Patent Issued for Driver behavior tracking and prediction (USPTO 11613271): Allstate Insurance Company

2023 APR 19 (NewsRx) -- By a News Reporter-Staff News Editor at Sports Research Daily -- According to news reporting originating from Alexandria, Virginia, by NewsRx journalists, a patent by the inventors Isaac, Emad (Downers Grove, IL, US), filed on August 18, 2020, was published online on March 28, 2023.

The assignee for this patent, patent number 11613271, is Allstate Insurance Company (Northbrook, Illinois, United States).

Reporters obtained the following quote from the background information supplied by the inventors: “Car rental services allow drivers to rent a wide variety of vehicles in a wide variety of locations. For example, a driver might rent a sedan when visiting a new city, and/or might rent a fun sports car when visiting the beach on vacation. To protect such vehicles, car rental services typically require that a renter have insurance, and/or such car rental services may maintain insurance on rented vehicles. Car rental services may also impose other requirements on rentals, such as requiring that the driver have a legal driver’s license.

“Increasingly, peer-to-peer vehicle sharing services are becoming popular. Such services allow automobile owners to list their vehicle for rent (e.g., on a smartphone app), allowing those owners to monetize their vehicle when they might not need it. A user may, for example, open an application on their phone, browse a listing of available vehicles (e.g., those parked at an airport, those available if the user travels to the home of the owner, or the like) and pay a time-based fee for access to a selected vehicle. That said, the ad hoc nature of such rentals often limits the legal protections that automobile owners might leverage to protect their automobile. For example, unless provided in the peer-to-peer vehicle sharing app, some automobile owners may not have the resources to verify the validity and/or comprehensiveness of an insurance policy maintained by a renter.

“The diversity and ready accessibility of such rental and peer-to-peer vehicle sharing services has allowed users to rent vehicles (e.g., exotic sports cars, manual transmission vehicles, large trucks, motorcycles) which renters might not necessarily have driven before. As such, automobile owners (whether companies or individuals) are often concerned that an inexperienced renter could damage their vehicle. For example, vintage automobile owners who list their cars on peer-to-peer vehicle sharing services are often concerned that inexperienced renters might crash their vehicles or damage the engine by revving the engine too hard. Though a potential renter of a vehicle may already have insurance and may already be associated with a driving score or traffic violation history, such information may be a poor indicator of how well the renter would drive a new type of vehicle, and validating the accuracy of such information may be prohibitively difficult for certain automobile owners. After all, the renter may be capable of driving their personal vehicle well, but may have difficulties driving a new and unfamiliar type of vehicle (e.g., a high horsepower sports car) in a similarly safe manner.”

In addition to obtaining background information on this patent, NewsRx editors also obtained the inventors’ summary information for this patent: “The following presents a simplified summary of various aspects described herein. This summary is not an extensive overview, and is not intended to identify required or critical elements or to delineate the scope of the claims. The following summary merely presents some concepts in a simplified form as an introductory prelude to the more detailed description provided below.

“To overcome limitations in the prior art described above, and to overcome other limitations that will be apparent upon reading and understanding the present specification, aspects described herein are directed towards tracking and predicting driver behavior across different vehicles.

