Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 03/04/2026 has been entered.
Response to Amendment
This is in response to applicant’s amendment/response filed on 02/04/2026, which has been entered and made of record. Claims 1, 14, and 18 have been amended. Claim 6 and 16 have been cancelled. Claims 1-5, 7-15, 17-22 are pending in the application.
Response to Arguments
Applicant's arguments filed on 02/04/2026 regarding claims rejection under 35 U.S.C 103 have been fully considered but they are not persuasive.
Applicant submits “Bailly does not disclose the elements of claim 1, as claim 1 requires storing for each tile a set of previous versions of the tile variations of the tile. Bailly does not store variations of a tile but rather stores a local copy on the vehicle and an updated copy on the cloud that can be used to update the local copy of the map on the vehicle.” (Remarks, Page 9.)
The examiner disagrees with Applicant’s premises and conclusion. Bailly teaches storing versions of map tiles in various paragraphs (Bailly, ¶0052, ¶0066, ¶0099, ¶0144, ¶0151, ¶0158). Banerjee also suggests the map tile 702 can be an updated version of the map tile 202, which reflects the one or more change(s) (e.g., 508) in the geographic area 204 (¶0071). Zhou et al. (US Pub 2023/0375363 A1) teaches the second device calculates a map content similarity between a version of each of the plurality of to-be-updated map tiles in the first device and a latest version; and the second device sets the map content similarity for each of the plurality of to-be-updated map tiles in ¶0214. the freshness of the to-be-updated map tiles in the first device is related to versions of the to-be-updated map tiles in the first device in ¶0225.
Applicant submits “Bailly stores a version of the map on the map system and a local version of the map on the vehicle. Bailly updates the vehicle map when the vehicle map is outdated or a change has occurred. Bailly does not store variations of tiles for lighting, weather, or time of day nor does Bailly determine a tile match based on the previous versions and the portion of the image data.” (Remarks, Page 9.)
The examiner disagrees with Applicant’s premises and conclusion. Bailly’s map is stored in local and cloud. Bailly used LIDAR and camera for map data, therefore the tiles have information for lighting. In ¶0176, Bailly determine a tile update based on color changes under different lighting conditions. An updated tile is a portion of the captured image data.
Applicant submits “Bailly does not teach or suggest a process where the tile match itself is "determined based on metadata of each tile," determining whether two tiles match by comparing their metadata. Bailly uses metadata to determine whether the map is up to date based on the metadata. Bailly does not determine whether the tiles "match." Further, in regard to claim 22, Bailly fails to disclose that the metadata comprising time of day, season, or measure of lighting is used to determine a tile match.” (Remarks, Page 9.)
The examiner disagrees with Applicant’s premises and conclusion. Bailly teaches in ¶0149, “the vehicle 150 compares the latitude and longitude coordinates of detected traffic signs to latitudes and longitudes of traffic signs on the map to determine any matches.” “for each matched geometric shape, the vehicle 150 compares the latitude and longitude coordinates between the objects.”, ¶0150, “The vehicle 150 determines that there is a match if the location data and the geometric shape data of a detected object matches the location data and the geometric shape data of a represented object” and ¶0319, “the sensor data may be annotated with certain metadata, such as a timestamp of when the sensor data was collected, a location where the sensor data was collected (e.g., latitude, longitude, and altitude), a map version of the map used by the vehicle (e.g., a production map, a demo map, a beta-testing map, etc.), etc.”. Therefore, Bailly matched the tile based on location, latitude, longitude which are the metadata of the tile containing the objects. Bailly also teaches in ¶0270, “The timestamp allows for the change detection system 1620 to perform a time-based query to find all of the change candidates within a timestamp range (e.g., period of time).“. Therefore, the timestamp is also relied on to determine changes.
Zhou teaches “map content similarities between versions of the plurality of to-be-updated map tiles in the first device and latest versions of the plurality of to-be-updated map tiles, and freshness of the plurality of to-be-updated map tiles in the first device” in ¶0275. Therefore, Zhou teaches updating the map based on timestamp matches update policy.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-5, 7-15, 17-22 are rejected under 35 U.S.C. 103 as being unpatentable over Bailly (US Pub 2021/0004363 A1) in view of Banerjee et al. (US Pub 2018/0253424 A1) and Zhou et al. (US Pub 2023/0375363 A1).
