Method and system for vehicular collision reconstruction
A system for accident reconstruction can include and/or be configured to interface with any or all of: a set of models, a set of modules, a processing system, client application, a user device (equivalently referred to herein as a mobile device), a set of sensors, a vehicle, and/or any other suitable components. A method for accident reconstruction includes collecting a set of inputs; detecting a collision and/or one or more features of the collision; reconstructing the collision; and producing an output based on the reconstruction. Additionally or alternatively, the method can include training a set of models and/or modules, and/or any other suitable processes.
1. A method for the detection and reconstruction of a collision, the method comprising:
at a computing system in communication with a mobile device associated with a driver, receiving a location dataset, a motion dataset, and a pressure dataset from the mobile device;
processing the location dataset, the motion dataset, and the pressure dataset with a set of modules to determine a set of outputs, the set of outputs comprising a confidence associated with the detection of the collision;
determining a score associated with a road segment arranged proximal to a location of the collision based on the set of outputs;
assigning the score to the road segment; and
providing a route recommendation based on the score assigned to the road segment, wherein the route comprises the road segment;
further comprising implementing an emergency response based on the set of outputs.
2. The method of claim 1 , wherein the set of modules comprises a machine learning model.
3. The method of claim 2 , further comprising updating the machine learning model based on the set of outputs.
4. The method of claim 1 , wherein the set of outputs further comprises:
a severity associated with the collision; and
a direction of impact of a vehicle, wherein the driver is arranged in the vehicle.
5. The method of claim 4 , further comprising transmitting the set of outputs to an insurance entity.
6. The method of claim 5 , further comprising transmitting a set of auxiliary outputs to the insurance entity.
7. The method of claim 6 , wherein the set of auxiliary outputs comprises at least one of: a set of gravitational force equivalent values and a speed of the vehicle prior to the collision.
8. The method of claim 1 , wherein the computing system is a remote computing system.
9. A method for the detection and reconstruction of a collision, the method comprising:
at a computing system in communication with a mobile device associated with a driver, receiving a dataset from the mobile device, the dataset comprising a location dataset, a motion dataset, and a pressure dataset;
processing the set of inputs with a set of modules to determine a set of outputs, the set of outputs comprising:
a confidence associated with the detection of the collision;
a severity associated with the collision;
a direction of impact of a vehicle, wherein the driver is arranged in the vehicle; and
a fraud metric associated with the collision, wherein determining the fraud metric comprises analyzing a subset of data from the dataset, wherein the subset of data is associated with a set of time points prior to a time of the impact;
transmitting the set of outputs to an insurance entity;
further comprising implementing an emergency response based on the set of outputs.
10. The method of claim 9 , further comprising receiving a second set of inputs after the collision.
11. The method of claim 10 , further comprising updating the set of modules based on the set of outputs and the second set of inputs.
12. The method of claim 9 , wherein the emergency response is determined at least in part based on the severity.
13. The method of claim 12 , wherein the emergency response is further determined based on the confidence.
14. The method of claim 13 , wherein implementing the emergency response comprises transmitting a notification to the driver at the mobile device, wherein an emergency action is triggered based on at least one of: a response from the driver at the mobile device and a lack of a response from the driver at the mobile device.
15. The method of claim 9 , wherein the set of modules comprises a machine learning model.
16. The method of claim 15 , wherein the set of modules further comprises a rule-based model.
17. The method of claim 9 , further comprising updating a score associated with a location proximal to the collision based on the set of outputs.
18. A method for the detection and reconstruction of a collision, the method comprising:
at a computing system in communication with a mobile device associated with a driver, receiving a set of inputs from the mobile device, the set of inputs comprising at least one of:
a location dataset;
A motion dataset; and
A pressure dataset;
processing the set of inputs with a set of modules to determine a set of outputs, wherein the set of outputs comprises at least one of:
a confidence associated with the detection of the collision;
a severity associated with the collision; and
a direction of impact of a vehicle, wherein the driver is arranged in the vehicle;
transmitting, to an insurance entity, the set of outputs and a set of auxiliary outputs comprising at least one of: a set of gravitational force equivalent values and a speed of the vehicle prior to the collision;
determining a score associated with a road segment arranged proximal to a location of the collision based on the set of outputs;
assigning the score to the road segment; and
providing a route recommendation based on the score assigned to the road segment, wherein the route comprises the road segment;
further comprising implementing an emergency response based on the set of outputs.