Patent Application Titled “Real-Time Driver Analysis And Notification System” Published Online (USPTO 20230036776): Allstate Insurance Company

2023 FEB 17 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- According to news reporting originating from Washington, D.C., by NewsRx journalists, a patent application by the inventors Byrd, Raymone (Northbrook, IL, US); Ecclesiastre, Kelsy (Northbrook, IL, US); Kuhler, Madison (Northbrook, IL, US); Mussa, Joseph (Northbrook, IL, US); Patil, Mallika (Northbrook, IL, US); Tucker, Judah (Northbrook, IL, US), filed on August 1, 2022, was made available online on February 2, 2023.

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

Reporters obtained the following quote from the background information supplied by the inventors: “Many vehicles include sensors and internal computer systems designed to monitor vehicle operations, driving conditions, and driving functions. But by tracking only vehicle-based data, these systems may only detect dangerous driving after it has already occurred. In order to improve vehicular safety, it may be advantageous to monitor the driver so that dangerous conditions can be detected earlier.”

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 methods and computer devices for determining a distraction level of a driver. In one embodiment, a driver analysis computing device may include a processor and a memory unit communicatively coupled to the processor and storing machine-readable instructions. When executed by the processor, the machine-readable instructions may cause the processor to receive driver sensor data from one or more driver sensors. The driver sensor data may be captured by the one or more driver sensors while a driver is driving a vehicle. The one or more driver sensors may monitor and record a plurality of conditions of the driver. The plurality of conditions may include at least movement of a body of the driver, movement of eyes of the driver, or combinations thereof. The processor may analyze the driver sensor data to determine a distraction level of the driver. The processor may compare the distraction level to a threshold. The processor may determine, when the distraction level is above the threshold, that the driver is distracted. Responsive to a determination that the driver is distracted, the processor may output, to a graphical user interface of a mobile computing device of the driver, one or more graphical warnings. Responsive to the determination that the driver is distracted, output, to a vehicle control computer of the vehicle, one or more control signals to the vehicle.

“In another embodiment, a computer-implemented method may include receiving driver sensor data from one or more driver sensors. The driver sensor data may be captured by the one or more driver sensors while a driver is driving a vehicle. The one or more driver sensors may monitor and record a plurality of conditions of the driver including movement of a body of the driver, movement of eyes of the driver, or combinations thereof. The method may further include analyzing the driver sensor data to determine a distraction level of the driver. The method may further include determining, when the distraction level is above the threshold, that the driver is distracted. The method may further include, responsive to a determination that the driver is distracted, outputting, to a graphical user interface of a mobile computing device of the driver, one or more graphical warnings. The method may further include, responsive to the determination that the driver is distracted, outputting, to a vehicle control computer of the vehicle, one or more control signals to the vehicle.

“In another embodiment, a computer-implemented method may include receiving vehicle sensor data from one or more vehicle sensors indicative of operation of the vehicle. The method may further include receiving driver sensor data from one or more driver sensors. The driver sensor data may be captured by the one or more driver sensors while a driver is driving a vehicle. The one or more driver sensors may monitor and record a plurality of conditions of the driver include at least movement of a body of the driver, movement of eyes of the driver, or combinations thereof. The method may further include analyzing the driver sensor data and the vehicle sensor data to determine a distraction level of the driver in real-time. The method may further include comparing the distraction level to a threshold. The method may further include determining, when the distraction level is above the threshold, that the driver is distracted. The method may further include, responsive to a determination that the driver is distracted, outputting, to a graphical user interface of a mobile computing device of the driver, one or more graphical warnings. The method may further include, responsive to the determination that the driver is distracted, outputting, to a vehicle control computer of the vehicle, one or more control signals to the vehicle.

“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 driver analysis computing device comprising: a processor; and a memory unit communicatively coupled to the processor and storing machine-readable instructions, wherein, when executed by the processor, the machine-readable instructions stored in the memory unit, cause the processor to: receive driver sensor data from one or more driver sensors, wherein the driver sensor data is captured by the one or more driver sensors while a driver is driving a vehicle, the one or more driver sensors configured to monitor and record a plurality of conditions of the driver, the plurality of conditions comprising at least movement of a body of the driver, movement of eyes of the driver, or combinations thereof; analyze the driver sensor data to determine a distraction level of the driver; compare the distraction level to a threshold; determine, when the distraction level is above the threshold, that the driver is distracted; responsive to a determination that the driver is distracted, output, to a graphical user interface of a mobile computing device of the driver, one or more graphical warnings; and responsive to the determination that the driver is distracted, output, to a vehicle control computer of the vehicle, one or more control signals to the vehicle.

“2. The driver analysis computing device of claim 1, wherein the machine-readable instructions further cause the processor to analyze the driver sensor data in real-time.

“3. The driver analysis computing device of claim 1, wherein the machine-readable instructions further cause the processor to configure the one or more driver sensors to send the driver sensor data to the driver analysis computing device in real-time.

“4. The driver analysis computing device of claim 1, wherein the one or more control signals comprise instructions to activate brakes of the vehicle, control the vehicle autonomously, switch control of the vehicle from autonomous driving to manual driving, or combinations thereof.