“A computing device may, using first sensors of a first vehicle, determine one or more first performance metrics indicating performance of a first vehicle when driven by a user. The computing device may determine, using second sensors of a second vehicle, one or more second performance metrics indicating performance of a second vehicle when driven by the user. The first sensors and/or the second sensors may comprise, for example, one or more first sensors of a smartphone. The first vehicle and second vehicle may be compared to determine a vehicle difference between the first vehicle and the second vehicle. Determining the vehicle difference may comprise determining that the first vehicle and the second vehicle are each configured to provide different levels of autonomous driving. The one or more first performance metrics and the one or more second performance metrics may be compared to determine a behavioral difference of the user when driving the first vehicle as compared to the second vehicle. Determining the behavioral difference may comprise determining that the user drove the first vehicle with a different quantity of passengers as compared to the second vehicle. Determining the behavioral difference may comprise determining that the user is more reckless when driving the first vehicle as compared to the second vehicle. Determining the behavioral difference may comprise determining that the user is more distracted when driving the first vehicle as compared to the second vehicle. Determining the behavioral difference may comprise determining how the user is predicted to drive a rental vehicle as compared to a personal vehicle, wherein the first vehicle is owned by the user, and wherein the second vehicle is rented by the user. Based on the behavioral difference and the vehicle difference, the computing device may determine one or more third performance metrics which predict performance of a third vehicle, different from the first vehicle and the second vehicle, when driven by the user. Determining the one or more third performance metrics may comprise determining at least one of the one or more third vehicles that is similar to the first vehicle; and predicting, based on the one or more first performance metrics, the one or more third performance metrics by estimating how the user would drive the at least one of the one or more third vehicles. The computing device may determine, based on the one or more third performance metrics, whether to provide the user access to the third vehicle. Determining whether to provide the user access to the third vehicle may comprise transmitting, to a second computing device associated with a second user that owns the third vehicle, a summary of the one or more third performance metrics; and receiving, from the second computing device, an indication of whether to provide the user access to the third vehicle. The computing device may cause display, based on the behavioral difference, of one or more recommendations for improving a driving skill of the user.

“These and additional aspects will be appreciated with the benefit of the disclosures discussed in further detail below.”

The claims supplied by the inventors are:

“1. A method comprising: determining, by a computing device and using first sensors of a first vehicle, one or more first performance metrics indicating performance of the first vehicle when driven by a user; determining, by the computing device and using second sensors of a second vehicle, one or more second performance metrics indicating performance of the second vehicle when driven by the user; comparing the first vehicle and the second vehicle to determine a vehicle difference between the first vehicle and the second vehicle; comparing the one or more first performance metrics and the one or more second performance metrics to determine a behavioral difference of the user when driving the first vehicle as compared to the second vehicle; determining, based on the behavioral difference, based on the vehicle difference, and using a machine learning model, one or more third performance metrics which predict performance of a third vehicle, different from the first vehicle and the second vehicle, when driven by the user, wherein the machine learning model is trained using a first set of example performance metrics corresponding to safe driving and a second set of performance metrics corresponding to unsafe driving; and based on determining, based on the one or more third performance metrics, whether to provide the user access to the third vehicle: generating a notification indicating whether to provide the user access to the third vehicle, the notification configured to unlock the third vehicle or maintain a locked state of the third vehicle; and transmitting the notification.

“2. The method of claim 1, wherein determining the vehicle difference between the first vehicle and the second vehicle comprises: determining that the first vehicle and the second vehicle each are configured to provide different levels of autonomous driving.

“3. The method of claim 1, wherein determining the behavioral difference comprises: determining that the user drove the first vehicle with a different number of passengers as compared to the second vehicle.

“4. The method of claim 1, wherein the first sensors comprise one or more first sensors of a smartphone associated with the user, and wherein the second sensors comprise the one or more first sensors of the smartphone.

“5. The method of claim 1, wherein determining the behavioral difference comprises: determining that the user drives the first vehicle at a higher speed as compared to the second vehicle.

“6. The method of claim 1, wherein determining the behavioral difference comprises: determining that the user uses a smartphone more often when driving the first vehicle as compared to the second vehicle.

“7. The method of claim 1, wherein predicting the one or more third performance metrics comprises: determining at least one of a plurality of vehicles that is similar to the first vehicle; and predicting, based on the one or more first performance metrics, the one or more third performance metrics by estimating how the user would drive the at least one of the plurality of vehicles.

“8. The method of claim 1, wherein the third vehicle is a different type of vehicle as compared to the first vehicle and the second vehicle.

