Patent Issued for Systems and methods for evaluating autonomous vehicle software interactions for proposed trips (USPTO 11048261)

2021 JUL 20 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- According to news reporting originating from Alexandria, Virginia, by NewsRx journalists, a patent by the inventors Chan, Aaron Scott (San Jose, CA, US), Cielocha, Steve (Bloomington, IL, US), Fields, Brian (Phoenix, AZ, US), filed on April 5, 2019, was published online on June 29, 2021.

The assignee for this patent, patent number 11048261, is State Farm Mutual Automobile Insurance Company (Bloomington, Illinois, United States).

Reporters obtained the following quote from the background information supplied by the inventors: “An autonomous vehicle (AV), also known as a “self-driving car”, is a vehicle that is capable of operating automatically without human input. AVs may operate at varying levels of autonomy, such as through a relatively low-level-autonomy system, sometimes referred to as an advanced driver-assistance system (ADAS) which is currently utilized in the automotive industry, or a high-level-autonomy system, sometimes referred to as an automatic-driving system (ADS) which is utilized in “self-driving” vehicles. While AV technology is advancing rapidly, developing a fully autonomous vehicle is an interdisciplinary challenge that requires further advancement in a number of related technologies.

“AVs may have many different types of software onboard, including autonomous driving systems, operating systems, user-selected infotainment applications, firmware, etc. These software applications may generally be updated several times through updated software versions, patches, etc. Over time, certain versions and/or combinations of software may result in unintended or adverse outcomes, particularly under specific environmental conditions. For example, certain software applications and/or combinations of software applications may have interaction issues with hilly environments or during snowfall that result in adverse vehicle performance (e.g., collisions).

“As AVs become more prevalent, minimizing risks associated with AVs become increasingly important. As discussed above, combinations of software within an AV “software ecosystem” (e.g., the entirety of software applications onboard the AV) may produce unexpected effects on AV performance, especially in certain environmental conditions. While these effects may be difficult to predict based on data from a single vehicle, data from a large number of AVs may facilitate enhanced analysis. Although at least some known systems may aggregate data from multiple AVs, none of these systems are able to evaluate risk based on interactions between AV software ecosystems and environmental conditions. Accordingly, there is a need for an AV system capable of evaluating risk of performance issues due to these software/condition interactions for a proposed trip of an AV based upon AV software-related data aggregated from a number of AVs.”

In addition to obtaining background information on this patent, NewsRx editors also obtained the inventors’ summary information for this patent: “The present embodiments may relate to systems and methods for evaluating potential performance outcomes and risks based on interactions between software onboard an autonomous vehicle and environmental conditions associated with a proposed trip of the autonomous vehicle, based on aggregated data from a plurality of autonomous vehicles.

“In one aspect, an autonomous vehicle (AV) computing device onboard an AV and including at least one processor may be provided. The at least processor may be programmed to (i) receive a proposed trip for the AV including a destination location and a departure time, (ii) determine environmental conditions data for the proposed trip based on the destination location and the departure time, wherein the environmental conditions data includes environmental conditions likely to be experienced by the AV during the proposed trip, (iii) retrieve current software ecosystem data for the AV, wherein the current software ecosystem data includes software applications currently onboard the AV, (iv) retrieve, from a memory device, aggregated data for a plurality of AVs including software ecosystem data, environmental conditions data, and performance data associated with the a plurality of AVs, the aggregated data further including a plurality of correlations, each correlation including a) an interaction between at least one software application and at least one environmental condition and b) an adverse performance outcome associated with the interaction, (v) compare the environmental conditions data for the proposed trip and the current software ecosystem data for the AV to the plurality of correlations included in the aggregated data to identify an adverse performance outcome associated with an interaction between at least one of the software applications currently onboard the AV and at least one of the environmental conditions likely to be experienced by the AV, and (vi) execute a remedial action to avoid the identified adverse performance outcome.