As to claim 1, Bailly discloses a method comprising:
storing, for each tile of a set of image tiles, a set of previous versions comprising variations of the tile, wherein each of the previous versions comprise at least one of a variation in lighting or weather (Bailly, ¶0052, “when the age of various map elements exceed a certain age, the map element may be marked or designated as being ready for an update, and vehicle sensor data from vehicles traversing roadways within the map elements may be obtained to generate an updated version of the map elements, thereby refreshing the map.” ¶0068, “The vehicle sensors 105 may comprise a camera, a light detection and ranging sensor (LIDAR)” “A LIDAR may survey the surroundings of the vehicle by measuring distance to a target by illuminating that target with a laser light pulses and measuring the reflected pulses.” ¶0066, “the online HD map system 110 may determine that the particular portion of the HD map data may be an updated version of the previously received HD map data that was updated by the online HD map system 110 since the particular vehicle 150 last received the previous HD map data.” ¶0099, “if a more recent update is available compared to the version installed on the vehicle 150, the vehicle computing system 120 may be configured to request and receive the latest update and to install it.” ¶0144, “As new versions of the map become available, these or portions of them are pushed to the vehicles in the fleet for use while driving around. The vehicles 150 verify the local copies of the landmark maps, and the online HD map system 110 updates the landmark maps based on the verification results.” ¶0151, “A match record may also include the version (e.g., a version ID) of the HD map that is stored in the local HD map store 275.” ¶0153, “the information sent from the object (e.g., traffic light, traffic sign) may be dynamically controlled, for example, based on various factors such as traffic condition, road condition, or weather condition.” ¶0158, “A mismatch record may also include the version (e.g., a version ID) of the HD map that is stored in the local HD map store 275.” Or claim 8 of the publication, “the map includes multiple versions of the map and the sensor data received from the vehicle includes an annotation of which version of the multiple versions the vehicle uses.”. ¶0176, “This is because the physical environment is subject to change and measurements of the physical environments may contain errors. In various embodiments, the online HD map system 110 verifies the existing occupancy maps and updates the existing occupancy maps. If an object (e.g., a tree, a wall, a barrier, a road surface) moves, appears, or disappears, then the occupancy map is updated to reflect the changes. For example, if a hole appears in a road, a hole has been filled, a tree is cut down, a tree grows beyond a reasonable tolerance, etc., then the occupancy map is updated. If an object's appearance changes, then the occupancy map is updated to reflect the changes. For example, if a road surface's reflectance and/or color changes under different lighting conditions, then the occupancy map is updated to reflect the changes.”)
collecting a portion of image data of a tile of a set of image tiles (¶0178, “The vehicle 150 receives the sensor data concurrently with the vehicle 150 traveling along a route. As described previously, the sensor data (e.g., the sensor data 230) includes, among others, image data, location data, vehicle motion data, and LIDAR scanner data.” ¶0179, “The images capture an environment surrounding the vehicle 150 at the current location from different perspectives.” Fig. 22, ¶0295, “the local sector 2210 may be divided into a quadtree repeatedly until the smallest unit provides a certain likelihood of a vehicle with sensors traveling along routes within the tile 2220. Additionally or alternatively, the local sector 2210 may be subdivided until a single tile 2220 may be completely covered by a single reading of sensor data for a vehicle (e.g., the sensor readings from a vehicle at the center of the vehicle may provide a data set that covers a geographic space that is the same size or larger than the tile 2220.”),
wherein the portion is less than the whole tile of the set of image tiles (¶0304, “the computing system 2350 may gather sensor data from multiple vehicles for a given tile before updating the tile. In these and other embodiments, the heading information may be used to obtain sensor data from vehicles traveling in different directions along the tracks of the tile. For example, certain road signs, environmental elements, lane markings, etc. related to a given map of the tile may be readily observed when traveling in one direction on a two-lane road, but not as readily discerned when traveling in the other direction. In some embodiments, the OMap pipeline 2390 may wait to update a given tile until sufficient sensor data has been collected for that tile (e.g., sensor data of three vehicles for one direction and sensor data of three additional vehicles traveling in the opposite direction).” ¶0318, “if the vehicle is at the periphery of a tile, the sensor data may not sufficiently cover the tile.”);
determining a tile match for the tile by selecting, from the set of previous versions of the set of image tiles a previous version that is determined to be a match based on a comparison of each previous version in the set of previous versions to the portion of the image data of the tile; (Bailly, ¶0052, “when the age of various map elements exceed a certain age, the map element may be marked or designated as being ready for an update, and vehicle sensor data from vehicles traversing roadways within the map elements may be obtained to generate an updated version of the map elements, thereby refreshing the map.” ¶0134, “the change detection module 1660 can be configured to perform an analysis of any point cloud difference that is identified by the localization module 1645, such as by a point cloud difference analysis service (e.g., performs checking of point cloud data for a location to identify matching point cloud data or point cloud data that is different for the location)” ¶0144, “As new versions of the map become available, these or portions of them are pushed to the vehicles in the fleet for use while driving around. The vehicles 150 verify the local copies of the landmark maps, and the online HD map system 110 updates the landmark maps based on the verification results.” ¶0149-¶0151, “The vehicle 150 creates 912 a match record. A match record is a type of a landmark map verification record. A match record corresponds to a particular represented object in the landmark map stored in the local HD map store 275 that is determined to match an object detected by the vehicle 150, which can be referred to as “a verified represented object.” The match record includes the current location of the vehicle 150 and a current timestamp. The match record may also include information about the verified represented object, such as an object ID identifying the verified represented object that is used in the existing landmark map stored in the HD map system HD map store 165. The object ID may be obtained from the local HD map store 275. The match record may further include other information about the vehicle 150 (e.g., a particular make and model, vehicle ID, a current direction (e.g. relative to north), a current speed, a current motion, etc.) A match record may also include the version (e.g., a version ID) of the HD map that is stored in the local HD map store 275.” ¶0158, “A mismatch record may also include the version (e.g., a version ID) of the HD map that is stored in the local HD map store 275.” Or claim 8 of the publication.);
