Driving condition specific sensor quality index
US-2020309533-A1 · Oct 1, 2020 · US
US11048261B1 · US · B1
| Field | Value |
|---|---|
| Publication number | US-11048261-B1 |
| Application number | US-201916376836-A |
| Country | US |
| Kind code | B1 |
| Filing date | Apr 5, 2019 |
| Priority date | Apr 5, 2019 |
| Publication date | Jun 29, 2021 |
| Grant date | Jun 29, 2021 |
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An autonomous vehicle (AV) computing device including at least one processor may be provided. The at least processor may be programmed to (i) receive a proposed trip including a destination location and a departure time, (ii) determine environmental conditions data based on the destination location and the departure time, (iii) retrieve current software ecosystem data for the AV, (iv) retrieve aggregated data for a plurality of AVs, the aggregated data 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 to identify an adverse performance outcome, and (vi) execute a remedial action to avoid the adverse performance outcome.
Opening claim text (preview).
We claim: 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, ag
Retrieval, searching and output of information related to real-time traffic, weather, or environmental conditions (arrangements for giving variable traffic instructions G08G1/09) · CPC title
Preferred or disfavoured areas, e.g. dangerous zones, toll or emission zones, intersections, manoeuvre types or segments such as motorways, toll roads or ferries · CPC title
Planning or execution of driving tasks · CPC title
Safety or protection, e.g. defining protection zones around obstacles or avoiding hazards (arrangements for controlling the position or course of two or more vehicles for avoiding collisions therebetween G05D1/693; arrangements for reacting to or preventing system or operator failure G05D1/80) · CPC title
using signals provided by artificial sources external to the vehicle, e.g. navigation beacons · CPC title
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