“In another aspect, a computer-implemented method may be provided. The computer-implemented method may include (i) receiving, by an autonomous vehicle (AV) computing device, a proposed trip for the AV including a destination location and a departure time, (ii) determining, by the AV computing device, environmental conditions data for the proposed trip based on the destination location and the departure time, wherein the environmental conditions data includes environmental conditions likely to be experienced by the AV during the proposed trip, (iii) retrieving, by the AV computing device, current software ecosystem data for the AV, wherein the current software ecosystem data includes software applications currently onboard the AV, (iv) retrieving, by the AV computing device, from a memory device, aggregated data for a plurality of AVs including software ecosystem data, environmental conditions data, and performance data associated with the a plurality of AVs, the aggregated data further including a plurality of correlations, each correlation including a) an interaction between at least one software application and at least one environmental condition and b) an adverse performance outcome associated with the interaction, (v) comparing, by the AV computing device, the environmental conditions data for the proposed trip and the current software ecosystem data for the AV to the plurality of correlations included in the aggregated data to identify an adverse performance outcome associated with an interaction between at least one of the software applications currently onboard the AV and at least one of the environmental conditions likely to be experienced by the AV, and (vi) executing, by the AV computing device, a remedial action to avoid the identified adverse performance outcome.

“In a further aspect, at least one non-transitory computer-readable media having computer-executable instructions thereon may be provided. When the instructions are executed by at least one processor of an autonomous vehicle (AV) computing device onboard an AV, the instructions may cause the at least one processor of the AV computing device to (i) receive a proposed trip for the AV including a destination location and a departure time, (ii) determine environmental conditions data for the proposed trip based on the destination location and the departure time, wherein the environmental conditions data includes environmental conditions likely to be experienced by the AV during the proposed trip, (iii) retrieve current software ecosystem data for the AV, wherein the current software ecosystem data includes software applications currently onboard the AV, (iv) retrieve, from a memory device, aggregated data for a plurality of AVs including software ecosystem data, environmental conditions data, and performance data associated with the a plurality of AVs, the aggregated data further including a plurality of correlations, each correlation including a) an interaction between at least one software application and at least one environmental condition and b) an adverse performance outcome associated with the interaction, (v) compare the environmental conditions data for the proposed trip and the current software ecosystem data for the AV to the plurality of correlations included in the aggregated data to identify an adverse performance outcome associated with an interaction between at least one of the software applications currently onboard the AV and at least one of the environmental conditions likely to be experienced by the AV, and (vi) execute a remedial action to avoid the identified adverse performance outcome.

“Advantages will become more apparent to those skilled in the art from the following description of the preferred embodiments which have been shown and described by way of illustration. As will be realized, the present embodiments may be capable of other and different embodiments, and their details are capable of modification in various respects. Accordingly, the drawings and description are to be regarded as illustrative in nature and not as restrictive.”

The claims supplied by the inventors are:

“1. An autonomous vehicle (AV) computing device onboard an AV and comprising at least one processor programmed to: receive a proposed trip for the AV including a destination location and a departure time; determine environmental conditions data for the proposed trip based on the destination location and the departure time, wherein the environmental conditions data includes environmental conditions likely to be experienced by the AV during the proposed trip; retrieve current software ecosystem data for the AV, wherein the current software ecosystem data includes software applications currently onboard the AV; retrieve, from a memory device, aggregated data for a plurality of AVs including software ecosystem data, environmental conditions data, and performance data associated with the a plurality of AVs, the aggregated data further including a plurality of correlations, each correlation including i) an interaction between at least one software application and at least one environmental condition and ii) an adverse performance outcome associated with the interaction; compare the environmental conditions data for the proposed trip and the current software ecosystem data for the AV to the plurality of correlations included in the aggregated data to identify an adverse performance outcome associated with an interaction between at least one of the software applications currently onboard the AV and at least one of the environmental conditions likely to be experienced by the AV; and execute a remedial action to avoid the identified adverse performance outcome.

“2. The AV computing device of claim 1, wherein the processor is further programmed to calculate a risk score based on the plurality of correlations.

“3. The AV computing device of claim 2, wherein the processor is further programmed to display an alert to a user of the AV if the risk score is above a predetermined threshold of risk.

“4. The AV computing device of claim 1, wherein to execute the remedial action the processor is further programmed to automatically install software for the AV to avoid the adverse performance outcome.

“5. The AV computing device of claim 1, wherein the software ecosystem data includes all software applications currently installed on the AV and a current version of each installed software application.

“6. The AV computing device of claim 1, wherein the environmental conditions data includes at least one of weather conditions, terrain, traffic conditions, local events, local regulations, and compliance trends associated with the local regulations along a route to the retrieved destination.

“7. The AV computing device of claim 1, wherein to receive the proposed trip, the processor is programmed to receive the destination location and the departure time based on an input from a user.

“8. The AV computing device of claim 1, wherein to receive the proposed trip, processor is programmed to identify the destination location and departure time by predicting the destination location and departure time based on data associated with a user.