determining whether the portion of the tile is different from a portion of a previous version of the tile (Change Detection System, ¶0122, “the changes to the physical world can be identified by the vehicle 150 and processed so that changes to the HD map can be made.” “The processing of data regarding changes to the physical world can be implemented at least partially by the vehicle 150 to identify a change candidate, and then the data related to the change candidate can be efficiently uploaded to the online HD map system” ¶0123, “The vehicle 150 can be configured to compare the sensor data with the HD map that includes the location that the vehicle 150 is traveling within. The comparison can determine whether there are changes to the surrounding environment of the route, which includes changes to objects on the actual route, changes to objects associated with the actual route, and changes to options for routes.” ¶0127, “Differences between the sensor point cloud data and the HD map point cloud data can be utilized by the change detection system 1620 to determine whether there has been a change at that location, such as a new object in a new object location or a known object being absent.” ¶0133-0134, ¶0299, “a map updates database 2364 (which may store information such as which tiles are designated for update and/or any other data or information used in determining which tiles are to be updated)”);
collecting the image data of one or more images tiles of the set of the image tiles based on the portion of the tile being different from the portion of the previous version of the tile (¶0301, “After a determination has been made that a given tile is to be updated, the update generator 2380 may modify the map updates database 2364 with the tiles that are to be updated. In these and other embodiments, such a change may cause the update server 2355 to request sensor data from vehicles traversing (or that have recently traversed) the map tiles to be updated.”);
examining image deviation data associated with the one or more image tiles of the set of the image tiles used to form a larger set view of a volume of space (¶0052, “the HD Maps and/or map elements may be updated based on the age of the map elements. For example, for certain elements of a map, the map elements may be updated based on the map elements aging beyond a threshold such that the map made up of the map elements retains a certain degree of freshness. In some embodiments, the freshness or staleness of a map (or map elements within the map) may be based on the sensor data used to create the maps. For example, the map elements may be generated based on sensor data received from vehicles, and as the sensor data becomes older the map becomes less reliable because of the dynamic nature of roadways and the surroundings of roadways. In these and other embodiments, when the age of various map elements exceed a certain age, the map element may be marked or designated as being ready for an update, and vehicle sensor data from vehicles traversing roadways within the map elements may be obtained to generate an updated version of the map elements, thereby refreshing the map. For example, once a map element is made from sensor data that is one month old, the map element may be ready to be updated (although any duration of time may be used and is consistent with the present disclosure). In some embodiments, the map elements are tiles such that tiles of a local sector of a map may be used to track the age and update the tiles of the map.” ¶0086, “The 3D map API 265 may be configured to provide access to the spatial 3-dimensional (3D) representation of the road and various physical objects around the road as stored in the local HD map store 275.” “The information describing occupancy may include a hierarchical volumetric grid of some or all positions considered occupied in the HD map.” ¶0107, “the occupancy map 530 may be represented using a 3D volumetric grid of cells at 5-10 cm resolution.”);
determining whether the one or more image tiles of the set are due for revision to update the larger set view of the volume of space based on the image deviation data that is examined (¶0122, “the changes to the physical world can be identified by the vehicle 150 and processed so that changes to the HD map can be made. The analysis of changes to the physical world can be performed at least partially by the vehicle 150 so that any data related to a change in the physical world can be packaged for efficient delivery to the online HD map system 110.” “The processing of data regarding changes to the physical world can be implemented at least partially by the vehicle 150 to identify a change candidate, and then the data related to the change candidate can be efficiently uploaded to the online HD map system 110.” ¶0123, “The HD maps may be updated with changes to the physical world. For example, a vehicle 150 that is driving along a route can use sensors to sense the physical world in order to capture sensor data. The vehicle 150 can be configured to compare the sensor data with the HD map that includes the location that the vehicle 150 is traveling within. The comparison can determine whether there are changes to the surrounding environment of the route, which includes changes to objects on the actual route, changes to objects associated with the actual route, and changes to options for routes.”); and
one or more of (a) scheduling a first vehicle to move through or by the volume of space with one or more sensors to capture one or more updated image tiles or (b) identifying a second vehicle that is moving through, by, or toward the volume of space with the one or more sensors to capture the one or more updated image tiles responsive to determining that the one or more image tiles of the set are due for revision (¶0203, “The vehicle ranking module 1320 ranks vehicles 150 based on various criteria to determine whether the map data collection module 460 should send a request to a vehicle 150 to provide additional map data for a specific location.” ¶0205, “The map data request module 1330 selects a vehicle for requesting additional map data for specific location and sends a request to the vehicle. The map data request module 1330 sends a request via the vehicle interface module 160 and also receives additional map data via the vehicle interface module 160. The map data request module 1330 selects a vehicle 150 based on various criteria including the vehicle ranking determined by the vehicle ranking module 1320 and a level or urgency associated with the map discrepancy, and a rate at which vehicles drive through that location of the street. In an embodiment, the map data request modules 1330 preferentially selects vehicles 150 which have data for the specific location recorded during daylight hours over vehicles 150 with data recorded at dawn, dusk, or night.”).
