METHOD AND SYSTEM FOR RISK DETERMINATION OF A ROUTE
A method for risk determination of a route includes collecting a set of inputs and determining a set of risk scores. Additionally, the method can include any or all of: processing the set of inputs; organizing the set of inputs; determining a model based on the set of inputs; determining a set of risk scores; producing an outputs based on the set of risk scores; and/or any other suitable processes.
1 . A method comprising:
receiving motion information from a set of mobile user devices, the motion information comprising location data and device handling information;
determining a set of near-miss events based on the motion information;
determining a set of collision events for each of a first and second series of route segments; and
with a model, determining a segment risk score for each of the first and second series of route segments based on the set of near-miss events and the set of collision events;
aggregating the segment risk scores of the first and second series of route segments to determine a first and second route risk score, respectively;
selecting a route based on the first and second route risk scores; and
providing navigation instructions at a second set of mobile user devices based on the route.
2 . The method of claim 1 , further comprising: updating the motion information based on positional information collected with the mobile user device during a traversal of the route, wherein a mobile user device of the set comprises an inertial sensor, wherein the method further comprises transforming a set of inertial measurements of the inertial sensor into the positional information.
3 . The method of claim 2 , further comprising: updating the model based on the updated motion information.
4 . The method of claim 1 , wherein each of the segment risk scores is further determined based on a time of day.
5 . The method of claim 1 , further comprising: transmitting the first route risk score to an insurance entity, wherein the first route risk score corresponds to the route.
6 . The method of claim 1 , wherein the set of near-miss events comprises a near-miss event associated with satisfaction of an acceleration threshold.
7 . The method of claim 6 , wherein the near-miss event is further associated with mobile device usage within a threshold time of the satisfaction of the acceleration threshold.
8 . The method of claim 1 , wherein the location data comprises incomplete Global Positioning System (GPS) traces of historical driving routes traversed by mobile devices of the set of mobile devices.
9 . The method of claim 1 , wherein the set of collision events is determined based on vehicle movement features extracted from the motion information.
10 . The method of claim 1 , wherein the first set of mobile user devices comprises the second set of mobile user devices.
11 . A method comprising:
determining a motion dataset with a mobile user device, the motion dataset comprising: an inertial dataset and a location dataset;
based on the motion dataset, determining vehicle movement features and mobile device motion features comprising device handling information;
with a model, based on the vehicle movement features and the mobile device motion features, determining a set of near-collision events;
for each of a series of route segments along a vehicle route, determining a segment risk score based on the set of near-collision events; and
aggregating the series of segment risk scores to determine a route risk score.
12 . The method of claim 11 , further comprising transmitting the route risk score to an insurance entity.
13 . The method of claim 11 , wherein the location dataset comprises an incomplete Global Positioning System (GPS) trace along the vehicle route.
14 . The method of claim 11 , wherein the set of near-collision events comprises a near-collision event associated with satisfaction of an acceleration threshold.
15 . The method of claim 11 , wherein the determination of the set of near-collision events with the model occurs locally at the first mobile user device.
16 . The method of claim 11 , wherein the model comprises a statistical model.
17 . The method of claim 11 , wherein the model comprises a convolutional neural network.
18 . The method of claim 11 , further comprising: at a second mobile user device, triggering an action based on the route risk score.
19 . The method of claim 18 , wherein the second mobile user device is the first mobile user device.
20 . The method of claim 11 , further comprising triggering an action at a remote processor based on the route risk score.