“9. The method of claim 1, wherein determining whether to provide the user access to the third vehicle comprises: transmitting, to a second computing device associated with a second user that owns the third vehicle, a summary of the one or more third performance metrics; and receiving, from the second computing device, an indication of whether to provide the user access to the third vehicle.

“10. The method of claim 1, further comprising: causing display, by the computing device and based on the behavioral difference, of one or more recommendations for improving a driving skill of the user.

“11. A method comprising: determining, by a computing device and using one or more sensors of a smartphone associated with a user, one or more first performance metrics indicating performance a first type of vehicle when driven by the user; determining, by the computing device and using the one or more sensors of the smartphone associated with the user, one or more second performance metrics indicating performance of a second type of vehicle, different from the first type of vehicle, when driven by the user; comparing the one or more first performance metrics and the one or more second performance metrics to determine a behavioral difference of the user when driving the first type of vehicle and the second type of vehicle; determining, based on the behavioral difference and the vehicle difference, one or more third performance metrics which predict performance of a third type of vehicle, different from the first type of vehicle and the second type of vehicle, when driven by the user; determining, based on the one or more third performance metrics, whether to provide the user access to a vehicle that corresponds to the third type of vehicle; and transmit a notification configured to unlock the third vehicle or maintain a locked state of the third vehicle based on the determining of whether to provide the user access.

“12. The method of claim 11, wherein the second type of vehicle executes a different level of autonomous driving as compared to the first type of vehicle.

“13. The method of claim 11, wherein the one or more first performance metrics indicate a first number of passengers in the first type of vehicle, and wherein the one or more second performance metrics indicate a second number of passengers in the second type of vehicle.

“14. The method of claim 11, wherein determining the behavioral difference comprises: determining that the user drives the first type of vehicle at a higher speed as compared to the second type of vehicle.

“15. The method of claim 11, wherein determining the behavioral difference comprises: determining that the user uses the smartphone more often when driving the first type of vehicle as compared to the second type of vehicle.

“16. The method of claim 11, further comprising: causing display, by the computing device and based on the behavioral difference, of one or more recommendations for improving a driving skill of the user.

“17. The method of claim 11, wherein determining whether to provide the user access to the vehicle comprises: transmitting, to a second computing device associated with a second user that owns the vehicle, a summary of the one or more third performance metrics; and receiving, from the second computing device, an indication of whether to provide the user access to the vehicle.

“18. A method comprising: determining, by a computing device, using first sensors of a first vehicle, and during a first trip taken by the first vehicle, one or more first performance metrics indicating performance of the first vehicle when driven by a user; determining, by the computing device, using second sensors of a second vehicle, and during a second trip taken by the second vehicle, one or more second performance metrics indicating performance of the second vehicle when driven by the user; comparing the first vehicle and the second vehicle to determine a vehicle difference between the first vehicle and the second vehicle; comparing, based on the vehicle difference, the one or more first performance metrics and the one or more second performance metrics to determine a behavioral difference of the user when driving the first vehicle as compared to the second vehicle; receiving, from the user, a request to access a third vehicle different from the first vehicle and the second vehicle; determining, based on the behavioral difference, the vehicle difference, and the request, one or more third performance metrics which predict performance of the third vehicle when driven by the user; and providing, based on comparing the one or more third performance metrics to a safety threshold, the user access to the third vehicle, wherein providing the user access includes transmitting signaling to unlock the third vehicle or maintain a locked state of the third vehicle.

“19. The method of claim 18, wherein determining the behavioral difference comprises: determining that the user drives the first vehicle at a higher speed as compared to the second vehicle.

“20. The method of claim 18, wherein determining the behavioral difference comprises: determining that the user uses a smartphone more often when driving the first vehicle as compared to the second vehicle.”

For more information, see this patent: Isaac, Emad. Driver behavior tracking and prediction. U.S. Patent Number 11613271, filed August 18, 2020, and published online on March 28, 2023. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(11613271)&db=USPAT&type=ids

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