# US 11,906,310 B2 · Map maintenance and verification > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,906,310 B2 - Document ID: US11906310B2 - Status: Granted - Kind: B2 - Application number: 18/106,554 - Filed: 2023-02-07 - Published: 2023-06-15 - Granted: 2024-02-20 - Earliest claimed: 2020-03-31 - Assignees: GM Cruise Holdings LLC - Applicants: GM Cruise Holdings LLC - Inventors: Chen Xie; Matthew Fox; Brian Joseph Donohue; Kangyuan Niu; Katherine Leung - Web page: https://patentgrep.com/patent/US11906310B2 ## CPC - G01C 21/32: Structuring or formatting of map data - G01C 21/3804: {Creation or updating of map data} - G06F 16/23: Updating - G06F 16/29: Geographical information databases - G01C: MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY (measuring liquid level G01F; radio navigation, determining distance or velocity by use of propagation effects, e.g. Doppler effects, propagation time, of radio waves, analogous arrangements using other waves G01S) - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract Techniques are disclosed for evaluating digital map quality. A process includes steps for receiving change data indicating one or more feature discrepancies associated with one or more geographic regions of a digital map, analyzing the change data to determine which of the one or more feature discrepancies resulted in verified updates to the digital map, and generating a quality score for each of the geographic map regions based on the verified updates. Systems and machine-readable media are also provided. ## Claims ### Claim 1 A method of validating a digital map comprising: determining, by one or more processors and using a decay model, an accuracy estimate for each of one or more features associated with one or more geographic regions of the digital map, wherein the accuracy estimate for each of the one or more features that is determined by the decay model decreases as a time period between measurements of the one or more features increases; receiving, by the one or more processors, change data indicating a discrepancy in a subset of the one or more features of the one or more geographic regions, wherein the change data comprises aggregated feature discrepancies received by a change detection database from one or more sources; updating a change rate with respect to the aggregated feature discrepancies in the subset of the one or more features; determining, by the one or more processors, a surveillance cadence based on an updated change rate and the accuracy estimate determined by the decay model, wherein the surveillance cadence indicates an accuracy of changes associated with the one or more features; and based on the surveillance cadence, triggering, by the one or more processors, generation of a surveillance task that causes a vehicle to navigate to the one or more geographic regions for data collection. ### Claim 2 (depends on 1) The method of claim 1, further comprising: calculating, by the one or more processors, an accuracy score for the digital map based on a quality score for each of the one or more geographic regions, wherein the accuracy score for the digital map indicates a need for additional change data from the one or more sources. ### Claim 3 (depends on 1) The method of claim 1, further comprising: estimating, by the one or more processors, a quality score for at least one geographic region based on verified updates to the digital map. ### Claim 4 (depends on 1) The method of claim 1, wherein the aggregated feature discrepancies in the subset of the one or more features comprise one or more precision discrepancies. ### Claim 5 (depends on 1) The method of claim 1, wherein the aggregated feature discrepancies in the subset of the one or more features comprise one or more accuracy discrepancies. ### Claim 6 (depends on 1) The method of claim 1, wherein the aggregated feature discrepancies in the subset of the one or more features comprise one or more recall discrepancies. ### Claim 7 (depends on 1) The method of claim 1, wherein the change data comprises one or more of: a feature type, a location of a feature change, or a change type. ### Claim 8 A system comprising: one or more sensors of an autonomous vehicle; and a processor for executing instructions stored in memory, wherein execution of the instructions by the processor executes: determining, by one or more processors and using a decay model, an accuracy estimate for each of one or more features associated with one or more geographic regions of a digital map, wherein the accuracy estimate for each of the one or more features that is determined by the decay model decreases as a time period between measurements of the one or more features increases; receiving, by the one or more processors, change data indicating a discrepancy in a subset of the one or more features of the one or more geographic regions, wherein the change data comprises aggregated feature discrepancies received by a change detection database from one or more sources; updating a change rate with respect to the aggregated feature discrepancies in the subset of the one or more features; determining, by the one or more processors, a surveillance cadence based on an updated change rate and the accuracy estimate determined by the decay model, wherein the surveillance cadence indicates an accuracy of changes associated with the one or more features; and based on the surveillance cadence, triggering, by the one or more processors, generation of a surveillance task that causes a vehicle to navigate to the one or more geographic regions for data collection. ### Claim 9 (depends on 8) The system of claim 8, wherein execution of the instructions by the processor further executes: calculating an accuracy score for the digital map based on a quality score for each of the one or more geographic regions, wherein the accuracy score for the digital map indicates a need for additional change data from the one or more sources. ### Claim 10 (depends on 8) The system of claim 8, wherein execution of the instructions by the processor further executes: estimating a quality score for at least one geographic region based on verified updates to the digital map. ### Claim 11 (depends on 8) The system of claim 8, wherein the aggregated feature discrepancies in the subset of the one or more features comprise one or more precision discrepancies. ### Claim 12 (depends on 8) The system of claim 8, wherein the aggregated feature discrepancies in the subset of the one or more features comprise one or more accuracy discrepancies. ### Claim 13 (depends on 8) The system of claim 8, wherein the aggregated feature discrepancies in the subset of the one or more features comprise one or more recall discrepancies. ### Claim 14 (depends on 8) The system of claim 8, wherein the change data comprises one or more of: a feature type, a location of a feature change, or a change type. ### Claim 15 A non-transitory computer readable medium comprising instructions, the instructions, when executed by a computing system, cause the computing system to: determine, by one or more processors and using a decay model, an accuracy estimate for each of one or more features associated with one or more geographic regions of a digital map, wherein the accuracy estimate for each of the one or more features that is determined by the decay model decreases as a time period between measurements of the one or more features increases; receive, by the one or more processors, change data indicating a discrepancy in a subset of the one or more features of the one or more geographic regions, wherein the change data comprises aggregated feature discrepancies received by a change detection database from one or more sources; update a change rate with respect to the aggregated feature discrepancies in the subset of the one or more features; determine, by the one or more processors, a surveillance cadence based on an updated change rate and the accuracy estimate determined by the decay model, wherein the surveillance cadence indicates an accuracy of changes associated with the one or more features; and based on the surveillance cadence, trigger, by the one or more processors, generation of a surveillance task that causes a vehicle to navigate to the one or more geographic regions for data collection. ### Claim 16 (depends on 15) The non-transitory computer readable medium of claim 15, wherein the instructions, when executed by the one or more processors, further cause the one or more processors to perform operations comprising: calculating an accuracy score for the digital map based on a quality score for each of the one or more geographic regions, wherein the accuracy score for the digital map indicates a need for additional change data from the one or more sources. ### Claim 17 (depends on 15) The non-transitory computer readable medium of claim 15, wherein the instructions, when executed by the one or more processors, further cause the one or more processors to perform operations comprising: estimating a quality score for at least one geographic region based on verified updates to the digital map. ### Claim 18 (depends on 15) The non-transitory computer readable medium of claim 15, wherein the aggregated feature discrepancies in the subset of the one or more features comprise one or more precision discrepancies. ### Claim 19 (depends on 15) The non-transitory computer readable medium of claim 15, wherein the aggregated feature discrepancies in the subset of the one or more features comprise one or more accuracy discrepancies. ### Claim 20 (depends on 15) The non-transitory computer readable medium of claim 15, wherein the aggregated feature discrepancies in the subset of the one or more features comprise one or more recall discrepancies.