Patent Application Titled “Vehicle-To-Vehicle Accident Detection” Published Online (USPTO 20230368587): Allstate Insurance Company
2023 NOV 01 (NewsRx) -- By a
The assignee for this patent application is
Reporters obtained the following quote from the background information supplied by the inventors: “Many vehicles include sophisticated sensors and advanced internal computer systems designed to monitor and control vehicle operations and driving functions. Vehicle-based computer systems, such as on-board diagnostics (OBD) systems and telematics devices, may be used in automobiles and other vehicles, and may be capable of collecting various driving data and vehicle sensor data. For example, OBD systems may receive information from the vehicle’s on-board computers and sensors in order to monitor a wide variety of information relating to the vehicle systems, such as engine RPM, emissions control, vehicle speed, throttle position, acceleration and braking rates, use of driver controls, etc. Vehicles may also include Global Positioning System (GPS) receivers and devices installed within or operating at the vehicle configured to collect vehicle location and time data.
“However, not all vehicles are equipped with systems capable of collecting, analyzing, and communicating driving data. In contrast to vehicle-based systems, mobile devices such as smartphones, personal digital assistants, tablet computers, and the like, are often carried and/or operated by a single user. Some mobile devices may include movement sensors, such as an accelerometer, gyroscope, speedometer, and/or GPS receivers, capable of detecting movement.”
In addition to obtaining background information on this patent application, NewsRx editors also obtained the inventors’ summary information for this patent application: “The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosure. The summary is not an extensive overview of the disclosure. It is neither intended to identify key or critical elements of the disclosure nor to delineate the scope of the disclosure. The following summary merely presents some concepts of the disclosure in a simplified form as a prelude to the description below.
“Aspects of the disclosure relate to determining, by a driving analysis computing device, whether a collision has occurred between a first vehicle and a second vehicle. The driving analysis computing device may receive first vehicle driving data collected by vehicle operation sensors within a first vehicle, the first vehicle driving data including X-axis positional data for the first vehicle, Y-axis positional data for the first vehicle, and Z-axis positional data for the first vehicle. The driving analysis computing device may receive second vehicle driving data collected by vehicle operation sensors within a second vehicle, the second vehicle driving data including X-axis positional data for the second vehicle, Y-axis positional data for the second vehicle, and Z-axis positional data for the second vehicle. The driving analysis computing device may determine a first difference between the X-axis positional data for the first vehicle and the X-axis positional data for the second vehicle, determine a second difference between the Y-axis positional data for the first vehicle and the Y-axis positional data for the second vehicle, and determine a third difference between the Z-axis positional data for the first vehicle and the Z-axis positional data for the second vehicle. The driving analysis computing device may determine whether a collision between the first vehicle and the second vehicle has occurred based on one or more of the first difference, the second difference, and the third difference.
“In accordance with further aspects of the present disclosure, determining whether a collision between the first vehicle and the second vehicle has occurred based on one or more of the first difference, the second difference, and the third difference may include determining whether the first difference is within a first range of values, determining whether the second difference is within a second range of values, and/or determining whether the third difference is within a third range of values. In some examples, determining a third difference between the Z-axis positional data for the first vehicle and the Z-axis positional data for the second vehicle may be performed in response to determining that the first difference is within a first range of values, and determining that the second difference is within a second range of values.
“In accordance with further aspects of the present disclosure, the driving analysis computing device may receive the first vehicle driving data and the second vehicle driving data in real-time. The driving analysis computing device may determine whether a collision has occurred in real-time. The first vehicle driving data further may include a first direction data for the first vehicle, a first velocity data for the first vehicle, and a first acceleration data for the first vehicle. The second vehicle driving data may include a second direction data for the second vehicle, a second velocity data for the second vehicle, and a second acceleration data for the second vehicle.