Bailly teaches all limitations of the claim. For sake of addressing applicant’s argument, examiner in addition provides Banerjee to teach the obviousness of the claim below.
Banerjee also teaches collecting a portion of image data of a tile of a set of image tiles (Banerjee, abstract, “obtaining data descriptive of an image depicting at least the portion of the geographic area. The image is acquired by an image acquisition system.”),
wherein the portion is less than the whole tile of the set of image tiles (Banerjee, ¶0028, “the computing system can split the map tile (e.g., depicting the geographic area) into a first plurality of cells. The computing system can split the image of the geographic area into a second plurality of cells. Each cell can depict a target, sub-region (e.g., land plot) of the larger geographic area (e.g., neighborhood). The computing system can select a first cell from the first plurality of cells and a corresponding second cell from the second plurality of cells. For example, the first cell and the second cell can be associated with the same (or similar), sub-region of the geographic area. The computing system can input data descriptive of the first and second cells into the machine-learned binary classifier model. This data can include the portion of the imagery (e.g., the individual pixels) represented in the individual cell, as well as the visual characteristics associated therewith” ¶0057, “the computing device(s) 106 can identify a first plurality of cells 502A associated with the map tile 202 and a second plurality of cells 502B associated with the image 302. A cell can be a portion of a map tile or image. A cell can include, for instance, an area made up of pixels of the respective map tile or image.”);
determining whether the portion of the tile is different from a portion of a previous version of the tile (Banerjee, abstract, “analyzing the data descriptive of the map tile and the data descriptive of the image to determine an occurrence of a change associated with the geographic area.” ¶0020, “obtain an image depicting the neighborhood shown in the particular map tile (e.g., from an image database). The image can be, for instance, one that has been recently captured by an image-capturing platform (e.g., automobile, aircraft, satellite) of an image acquisition system. The computing system can analyze the map tile and the image to determine an occurrence of a change within the neighborhood depicted in the particular map tile and the corresponding image. In particular, in one example, the computing system can use a machine-learned binary classifier model to evaluate the map tile and the image to identify a change in buildings, roads, etc. within various sub-regions (e.g., land plots) within the neighborhood.”);
collecting the image data of one or more images tiles of the set of the image tiles based on the portion of the tile being different from the portion of the previous version of the tile (Banerjee, abstract, “updating the map interface to reflect the change associated with the geographic area based at least in part on the occurrence of the change associated with the geographic area.” ¶0029, “This process can be repeated for other cells of the map tile and image to identify the occurrence of change within multiple sub-regions of the geographic area.”).
Bailly and Banerjee are considered to be analogous art because all pertain to updating a map tile. It would have been obvious before the effective filing date of the claimed invention to have modified Bailly with the features of “collecting a portion of image data of a tile of a set of image tiles, wherein the portion is less than the whole tile of the set of image tiles; determining whether the portion of the tile is different from a portion of a previous version of the tile; collecting the image data of one or more images tiles of the set of the image tiles based on the portion of the tile being different from the portion of the previous version of the tile” as taught by Banerjee. The suggestion/motivation would have been in order to updating the map tile to reflect the change associated with the geographic area based on the occurrence of the change associated with the geographic area (Banerjee, ¶0004).
Zhou also suggest “storing, for each tile of a set of image tiles, a set of previous versions comprising variations of the tile, wherein each of the previous versions comprise at least one of a variation in lighting or weather” and “determining a tile match for the tile by selecting, from the set of previous versions of the set of image tiles a previous version that is determined to be a match based on a comparison of each previous version in the set of previous versions to the portion of the image data of the tile” (Zhou, ¶0003, “Generally, the map in the vehicle is managed based on map tiles. A map tile is a raster image that is obtained by slicing a map region into several rows and columns based on a specific size and format, a zoom level, or a scale. When the map is updated, the vehicle downloads the latest version of the map tile from the cloud to update the map.” ¶0102, “the map in the vehicle is managed based on map tiles. A map tile is a raster image that is obtained by slicing a map region into several rows and columns based on a specific size and format, a zoom level, or a scale. When the map is updated, the vehicle downloads the latest version of the map tile from the cloud to update the map. For example, to accelerate map update, incremental update is used to update the map, and only changed map tiles are updated, thereby reducing an amount of map update data.” ¶0173, “the first device compares the coordinate information of the to-be-updated map tiles with coordinate information of tiles used for path planning, to obtain the update policy.” ¶0215, “A map content similarity can be calculated based on an image similarity. Image similarity calculation includes feature extraction and feature comparison.”” The second device may perform feature comparison by using algorithms such as a Hamming distance algorithm and/or a cosine similarity algorithm.” ¶0225, “the freshness of the to-be-updated map tiles in the first device is related to versions of the to-be-updated map tiles in the first device.” ¶0275, “map content similarities between versions of the plurality of to-be-updated map tiles in the first device and latest versions of the plurality of to-be-updated map tiles, and freshness of the plurality of to-be-updated map tiles in the first device”)
Bailly, Banerjee and Zhou are considered to be analogous art because all pertain to updating a map tile. It would have been obvious before the effective filing date of the claimed invention to have modified Bailly with the features of “storing , for each tile of a set of image tiles, a set of previous versions comprising variations of the tile, wherein each of the previous versions comprise at least one of a variation in lighting or weather” and “determining a tile match for the tile by selecting, from the set of previous versions of the set of image tiles a previous version that is determined to be a match based on a comparison of each previous version in the set of previous versions to the portion of the image data of the tile” as taught by Zhou. The suggestion/motivation would have been in order to reducing an amount of map update data (Zhou, ¶0102).
