# US 12,182,010 B2 · Vehicle software shadow mode testing > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,182,010 B2 - Document ID: US12182010B2 - Status: Granted - Kind: B2 - Application number: 17/705,623 - Filed: 2022-03-28 - Published: 2022-10-27 - Granted: 2024-12-31 - Earliest claimed: 2021-04-23 - Assignees: Zenseact AB - Applicants: Zenseact AB - Inventors: Magnus Gyllenhammar; Carl Zandén; Majid Khorsand Vakilzadeh; Mina Alibeigi - Web page: https://patentgrep.com/patent/US12182010B2 ## CPC - G06F 11/3696: {Methods or tools to render software testable} - B60W 60/0011: {involving control alternatives for a single driving scenario, e.g. planning several paths to avoid obstacles} - G01C 21/3407: {specially adapted for specific applications} - G06F 11/3457: {Performance evaluation by simulation} - G06F 11/3688: {for test execution, e.g. scheduling of test suites} - B60W 2556/50: of positioning data, e.g. GPS [Global Positioning System] data - B60W 2756/10: Involving external transmission of data to or from the vehicle - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - B60W: CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT - 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) ## Abstract A test-optimizing system for supporting shadow mode testing of ADS software included in an ADS-provided vehicle. One or more potential vehicle routes are retrieved. A geographical area covering the one or more potential vehicle routes is obtained and data of crucial locations associated with past vehicle situations identified as critical and/or challenging. Moreover, the test-optimizing system retrieves respective ODD for one or more candidate software respectively adapted to run in the background of the vehicle. ODD-compliant locations for respective candidate software are determined, by identifying locations out of the data of crucial locations lying within respective candidate software's ODD. At least a first test-compliant location along at least a first route out of the one or more potential vehicle routes is determined by identifying for at least a first candidate software, locations out of the ODD-compliant locations situated along the at least first route. ## Claims ### Claim 1 A method performed by a test-optimizing system for supporting shadow mode testing of automated driving system, ADS, software comprised in an ADS provided vehicle, the method comprising: retrieving one or more potential vehicle routes; obtaining for a geographical area covering the one or more potential vehicle routes, data of crucial locations associated with past vehicle situations identified as at least one of critical and challenging; retrieving respective operational design domain, ODD, for one or more candidate software respectively adapted to run in a background of the vehicle; determining ODD-compliant locations for respective candidate software, by identifying locations out of the data of crucial locations lying within the ODD of the respective candidate software; determining at least a first test-compliant location along at least a first route out of the one or more potential vehicle routes, by identifying for at least a first candidate software, locations out of the ODD-compliant locations, situated along the at least first route; determining with support from a positioning system, a geographical position of the vehicle along a route selected out of the at least first route; and activating in the background of the vehicle the one or more candidate software out of the at least first candidate software, when the vehicle position is within at least one of a predeterminable distance of and a time range from the at least first test-compliant location. ### Claim 2 (depends on 1) The method according to claim 1, further comprising: selecting a route out of the at least first route in consideration of properties of respective test-compliant locations of the at least first route. ### Claim 3 (depends on 2) The method according to claim 2, wherein the obtained data of crucial locations, comprises obtaining the data from at least one of: accidentology data indicative of at least one of: past various geo-tagged critical; challenging vehicle situations; and vehicle accidents; and at least one of actual and simulated vehicle performance data indicative of past various geo-tagged key performance indicators, KPIs, identified as the at least one of critical and challenging. ### Claim 4 (depends on 1) The method according to claim 1, further comprising: determining with support from a positioning system, a geographical position of the vehicle along a route selected out of the at least first route; and activating in the background of the vehicle the one or more candidate software out of the at least first candidate software, when the vehicle position is within at least one of a predeterminable distance of and a time range from the at least first test-compliant location. ### Claim 5 (depends on 4) The method according to claim 4, wherein the activating comprises activating the one or more candidate software, when the vehicle position is within the at least one of a predeterminable distance of and a time range from the at least first test-compliant location and dynamic ODD conditions for the one or more candidate software are fulfilled. ### Claim 6 (depends on 5) The method according to claim 5, further comprising: storing output data generated by the one or more candidate software. ### Claim 7 (depends on 1) The method according to claim 1, wherein the obtained data of crucial locations, comprises obtaining the data from at least one of: accidentology data indicative of at least one of: past various geo-tagged critical; challenging vehicle situations; and vehicle accidents; and at least one of actual