“In accordance with further aspects of the present disclosure, the driving analysis computing device may determine a first projected location for the first vehicle at a first time based on the first direction data, the first velocity data, and the first acceleration data. The driving analysis computing device may determine a second projected location for the second vehicle at a first time based on the second direction data, the second velocity data, and the second acceleration data. The driving analysis computing device may determine a probability of a collision between the first vehicle and the second vehicle at the first time based on the first projected location and the second projected location. The driving analysis computing device may determine that the probability of the collision between the first vehicle and the second vehicle is above a threshold value, and may transmit a first set of warnings to the first vehicle and a second set of warnings to the second vehicle. The first set of warnings and the second set of warnings may be based on the historical behavior of a driver of the first vehicle and a driver of the second vehicle, respectively. The driving analysis computing device may determine that a third vehicle is within a predetermined radius of the first vehicle and may transmit a request for vehicle driving data collected by vehicle operation sensors within the third vehicle.
“In accordance with further aspects of the present disclosure, the driving analysis computing device may receive first vehicle driving data collected by vehicle operation sensors within a first vehicle, the first vehicle driving data including X-axis positional data for the first vehicle, Y-axis positional data for the first vehicle, and Z-axis positional data for the first vehicle, receive second vehicle driving data collected by vehicle operation sensors within a second vehicle, the second vehicle driving data including X-axis positional data for the second vehicle, Y-axis positional data for the second vehicle, and Z-axis positional data for the second vehicle, determine a first difference between the X-axis positional data for the first vehicle and the X-axis positional data for the second vehicle, determine a second difference between the Y-axis positional data for the first vehicle and the Y-axis positional data for the second vehicle, and responsive to a determination that the first difference is within a first predetermined range and that the second difference is within a second predetermined range, the driving analysis computing device may determine a third difference between the Z-axis positional data for the first vehicle and the Z-axis positional data for the second vehicle, and determine whether a collision between the first vehicle and the second vehicle has occurred based on the third difference.
“Other features and advantages of the disclosure will be apparent from the additional description provided herein.”
The claims supplied by the inventors are:
“1. A driving analysis computing device comprising: a processing unit comprising a processor; and a memory unit storing computer-executable instructions, which when executed by the processing unit, cause the driving analysis computing device to: determine a probability of a collision between a first vehicle and a second vehicle generate a collision identification number associated with the probability of the collision; determine that a collision between the first vehicle and the second vehicle has occurred and associate the collision with the collision identification number; send, to a mobile computing device associated with the first vehicle, a request for additional driving data of a third vehicle that is within a predetermined distance of the first vehicle upon determination that the collision has occurred; and receive, from the mobile computing device associated with the first vehicle and in response to sending the request, additional driving data of the third vehicle tagged with the collision identification number; and conduct an accident analysis based on the additional driving data of the third vehicle.
“2. The driving analysis computing device of claim 1, wherein the accident analysis comprises at least a likelihood of fault analysis, a fraud detection analysis or combinations thereof, wherein the likelihood of fault analysis comprises determining, upon determination that the collision has occurred, a likelihood of fault of whether the first vehicle or the second vehicle was at fault for the collision based on a set of fault detection rules and the additional driving data of the third vehicle, and wherein the fraud detection analysis comprises validation of a claim submitted by a driver of the first vehicle indicating damage to the first vehicle based on comparison of the claim to the additional driving data of the third vehicle.
“3. The driving analysis computing device of claim 1, wherein receiving of first vehicle driving data and second vehicle driving data is performed in real-time, and wherein the vehicle driving data comprises three-dimensional position data.
“4. The driving analysis computing device of claim 1, wherein first vehicle driving data collected by vehicle operation sensors within the first vehicle comprises a first direction data for the first vehicle and a first acceleration data for the first vehicle, and wherein second vehicle driving data collected by vehicle operation sensors within the second vehicle further comprises a second direction data for the second vehicle and a second acceleration data for the second vehicle.
“5. The driving analysis computing device of claim 4, wherein a first projected location for the first vehicle during a first time interval is further based on the first direction data and the first acceleration data, and wherein a second projected location for the second vehicle during the first time interval is further based on the second direction data and the second acceleration data.
“6. The driving analysis computing device of claim 5, the memory unit storing computer-executable instructions, which when executed by the processing unit, further cause the driving analysis computing device to: transmit a first and a second set of warnings to the second vehicle.
“7. The driving analysis computing device of claim 6, wherein: the first set of warnings is based on historical behavior of a first driver of the first vehicle; and the second set of warnings is based on historical behavior of a second driver of the second vehicle.