As to claim 2, claim 1 is incorporated and Bailly discloses the image deviation data include a difference between image data of a first image tile of the one or more image tiles and image data of a second image tile of the one or more image tiles (Bailly, ¶0122, “Any changes to the physical world that may impact the route can be made to the corresponding HD map so that the vehicles 150 can navigate the route in response to the at least one change. In some aspects, the changes to the physical world can be identified by the vehicle 150 and processed so that changes to the HD map can be made.” ¶0123, “The online HD map system 110 can collect the map change candidate information from multiple vehicles 150 driving along a route to determine whether the map change candidate information is accurate or erroneously reported by a vehicle 150.”).
As to claim 3, claim 1 is incorporated and Bailly discloses the image deviation data include a time difference between a first time at which a first image tile of the one or more image tiles was obtained and image data of a second image tile of the one or more image tiles was obtained (Bailly, ¶0293, “once a map element is made from sensor data that is one month old, the map element may be ready to be updated” ¶0300, “the computing system 2350 may periodically scan the statistics to find any tiles that have aged beyond a threshold.” ¶0313)
As to claim 4, claim 1 is incorporated and Bailly discloses at least one of the one or more image tiles in the set is a combination of different sensor outputs (Bailly, ¶0055, “The online HD map system 110 may be configured to receive sensor data that may be captured by vehicle sensors 105 (e.g., 105a-105d) of the vehicles 150 and combine data received from the vehicles 150 to generate and maintain HD maps.” ¶0060, “the sensor data may include LIDAR data, captured images, etc. Additionally or alternatively, the sensor data may include information that may describe the current state of the vehicle 150, the location and motion parameters of the vehicles 150” ¶0304, “the computing system 2350 may gather sensor data from multiple vehicles for a given tile before updating the tile.” “the OMap pipeline 2390 may wait to update a given tile until sufficient sensor data has been collected for that tile”).
As to claim 5, claim 1 is incorporated and Bailly discloses the larger set view of the image tiles includes two or more images, video frames, or data output from an optical sensor that are stitched together to form the larger set view of the volume of space (Bailly, ¶0060, the sensor data may include LIDAR data, captured images, etc. ¶0068, “The vehicle sensors 105 may include one or more cameras that may capture images of the surroundings of the vehicle. A LIDAR may survey the surroundings of the vehicle by measuring distance to a target by illuminating that target with a laser light pulses and measuring the reflected pulses.’ ¶0110, “Each geographical region may represent a contiguous area bounded by a geometric shape, for example, a rectangle or square.” ¶0181, “The vehicle 150 registers 1108 the images of the surroundings with the occupancy map. In other words, the vehicle 150 transforms 2D image information into the 3D coordinate system of the occupancy map. For example, the vehicle 150 maps points, lines, and surfaces in the stereo images to points, lines, and surfaces in the 3D coordinate system. The vehicle 150 also registers LIDAR scanner data with the occupancy map. The vehicle 150 thereby creates a 3D representation of the environment surrounding the vehicle 150 using the images, the LIDAR scanner data, and the occupancy map. As such, the vehicle 150 creates a 3D representation of the surroundings.”).
As to claim 7, claim 1 is incorporated and Bailly discloses determining whether the one or more image tiles of the set are due for revision includes determining whether a data content of a previously obtained image tile of the one or more image tiles differs from a data content of a more recently obtained image tile by more than a threshold content amount (Bailly, ¶0008, “based on the age exceeding a threshold age, determining that the tile of the map is to be updated.” ¶0189, “the vehicle 150 calculates a significance value for a particular discrepancy according to predetermined rules and compares the significance value to a threshold value to evaluate whether the discrepancy is significant.” ¶0206, “An outdated map alert may be sent requesting a refresh of the map data unit if either the oldest timestamp or newest timestamp of that data unit is older than a respective threshold age.”).
As to claim 8, claim 1 is incorporated and Bailly discloses determining whether the one or more image tiles of the set are due for revision includes determining whether a time period between (c) an earlier time when a data content of a previously obtained image tile of the one or more image tiles was obtained and (d) a later time when a data content of a more recently obtained image tile was obtained is longer than a threshold time period (Bailly, ¶0008, “based on the age exceeding a threshold age, determining that the tile of the map is to be updated.” ¶0206, “An outdated map alert may be sent requesting a refresh of the map data unit if either the oldest timestamp or newest timestamp of that data unit is older than a respective threshold age.”).