and simulated vehicle performance data indicative of past various geo-tagged key performance indicators, KPIs, identified as the at least one of critical and challenging. ### Claim 8 A test-optimizing system for supporting shadow mode testing of automated driving system, ADS, software comprised in an ADS-provided vehicle, the test-optimizing system comprising: at least one processor configured to: retrieve one or more potential vehicle routes; obtain, for a geographical area covering the one or more potential vehicle routes, data of crucial locations associated with past vehicle situations identified as at least one of critical and challenging; retrieve respective operational design domain, ODD, for one or more candidate software respectively adapted to run in a background of the vehicle; determine ODD-compliant locations for respective candidate software, by identifying locations out of the data of crucial locations lying within the ODD of the respective candidate software; determine at least a first test-compliant location along at least a first route out of the one or more potential vehicle routes, by identifying for at least a first candidate software, locations out of the ODD-compliant locations, situated along the at least first route; determine, with support from a positioning system, a geographical position of the vehicle along a route selected out of the at least first route; and activate, in the background of the vehicle, the one or more candidate software out of the at least first candidate software, when the vehicle position is within at least one of a predeterminable distance of and a time range from the at least first test-compliant location. ### Claim 9 (depends on 8) The test-optimizing system according to claim 8, wherein the at least one processor is further configured to: select a route out of the at least first route in consideration of properties of respective test-compliant locations of the at least first route. ### Claim 10 (depends on 9) The test-optimizing system according to claim 9, wherein the at least one processor is further configured to obtain the data from: accidentology data indicative of at least one of: past various geo-tagged critical; challenging vehicle situations; and vehicle accidents; and at least one of actual and simulated vehicle performance data indicative of past various geo-tagged key performance indicators, KPIs, identified as the at least one of critical and challenging. ### Claim 11 (depends on 8) The test-optimizing system according to claim 8, wherein the at least one processor is further configured to: determine, with support from a positioning system, a geographical position of the vehicle along a route selected out of the at least first route; and activate, in the background of the vehicle, the one or more candidate software out of the at least first candidate software, when the vehicle position is within at least one of a predeterminable distance of and a time range from the at least first test-compliant location. ### Claim 12 (depends on 11) The test-optimizing system according to claim 11, wherein the at least one processor is further configured to activate the one or more candidate software, when the vehicle position is within the at least one of a predeterminable distance of and a time range from the at least first test-compliant location and dynamic ODD conditions for the one or more candidate software are fulfilled. ### Claim 13 (depends on 12) The test-optimizing system according to claim 12, wherein the at least one processor is further configured to: store output data generated by the one or more candidate software. ### Claim 14 (depends on 8) The test-optimizing system according to claim 8, wherein the at least one processor is further configured to obtain the data from: accidentology data indicative of at least one of: past various geo-tagged critical; challenging vehicle situations; and vehicle accidents; and at least one of actual and simulated vehicle performance data indicative of past various geo-tagged key performance indicators, KPIs, identified as the at least one of critical and challenging. ### Claim 15 (depends on 8) The test-optimizing system according to claim 8, wherein the test-optimizing system is comprised in a vehicle. ### Claim 16 A non-transitory computer storage medium storing a computer program containing computer program code configured to cause one of a computer and a processor to perform a method, the method comprising: retrieving one or more potential vehicle routes; obtaining for a geographical area covering the one or more potential vehicle routes, data of crucial locations associated with past vehicle situations identified as at least one of critical and challenging; retrieving respective operational design domain, ODD, for one or more candidate software respectively adapted to run in a background of the vehicle; determining ODD-compliant locations for respective candidate software, by identifying locations out of the data of crucial locations lying within the ODD of the respective candidate software; determining at least a first test-compliant location along at least a first route out of the one or more potential vehicle routes, by identifying for at least a first candidate software, locations out of the ODD-compliant locations, situated along the at least first route; determining with support from a positioning system, a geographical position of the vehicle along a route selected out of the at least first route; and activating in the background of the vehicle the one or more candidate software out of the at least first candidate software, when the vehicle position is within at least one of a predeterminable distance of and a time range from the at least first test-compliant location.