“8. The driving analysis computing device of claim 6, wherein the first time interval is determined by a driver of the first vehicle.
“9. A method, comprising: determining a probability of a collision between the first vehicle and the second vehicle; generating a collision identification number associated with the probability of the collision; determining that a collision between the first vehicle and the second vehicle has occurred and associating the collision with the collision identification number; sending, to a mobile computing device associated with the first vehicle, a request for additional driving data of a third vehicle that is within a predetermined distance of the first vehicle upon determination that the collision has occurred; receiving, from the mobile computing device associated with the first vehicle and in response to sending the request, additional driving data of the third vehicle tagged with the collision identification number; and conducting an accident analysis based on the additional driving data of the third vehicle.
“10. The method of claim 9, wherein determining whether a collision between the first vehicle and the second vehicle has occurred based on the first vehicle driving data collected by vehicle operation sensors within the first vehicle and the second vehicle driving data collected by vehicle operation sensors within the second vehicle comprises: determining whether a difference between first positional data of the first vehicle driving data and second positional data of the fourth vehicle driving data is within a first range of values.
“11. The method of claim 9, wherein the first vehicle driving data comprises three-dimensional position data.
“12. The method of claim 9, wherein the receiving the first vehicle driving data and the second vehicle driving data is performed in real-time.
“13. The method of claim 9, wherein the first vehicle driving data comprises a first direction data for the first vehicle and a first acceleration data for the first vehicle, and wherein the second vehicle driving data further comprises a second direction data for the second vehicle and a second acceleration data for the second vehicle.
“14. The method of claim 13, wherein a first projected location for the first vehicle during a first time interval is further based on the first direction data and the first acceleration data, and wherein a second projected location for the second vehicle during the first time interval is further based on the second direction data and the second acceleration data.
“15. The method of claim 14, further comprising: transmitting a first and a second set of warnings to the second vehicle.
“16. The method of claim 15, wherein the first set of warnings is based on historical behavior of a first driver of the first vehicle and the second set of warnings is based on historical behavior of a second driver of the second vehicle.
“17. The method of claim 14, wherein the first time interval is determined by a driver of the first vehicle.
“18. A non-transitory computer-readable medium storing instructions that, when executed by a processor, cause the processor to: determine a probability of a collision between the first vehicle and the second vehicle; generate a collision identification number associated with the probability of the collision; determine that a collision between the first vehicle and the second vehicle has occurred and associate the collision with the collision identification number; send, to a mobile computing device associated with the first vehicle, a request for additional driving data of a third vehicle that is within a predetermined distance of the first vehicle upon determination that the collision has occurred; receive, from the mobile computing device associated with the first vehicle and in response to sending the request, additional driving data of the third vehicle tagged with the collision identification number; and conduct an accident analysis based on the additional driving data of the third vehicle.”
For more information, see this patent application: Brandmaier, Jennifer; Higgins, Martin; Loo, William; Plachta, Christopher G.; Ramirez,
(Our reports deliver fact-based news of research and discoveries from around the world.)
Researchers from Harvard University Provide Details of New Studies and Findings in the Area of Managed Care (Promoting Health Equity Through Poverty Alleviation Policy: Factors Associated With Receipt of the 2021 Us Child Tax Credit In a …): Managed Care
Studies from Oregon State University Yield New Data on Risk Management (Enhancing the resilience of blue foods to climate shocks using insurance): Risk Management
Advisor News
- Your client’s $3 million portfolio doesn’t tell you their insurance needs
- How life insurance can provide liquidity for wealthy families
- Retirement providers turn to digital engagement to retain assets
- Looking out for clients with diminished mental capacity
- House panel advances CLEAR Forms Act backed by IRI
More Advisor NewsAnnuity News
- AM Best downgrades A-Cap insurers amid financial and regulatory troubles
- Lawsuit claims Delaware Life hid billions in insurer-linked investments
- AM Best to Deliver Presentation at 2026 ACLI Annual Conference
- Global Atlantic Announces Launch of ForeLifetime Income, a New Fixed Index Annuity
- A-Cap strikes back with lawsuit accusing SC regulators of sloppy process, leaking secrets
More Annuity NewsHealth/Employee Benefits News
Life Insurance News