As to claim 9, claim 1 is incorporated and Bailly discloses the one or more of (a) scheduling the first vehicle or (b) identifying the second vehicle includes directing the first vehicle or the second vehicle to use an onboard sensor to sense data for updating at least one of the image tiles that is older than one or more others of the image tiles or that is associated with an increased frequency of prior changes (Bailly, ¶0008, “based on the age exceeding a threshold age, determining that the tile of the map is to be updated. The method may additionally include transmitting an update message to a vehicle traversing a track within the tile, where the update message includes instructions to cause the vehicle to gather and submit sensor data to a computing system.” ¶0229, “the online HD map system 110 tracks the route handshakes as described above, and maintains a database of route coverage frequency. If a given route is covered N times a day by vehicles 150, and the online HD map system 110 ensures that the latest and oldest data for that route is within a given period of time (our freshness constraint). The online HD map system 110 estimates how often the online HD map system 110 needs an update to keep this freshness constraint (statistically).”).
As to claim 10, claim 1 is incorporated and Bailly discloses the one or more of (a) scheduling the first vehicle or (b) identifying the second vehicle includes directing the first vehicle or the second vehicle to use an onboard sensor of the one or more sensors to sense partial data of a sampled part, but not all, of at least one of the image tiles, and further comprising: examining the partial data of the at least one of the image tiles that is sensed by the onboard sensor to determine whether the partial data of the at least one of the image tiles indicates that the at least one of the image tiles has changed (Bailly, Change Detection System, ¶0121-0143).
As to claim 11, claim 10 is incorporated and Bailly discloses updating a timestamp of the at least one of the image tiles associated with the partial data responsive to determining that the at least one of the image tiles has not changed; or directing the onboard sensor to obtain additional data of an entirety of the at least one of the image tiles responsive to determining that the at least one of the image tiles has changed (Bailly, ¶0150, “The vehicle 150 determines 910 if there are any matches between the objects it detected and those on the map based on the comparison. The vehicle 150 determines that there is a match if the location data and the geometric shape data of a detected object matches the location data and the geometric shape data of a represented object, respectively. As described herein, a match refers to a difference between data being within a predetermined threshold.” ¶0151, “The vehicle 150 creates 912 a match record. A match record is a type of a landmark map verification record. A match record corresponds to a particular represented object in the landmark map stored in the local HD map store 275 that is determined to match an object detected by the vehicle 150, which can be referred to as “a verified represented object.” The match record includes the current location of the vehicle 150 and a current timestamp. The match record may also include information about the verified represented object, such as an object ID identifying the verified represented object that is used in the existing landmark map stored in the HD map system HD map store 165.” ¶0158, “A mismatch record includes a mismatch record type, the current location (e.g., latitude and longitude coordinates) of the vehicle 150, and a current timestamp.” ¶0162, “For each created landmark map verification record, the vehicle 150 determines 916 whether to report the record. The vehicle 150 may report landmark map verification records periodically. For example, the vehicle 150 reports verification records every predetermined time interval.” ¶0174, “The HD map system 110 associates the change record with a timestamp” ¶0299, “a computing system 2350 may communicate with a vehicle 2310 to obtain sensor data from the vehicle to update the maps based on certain conditions.” “a map updates database 2364 (which may store information such as which tiles are designated for update and/or any other data or information used in determining which tiles are to be updated), and/or a map statistics database 2366 (which may store information such as statistics for individual tiles (e.g., a vector with information such as a tile identifier, a timestamp of the sensor data used to create the tile, a relative altitude of the tile, a quantization level of the tile, etc.), statistics for local sectors of a map, statistics for OMaps, statistics for LMaps, statistics for HD maps, etc.). The computing system 2350 may additionally utilize a visualizer 2370 that may facilitate visualization of ages of map elements such as tiles, an update generator 2380 that may utilize information from one or more of the databases to determine which tiles are to be upgraded, and/or an OMap pipeline 2390 that may be used to track and or update map statistics (such as those stored in the map statistics database 2366) as map information is updated and as new maps are drawn.” ¶0270, “the change detection module 1660 or change management module 1625 can be configured to label each change candidate with a timestamp. The timestamp allows for the change detection system 1620 to perform a time-based query to find all of the change candidates within a timestamp range (e.g., period of time). In some aspects, the change candidates may be generated or provided to the change management system 1625 out of order from the order in which the relevant sensor data was acquired. For example, the change candidates being out of order may be due to different delays from the perception module 1610 or perception integration module 1615. The timestamp can be obtained from the source sensor data module 1630 that is retained therewith during processing and generation of a change candidate. When multiple change candidates relate to the same lane closure object, the timestamp can be the creation timestamp of the sensor data. A timestamp based query can be used by HD map update module 1650 to upload the final change candidates to the online HD map system 110.” ¶0300, “the vehicle 2310 may upload a set of coordinates along which the vehicle 2310 has traversed, and the computing system 2350 may convert those coordinates to a corresponding map tile, and may determine whether the map of the tile is outdated. In some embodiments, such decisions may be made within the vehicle, without the help of computing system 2350, as the vehicle knows about its trajectory and the local tile can contain the timestamps used in rendering the decision.”).
