System and method for adverse vehicle event determination

1. A method for determining an adverse vehicle event, comprising:

sampling sensor data over a time interval using an onboard vehicle system rigidly coupled to an ego-vehicle;

at a processor of the onboard vehicle system, determining a set of event parameters, wherein at least one of the event parameters is based on the sensor data, wherein the event parameters are associated with a vehicle event occurring within the time interval, wherein the set of event parameters comprises:

a first event parameter comprising a participant identifier,

a second event parameter comprising an acceleration of the ego-vehicle during the time interval, and

a third event parameter comprising an attitudinal shift of the ego-vehicle during the time interval;

computing a loss probability based on the attitudinal shift or based on both the acceleration and the attitudinal shift, wherein the loss probability indicates a probability of property loss and/or personal injury;

in response to the loss probability exceeding a threshold probability, determining insurance claim data based on one or more of the event parameters; and

transmitting the insurance claim data to a recipient;

wherein the sensor data comprise image data, and wherein the act of determining the third event parameter comprising the attitudinal shift of the ego-vehicle comprises:

determining a first position of an object depicted in a first frame of the image data at a first time point within the time interval;

determining a second position of the object or another object depicted in a second frame of the image data at a second time point within the time interval subsequent to the first time point; and

calculating the attitudinal shift of the ego-vehicle based on the first position and the second position.

2. The method of claim 1 , wherein the act of sampling the image data is performed at a monocular camera of the onboard vehicle system.

3. The method of claim 1 , wherein the act of sampling the image data is performed in response to detecting a trigger.

4. The method of claim 3 , further comprising sampling an accelerometer signal from an accelerometer of the onboard vehicle system at a time point prior to the time interval, wherein the trigger comprises the accelerometer signal exceeding a threshold value.

5. The method of claim 1 , further comprising:

determining driver behavior data corresponding to a driver of the ego-vehicle based on the image data; and

determining a fault status associated with the driver based on the driver behavior data;

wherein the insurance claim data is determined based also on the fault status.

6. The method of claim 5 , wherein the act of determining the insurance claim data comprises estimating a claim cost based on the loss probability and the fault status.

7. The method of claim 1 , further comprising determining a number of occupants in the ego-vehicle during the time interval.

8. The method of claim 1 , further comprising training a claim adjustment module based on other sets of event parameters determined from sensor data sampled by one or more other onboard vehicle systems of one or more other ego-vehicles, and wherein the insurance claim data is determined using the claim adjustment module.

9. The method of claim 1 , further comprising prompting a person involved in the vehicle event to provide a transmission instruction at a mobile device associated with the person, and wherein the insurance claim data is transmitted in response to receiving the transmission instruction.

10. The method of claim 1 , wherein the act of determining the second event parameter comprising the acceleration comprises:

determining a first velocity of an object represented in the image data;

determining a second velocity of the object or another object represented in the image data; and

calculating the acceleration of the ego-vehicle based on the first velocity and the second velocity.

11. The method of claim 10 , wherein the loss probability is determined using an adverse vehicle event model, wherein the adverse vehicle event model is trained based on other event parameters associated with other ego-vehicles and corresponding insurance claim data.

12. The method of claim 1 , wherein the acceleration comprises a single peak acceleration value, and wherein the attitudinal shift comprises a single peak attitudinal shift value.

13. A method for determining an adverse vehicle event, comprising:

obtaining event parameters associated with a vehicle event occurring within a time interval, wherein the event parameters are sensor data or are based on the sensor data provided by an onboard vehicle system, wherein the event parameters comprise:

an acceleration of a vehicle, and

an attitudinal shift of the vehicle;

determining insurance claim data based on one or more of the event parameters;

determining, by a processing unit, a loss probability indicating a probability of property loss and/or personal injury, wherein the processing unit determining the loss probability is configured to obtain (1) the attitudinal shift or (2) both of the acceleration and the attitudinal shift as input; and

in response to the loss probability exceeding a threshold probability, transmitting the insurance claim data to a recipient;

wherein the attitudinal shift of the vehicle is based on:

a first position of an object depicted in a first frame of image data at a first time point within the time interval; and

a second position of the object or another object depicted in a second frame of the image data at a second time point within the time interval subsequent to the first time point.

14. The method of claim 13 , wherein the act of obtaining the event parameters, the act of determining the loss probability, the act of determining the insurance claim data, and the act of transmitting the insurance claim data, are performed by a system that is in communication with the onboard vehicle system.

15. The method of claim 13 , further comprising obtaining a participant identifier indicating an identity of a participant involved in the vehicle event.

16. The method of claim 15 , further comprising determining the recipient to which the insurance claim data are to be transmitted, wherein the recipient is determined based on the participant identifier.

17. The method of claim 13 , wherein the acceleration of the vehicle is based on the image data, or is provided by an accelerometer.

18. The method of claim 13 , further comprising:

obtaining driver behavior data corresponding to a driver of the vehicle, wherein the driver behavior data are based the sensor data provided by the onboard vehicle system; and

determining a fault status associated with the driver based on the driver behavior data;

wherein the insurance claim data is determined based also on the fault status.

19. The method of claim 13 , wherein the loss probability is determined using an adverse vehicle event model, wherein the adverse vehicle event model is a neural network model.