehicle is determined by:
determining a first velocity of an object depicted in a first frame of the exterior image data, wherein the first frame is captured at a first time point in the time interval,
determining a second velocity of the object depicted in a second frame of the exterior image data, wherein the second frame is captured at a second time point subsequent to the first time point, and
calculating the acceleration associated with the ego-vehicle based on the first velocity of the object and the second velocity of the object;
calculating a loss probability based on the acceleration;
in response to the loss probability exceeding a threshold probability, determining insurance data based on the set of event parameters; and
transmitting the insurance claim data to a receiving device.
2. The method of claim 1 , further comprising obtaining an accelerometer signal from an accelerometer at a time point prior to the time interval;
wherein the interior image data and the exterior image data are sampled in response to the accelerometer signal exceeding a threshold value.
3. The method of claim 2 , wherein, at the time point, the ego-vehicle is parked.
4. The method of claim 1 , wherein the act of calculating the loss probability comprises calculating the loss probability using an adverse vehicle event model.
5. The method of claim 1 , wherein the processor comprises a module trained based on vehicle event data provided by other onboard vehicle systems.
6. The method of claim 1 , wherein the act of sampling the exterior image data is performed in response to detecting a trigger.
7. The method of claim 1 , further comprising determining driver behavior data based on the interior image data; and
determining a fault status based on the driver behavior data;
wherein the insurance claim data is based on the fault status.
8. The method of claim 1 , wherein the insurance claim data comprises a claim cost.
9. The method of claim 1 , further comprising determining a number of occupants in the ego-vehicle.
10. The method of claim 1 , wherein the set of event parameters is determined by a claim adjustment module in the processor, wherein the claim adjustment module is trained based on vehicle event data.
11. The method of claim 1 , further comprising receiving an instruction from a mobile device of a user corresponding to a participant identifier, wherein the insurance claim data is transmitted in response to the instruction.
12. A method for automatically determining insurance claim data, comprising:
sampling interior image data over a time interval using an interior-facing camera of an onboard vehicle system rigidly coupled to an ego-vehicle;
sampling exterior image data over the time interval using an exterior-facing camera of the onboard vehicle system;
at a processor of the onboard vehicle system, determining a set of event parameters based on the interior image data and the exterior image data, wherein the set of event parameters comprises:
a first event parameter; and
a second event parameter comprising an attitudinal shift of the ego-vehicle during the time interval, wherein the attitudinal shift of the ego-vehicle is determined by:
determining a first position of an object depicted in a first frame of the exterior image data, wherein the first frame is captured at a first time point in the time interval,
determining a second position of the object or another object depicted in a second frame of the exterior image data, wherein the second frame is captured at a second time point subsequent to the first time point, and
calculating the attitudinal shift of the ego-vehicle based on the first position and the second position;
calculating a loss probability based on the attitudinal shift;
in response to the loss probability exceeding a threshold probability, determining insurance data based on the set of event parameters; and
transmitting the insurance claim data to a receiving device.
13. The method of claim 12 , further comprising obtaining an accelerometer signal from an accelerometer at a time point prior to the time interval;
wherein the interior image data and the exterior image data are sampled in response to the accelerometer signal exceeding a threshold value.
14. The method of claim 13 , wherein, at the time point, the ego-vehicle is parked.
15. The method of claim 12 , wherein the processor comprises a module trained based on vehicle event data provided by other onboard vehicle systems.
16. The method of claim 12 , wherein the act of sampling the exterior image data is performed in response to detecting a trigger.
17. The method of claim 12 , further comprising determining driver behavior data based on the interior image data; and
determining a fault status based on the driver behavior data;
wherein the insurance claim data is based on the fault status.
18. The method of claim 12 , wherein the insurance claim data comprises a claim cost.
19. The method of claim 12 , further comprising determining a number of occupants in the ego-vehicle.
20. The method of claim 12 , wherein the set of event parameters is determined by a claim adjustment module in the processor, wherein the claim adjustment module is trained based on vehicle event data.
21. The method of claim 12 , further comprising receiving an instruction from a mobile device of a user corresponding to a participant identifier, wherein the insurance claim data is transmitted in response to the instruction.