As to claim 12, claim 11 is incorporated and Bailly discloses one or more of (c) scheduling a third vehicle to move through or by the volume of space with the one or more sensors to capture the one or more updated image tiles or (d) identifying a fourth vehicle that is moving through, by, or toward the volume of space with the one or more sensors to capture the one or more updated image tiles responsive to determining that the at least one of the image tiles has changed by more than a threshold amount (Bailly, ¶0304, “the computing system 2350 may gather sensor data from multiple vehicles for a given tile before updating the tile. In these and other embodiments, the heading information may be used to obtain sensor data from vehicles traveling in different directions along the tracks of the tile. For example, certain road signs, environmental elements, lane markings, etc. related to a given map of the tile may be readily observed when traveling in one direction on a two-lane road, but not as readily discerned when traveling in the other direction. In some embodiments, the OMap pipeline 2390 may wait to update a given tile until sufficient sensor data has been collected for that tile (e.g., sensor data of three vehicles for one direction and sensor data of three additional vehicles traveling in the opposite direction)”).
As to claim 13, claim 1 is incorporated and Bailly discloses communicating the set of the image tiles to at least a third vehicle for the at least the third vehicle to control or change movement of the at least the third vehicle while the at least the third vehicle is moving through the volume of space (Bailly, ¶0077, “The planning module 220 may also be configured to use the information from the prediction module 215 and the route 240 to plan a sequence of actions that the vehicle 150 may take within a short time interval, for example, within the next few seconds. In some embodiments, the planning module 220 may be configured to specify a sequence of actions as one or more points representing nearby locations that the vehicle 150 may drive through next. The planning module 220 may be configured to provide, to the control module 225, the details of a plan comprising the sequence of actions to be taken by the corresponding vehicle 150.” ¶0218, “The vehicle 150 receives 1510 map data from the online HD map system 110 comprising HD maps for a geographical region. The vehicle 150 then receives 1520 sensor data 230 describing a particular location through which the vehicle 150 is driving.” ¶0233, “The autonomous vehicle 150 is also configured to load HD map data for the region through which the autonomous vehicle 150 is driving. The vehicle computing system 120, such as by the change detection system 1620, compares the sensor data from a sensor data module 1630 with the HD map data to determine whether the sensor data matches the HD map data. For example, the comparison can be used to perform a localization analysis in order to determine a pose of the vehicle 150.”).
As to claim 14, Bailly discloses a system comprising: one or more processors configured to store, for each tile of a set of image tiles, a set of previous versions comprising variations of the tile, wherein each of the previous versions comprise at least one of a variation in lighting or weather, the one or more processors configured to collect a portion of image data of a tile of the set of image tiles, wherein the portion is less than the whole tile of the set of image tiles, the one or more processors configured to determine a tile match for the tile by selecting, from the set of previous versions of the set of image tiles a previous version that is determined to be a match based on a comparison of each previous version in the set of previous versions to the portion of the image data of the tile, the one or more processors configured to determine whether the portion of the tile is different from a portion of the match previous version of the tile, the one or more processors configured to collect the image data of one or more images tiles of the set of the image tiles based on the portion of the tile being different from the portion of the previous version of the tile one or more processors configured to examine image deviation data associated with one or more image tiles of a set of the image tiles used to form a larger set view of a volume of space, the one or more processors configured to determine whether the one or more image tiles of the set are due for revision to update the larger set view of the volume of space based on the image deviation data that is examined (See claim 1 for detailed analysis.),
the one or more processors configured to calculate a frequency of change for the one or more images tiles based on the image deviation data (Bailly, Change Detection System, ¶0122, “the changes to the physical world can be identified by the vehicle 150 and processed so that changes to the HD map can be made.” “The processing of data regarding changes to the physical world can be implemented at least partially by the vehicle 150 to identify a change candidate, and then the data related to the change candidate can be efficiently uploaded to the online HD map system” ¶0123, “The vehicle 150 can be configured to compare the sensor data with the HD map that includes the location that the vehicle 150 is traveling within. The comparison can determine whether there are changes to the surrounding environment of the route, which includes changes to objects on the actual route, changes to objects associated with the actual route, and changes to options for routes.” ¶0127, “Differences between the sensor point cloud data and the HD map point cloud data can be utilized by the change detection system 1620 to determine whether there has been a change at that location, such as a new object in a new object location or a known object being absent.” ¶0244, The online HD map system 110 can be configured to combine the information obtained from a plurality of vehicles 150 to select the appropriate change candidate for the lane modification proposals that have the highest frequency in the change candidate for the lane modification proposals that are received from the plurality of vehicles 150.” ¶0245, “the dynamic layer represents information that changes at a higher frequency than the information in the base layer, such as for lane closure information that may change in hours, days, or weeks. The online HD map system 110 can be configured to store the lane closure information as part of the dynamic layer of an HD map.”),
the one or more processors also configured to one or more of (a) schedule a first vehicle to move through or by the volume of space with one or more sensors to capture one or more updated image tiles or (b) identify a second vehicle that is moving through, by, or toward the volume of space with the one or more sensors to capture the one or more updated image tiles responsive to determining that the one or more image tiles of the set are due for revision (See claim 1 for detailed analysis.).