“5. The driver analysis computing device of claim 1, wherein the machine-readable instructions further cause the processor receive vehicle sensor data from one or more vehicle sensors indicative of operation of the vehicle, and analyze the vehicle sensor data and the driver sensor data to determine the distraction level of the driver.

“6. The driver analysis computing device of claim 1, wherein the driver sensor data comprises video data.

“7. The driver analysis computing device of claim 1, wherein the distraction level of the driver comprises a type of distraction.

“8. The driver analysis computing device of claim 7, wherein the type of distraction comprises an indication of the driver falling asleep, the driving losing consciousness, or the driver having a seizure.

“9. The driver analysis computing device of claim 1, wherein the machine-readable instructions further cause the processor to: receive user preferences; activate a first sensor of the one or more driver sensors based on the user preferences, the first sensor configured to monitor movement of one of the body or the eyes of the driver; and de-activate a second sensor of the one or more driver sensors based on the user preferences, the second sensor configured to monitor movement of the other of the body or the eyes of the driver.

“10. The driver analysis computing device of claim 1, wherein the machine-readable instructions further cause the processor to: receive user preferences comprising one or more time period preferences for monitoring the driver; and cause the one or more driver sensors to monitor the driver during the one or more time period preferences.

“11. The driver analysis computing device of claim 1, wherein the machine-readable instructions further cause the processor to: receive a baseline image of the driver; perform a comparison of an image of the driver received from the one or more driver sensors to the baseline image; identify the driver based on the comparison; and determine the distraction level of the driver based on the comparison.

“12. The driver analysis computing device of claim 1, wherein the machine-readable instructions further cause the processor to: receive user preferences associating a plurality of alert configurations with a plurality of driver distraction levels; determine an alert configuration from among the plurality of alert configurations associated with the determined distraction level based on the user preferences; and output the determined alert configuration, wherein the determined alert configuration comprises an output to the graphical user interface of the mobile computing device of the driver, an output of the one or more control signals to the vehicle, or combinations thereof.

“13. The driver analysis computing device of claim 1, wherein the machine-readable instructions further cause the processor to: determine trip data comprising the distraction level of the driver at a plurality of time steps during a driving trip; and update an insurance premium of the driver based on the trip data.

“14. A computer-implemented method comprising: receiving driver sensor data from one or more driver sensors, wherein the driver sensor data is captured by the one or more driver sensors while a driver is driving a vehicle, the one or more driver sensors configured to monitor and record a plurality of body of the driver, movement of eyes of the driver, or combinations thereof; analyzing the driver sensor data to determine a distraction level of the driver; comparing the distraction level to a threshold; determining, when the distraction level is above the threshold, that the driver is distracted; responsive to a determination that the driver is distracted, outputting, to a graphical user interface of a mobile computing device of the driver, one or more graphical warnings; and responsive to the determination that the driver is distracted, outputting, to a vehicle control computer of the vehicle, one or more control signals to the vehicle.

“15. The method of claim 14, wherein the one or more control signals comprise instructions to activate brakes of the vehicle.

“16. The method of claim 14, wherein the one or more control signals comprise instructions to control the vehicle autonomously response to the determination that the driver is distracted and a determination that an autonomous driving mode is active.

“17. The method of claim 14, the distraction level of the driver comprises a type of distraction, and the type of distraction comprises an indication of the driver falling asleep or the driver having a seizure.

“18. The method of claim 14, further comprising: receiving user preferences; activating a first sensor of the one or more driver sensors based on the user preferences, the first sensor configured to monitor movement of one of the body or the eyes of the driver; and de-activating a second sensor of the one or more driver sensors based on the user preferences, the second sensor configured to monitor movement of the other of the body or the eyes of the driver.

“19. The method of claim 14, further comprising: receiving a baseline image of the driver; performing a comparison of an image of the driver received from the one or more driver sensors to the baseline image; and determining the distraction level of the driver based on the comparison.

“20. A computer-implemented method comprising: receiving vehicle sensor data from one or more vehicle sensors indicative of operation of the vehicle; receiving driver sensor data from one or more driver sensors, wherein the driver sensor data is captured by the one or more driver sensors while a driver is driving a vehicle, the one or more driver sensors configured to monitor and record a plurality of conditions of the driver, the plurality of conditions comprising at least movement of a body of the driver, movement of eyes of the driver, or combinations thereof; analyzing the driver sensor data and the vehicle sensor data to determine a distraction level of the driver in real-time; comparing the distraction level to a threshold; determining, when the distraction level is above the threshold, that the driver is distracted; responsive to a determination that the driver is distracted, outputting, to a graphical user interface of a mobile computing device of the driver, one or more graphical warnings; and responsive to the determination that the driver is distracted, outputting, to a vehicle control computer of the vehicle, one or more control signals to the vehicle.”

For more information, see this patent application: Byrd, Raymone; Ecclesiastre, Kelsy; Kuhler, Madison; Mussa, Joseph; Patil, Mallika; Tucker, Judah. Real-Time Driver Analysis And Notification System. U.S. Patent Application Number 20230036776, filed August 1, 2022 and posted February 2, 2023. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(20230036776)&db=US-PGPUB&type=ids

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