“9. The AV computing device of claim 8, wherein to receive the proposed trip, the processor is programed to: retrieve the data associated with the user from a user computing device; compare the data associated with the user to data known to correspond to a potential destination location and potential departure time; and identify the destination as the potential destination and the departure time as the potential departure time based on the comparison.

“10. A computer-implemented method comprising: receiving, by an autonomous vehicle (AV) computing device, a proposed trip for the AV including a destination location and a departure time; determining, by the AV computing device, environmental conditions data for the proposed trip based on the destination location and the departure time, wherein the environmental conditions data includes environmental conditions likely to be experienced by the AV during the proposed trip; retrieving, by the AV computing device, current software ecosystem data for the AV, wherein the current software ecosystem data includes software applications currently onboard the AV; retrieving, by the AV computing device, from a memory device, aggregated data for a plurality of AVs including software ecosystem data, environmental conditions data, and performance data associated with the a plurality of AVs, the aggregated data further including a plurality of correlations, each correlation including i) an interaction between at least one software application and at least one environmental condition and ii) an adverse performance outcome associated with the interaction; comparing, by the AV computing device, the environmental conditions data for the proposed trip and the current software ecosystem data for the AV to the plurality of correlations included in the aggregated data to identify an adverse performance outcome associated with an interaction between at least one of the software applications currently onboard the AV and at least one of the environmental conditions likely to be experienced by the AV; and executing, by the AV computing device, a remedial action to avoid the identified adverse performance outcome.

“11. The method of claim 10, further comprising calculating, by the AV computing device, a risk score based on the plurality of correlations.

“12. The method of claim 11, further comprising displaying, by the AV computing device, an alert to a user of the AV if the risk score is above a predetermined threshold of risk.

“13. The method of claim 10, wherein executing the remedial action comprises automatically installing, by the AV computing device, software for the AV to avoid the adverse performance outcome.

“14. The method of claim 10, wherein receiving the proposed trip further comprises receiving, by the AV computing device, the destination location and the departure time based on an input from a user.

“15. The method of claim 10, wherein receiving the proposed trip further comprises receiving, by the AV computing device, the destination location and the departure time by predicting the destination location and the departure time based on data associated with a user.

“16. The method of claim 15, wherein predicting the destination and the departure time further comprises: retrieving, by the AV computing device, the data associated with the user from a user computing device; comparing, by the AV computing device, the data associated with the user to data known to correspond to a potential destination location and potential departure time; and identifying, by the AV computing device, the destination location as the potential destination location and the departure time as the potential departure time based on the comparison.

“17. At least one non-transitory computer-readable media having computer-executable instructions thereon, wherein when executed by at least one processor of an autonomous vehicle (AV) computing device onboard an AV, cause the at least one processor of the AV computing device to: receive a proposed trip for the AV including a destination location and a departure time; determine environmental conditions data for the proposed trip based on the destination location and the departure time, wherein the environmental conditions data includes environmental conditions likely to be experienced by the AV during the proposed trip; retrieve current software ecosystem data for the AV, wherein the current software ecosystem data includes software applications currently onboard the AV; retrieve, from a memory device, aggregated data for a plurality of AVs including software ecosystem data, environmental conditions data, and performance data associated with the a plurality of AVs, the aggregated data further including a plurality of correlations, each correlation including i) an interaction between at least one software application and at least one environmental condition and ii) an adverse performance outcome associated with the interaction; compare the environmental conditions data for the proposed trip and the current software ecosystem data for the AV to the plurality of correlations included in the aggregated data to identify an adverse performance outcome associated with an interaction between at least one of the software applications currently onboard the AV and at least one of the environmental conditions likely to be experienced by the AV; and execute a remedial action to avoid the identified adverse performance outcome.

“18. The computer-readable media of claim 17, wherein the computer-executable instructions further cause the at least one processor to calculate a risk score based on the plurality of correlations.

“19. The computer-readable media of claim 18, wherein the computer-executable instructions further cause the at least one processor to display an alert to a user of the AV if the risk score is above a predetermined threshold of risk.

“20. The computer-readable media of claim 17, wherein to execute the remedial action the computer-executable instructions further cause the at least one processor to automatically install software for the AV to avoid the adverse performance outcome.”

For more information, see this patent: Chan, Aaron Scott. Systems and methods for evaluating autonomous vehicle software interactions for proposed trips. U.S. Patent Number 11048261, filed April 5, 2019, and published online on June 29, 2021. Patent URL: http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.htm&r=1&f=G&l=50&s1=11048261.PN.&OS=PN/11048261RS=PN/11048261

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