Location and event capture circuitry to facilitate remote vehicle location predictive modeling when global positioning is unavailable

• US 10,223,744 B2
• Filed: 04/11/2016
• Issued: 03/05/2019
• Est. Priority Date: 12/31/2013
• Status: Active Grant

• Current Assignee: Spireon Incorporated (Solera Holdings Incorporated)
• Original Assignee: Spireon Incorporated (Solera Holdings Incorporated)
• Inventors: Brady, James, Wheeler, Brian, Estes, David, Marks, Thomas, Warner, Andy, Tran, Ben, Callinan, Michael, Collingwood, Chris, Withers, David, Ardelean, Ilie
• Primary Examiner(s): Nguyen, Nga X
• Application Number:
  US15/095,184
• Publication Number:
  US 20160225072A1
• Time in Patent Office: 1,058 Days
• Field of Search: 705 36 R, 705 35, 705 40, 701 36
• CPC Class Codes: B60R 16/0231 Circuits relating to the driving or the functioning of the vehicle monitoring tyres B60C23/00; indicating overspeed B60K31/00; for dash boards B60K37/00, B60Q3/10; for indicating emergencies B60Q1/52; brake control systems B60T; registering or indicating the working of vehicles G07C5/00; measuring distance G01C, e.g. combinations of speed and distance G01C23/00; engine indicators G01L; measuring speed or acceleration G01P
• CPC Class Codes: G01S 5/0027 of actual mobile position, i.e. position determined on mobile
• CPC Class Codes: G06Q 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03
• CPC Class Codes: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C
• CPC Class Codes: G07C 5/0841 Registering performance data recording measured values G01D; information storage G11B

Abstract

Disclosed are a device and/or a method of location and event capture circuitry to facilitate remote vehicle location predictive modeling when global positioning is unavailable. In one embodiment, a predictive circuit of a vehicle includes event detection circuitry to initiate a timer circuit of the vehicle when a wheel of the vehicle is in a stationary state beyond threshold amount of time during an event; an event categorization circuitry to monitor a telemetry data of the vehicle to assign a category to the event; a data communication circuitry to communicate the event, the category, and/or a set of other events and categories to a predictive recommendation server on a periodic basis; and a repossession detection circuitry to determine that the vehicle is pending repossession based on the event, the category, the set of other events and categories, and/or a message communicated from the predictive recommendation server to the predictive circuit.

Claims

1. A repossession recommendation system for providing a recommendation regarding locations and times at which a target vehicle will be parked and available for repossession, the apparatus comprising:

one or more electronic devices that generate and communicate vehicle location data comprising one or more of;

a tracking device in the target vehicle that generates location data based on satellite signals when satellite signals are available; and

a mobile device associated with a user of the target vehicle that generates location data based on satellite signals when satellite signals are available or based on a triangulation algorithm when satellite signals are unavailable;

a network through which the vehicle location data is communicated; and

a predictive recommendation server for receiving the vehicle location data via the network, the predictive recommendation server comprising one or more processors that are operable to execute instructions to;

create a plurality of destination zones associated with the target vehicle based on the vehicle location data, each destination zone having a geographic boundary;

group a set of visits within each destination zone, wherein each visit comprises an instance during which the target vehicle was parked within the geographic boundary of the destination zone;

determine a frequency of visits for one or more of the destination zones;

receive non-tracking data via the network from one or more of a commercial data server, a government data server, a social media server, a lender server, and a law enforcement server, wherein the non-tracking data provides information about the operation of vehicle other than locations and times at which the target vehicle is parked; and

run a predictive model based at least in part on the frequency of visits and the non-tracking data to generate a list of recommended destination zones and times to repossess the target vehicle.

2. The repossession recommendation system of claim 1 wherein the non-tracking data provides information about types of parking available to the target vehicle in each of the destination zones, wherein the types of parking include one or more of street parking, driveway parking, garage parking, and gated lot parking.

3. The repossession recommendation system of claim 1 wherein the non-tracking data provides one or more of information about results of previous repossession attempts for the target vehicle, and information about a geographic location of a repossessor entity.

4. The repossession recommendation system of claim 1 wherein the predictive recommendation server comprises one or more processors that are operable to execute instructions to display the recommended destination zones on a predictive timeline indicating a probability of the target vehicle being within particular recommended destination zones at particular times of day.

5. A repossession recommendation system for providing a recommendation regarding locations and times at which a target vehicle will be parked and available for repossession, the apparatus comprising:

a tracking device in the target vehicle that generates vehicle location data; and

a network through which the vehicle location data is communicated; and

a predictive recommendation server for receiving the vehicle location data via the network, the predictive recommendation server comprising one or more processors that are operable to execute instructions to;

create a plurality of destination zones associated with the target vehicle based on the vehicle location data, each destination zone having a geographic boundary;

group a set of visits within each destination zone, wherein each visit comprises an instance during which the target vehicle was parked within the geographic boundary of the destination zone;

determine a frequency of visits for one or more of the destination zones; and

run a predictive model based at least in part on the frequency of visits to generate and display a predictive timeline as a graphical user interface comprising a plurality of graphical data points, each graphical data point corresponding to a particular time of day on a particular day of the week, each graphical data point having an appearance characteristic that indicates a confidence level of finding the target vehicle within a particular destination zone at the particular time of day on the particular day of the week.

6. The repossession recommendation system of claim 5 wherein the one or more processors of the predictive recommendation server receive user input information via the network indicating a particular one of the graphical data points that was selected by a user using the graphical user interface, wherein the one or more processors execute instructions to display to the user one or more actions that may be taken with respect to the graphical data point selected by the user, wherein the one or more actions include one or more of:

providing the user a recommendation of a repossessor entity to which repossession of the target vehicle may be assigned;

assigning a repossessor entity to retrieve the target vehicle at the location, time of day, and day of the week associated with the graphical data point selected by the user;

establishing a geofence around the location associated with the graphical data point clicked on by the user, and alerting a repossessor entity when the target vehicle arrives within the geofence around the location on the day associated with the graphical data point selected by the user; and

displaying additional information to the user indicating a probability of successful repossession of the target vehicle within the destination zone at the particular time of day on the particular day of the week indicated by the graphical data point selected by the user.

7. The repossession recommendation system of claim 5 wherein each graphical data point is displayed in a specific color indicating a specific one of the destination zones.

8. The repossession recommendation system of claim 5 wherein the appearance characteristic of each graphical data point that indicates a confidence level of finding the target vehicle within a particular destination zone at the particular time of day on the particular day of the week is a size of the graphical data point, wherein the size of the graphical data point is proportional to the confidence level.

9. The repossession recommendation system of claim 6 wherein the user selects a graphical data point by clicking on or hovering over the graphical data point.