Bailly teaches all limitations of the claim. For sake of addressing applicant’s argument, examiner in addition provides Banerjee to teach the obviousness of the claim below.
Banerjee teaches the one or more processors configured to calculate a frequency of change for the one or more images tiles based on the image deviation data (Banerjee, ¶0020, “if the neighborhood is experiencing a high level of change, the computing system can also task the image acquisition system to more frequently acquire images associated with the neighborhood, such that the system can monitor and detect future changes in the neighborhood. In this way, the computing system can use the detection of change within a geographic area to more efficiently refresh the map tiles of a map interface, increasing the accuracy of the map interface.” ¶0033, “geographic areas that are undergoing a rapid increase in infrastructure, with an accompanying increase in the number of roads and/or buildings can be updated more frequently than those in which there are few changes taking place over time.”).
Bailly and Banerjee are considered to be analogous art because all pertain to updating a map tile. It would have been obvious before the effective filing date of the claimed invention to have modified Bailly with the features of “calculate a frequency of change for the one or more images tiles based on the image deviation data” as taught by Banerjee. The suggestion/motivation would have been in order to updating the map tile to reflect the change associated with the geographic area based on the occurrence of the change associated with the geographic area (Banerjee, ¶0004).
Zhou also suggest “storing, for each tile of a set of image tiles, a set of previous versions comprising variations of the tile, wherein each of the previous versions comprise at least one of a variation in lighting or weather” and “determining a tile match for the tile by selecting, from the set of previous versions of the set of image tiles a previous version that is determined to be a match based on a comparison of each previous version in the set of previous versions to the portion of the image data of the tile” (Zhou, ¶0003, “Generally, the map in the vehicle is managed based on map tiles. A map tile is a raster image that is obtained by slicing a map region into several rows and columns based on a specific size and format, a zoom level, or a scale. When the map is updated, the vehicle downloads the latest version of the map tile from the cloud to update the map.” ¶0102, “the map in the vehicle is managed based on map tiles. A map tile is a raster image that is obtained by slicing a map region into several rows and columns based on a specific size and format, a zoom level, or a scale. When the map is updated, the vehicle downloads the latest version of the map tile from the cloud to update the map. For example, to accelerate map update, incremental update is used to update the map, and only changed map tiles are updated, thereby reducing an amount of map update data.” ¶0173, “the first device compares the coordinate information of the to-be-updated map tiles with coordinate information of tiles used for path planning, to obtain the update policy.” ¶0215, “A map content similarity can be calculated based on an image similarity. Image similarity calculation includes feature extraction and feature comparison.”” The second device may perform feature comparison by using algorithms such as a Hamming distance algorithm and/or a cosine similarity algorithm.” ¶0225, “the freshness of the to-be-updated map tiles in the first device is related to versions of the to-be-updated map tiles in the first device.” ¶0275, “map content similarities between versions of the plurality of to-be-updated map tiles in the first device and latest versions of the plurality of to-be-updated map tiles, and freshness of the plurality of to-be-updated map tiles in the first device”)
Bailly, Banerjee and Zhou are considered to be analogous art because all pertain to updating a map tile. It would have been obvious before the effective filing date of the claimed invention to have modified Bailly with the features of “storing , for each tile of a set of image tiles, a set of previous versions comprising variations of the tile, wherein each of the previous versions comprise at least one of a variation in lighting or weather” and “determining a tile match for the tile by selecting, from the set of previous versions of the set of image tiles a previous version that is determined to be a match based on a comparison of each previous version in the set of previous versions to the portion of the image data of the tile” as taught by Zhou. The suggestion/motivation would have been in order to reducing an amount of map update data (Zhou, ¶0102).
As to claim 15, claim 14 is incorporated and Bailly discloses the image deviation data include one or more of: a difference between image data of a first image tile of the one or more image tiles and image data of a second image tile of the one or more image tiles; or a time difference between a first time at which a first image tile of the one or more image tiles was obtained and image data of a second image tile of the one or more image tiles was obtained (See claim 2-3 for detailed analysis.)
As to claim 17, claim 14 is incorporated and Bailly discloses determining whether the one or more image tiles of the set are due for revision includes determining whether a data content of a previously obtained image tile of the one or more image tiles differs from a data content of a more recently obtained image tile by more than a threshold content amount (See claim 7 for detailed analysis.)
As to claim 18, Bailly discloses a system comprising: a controller configured to store, for each tile of a set of image tiles, a set of previous versions comprising variations of the tile, wherein each of the previous versions comprise at least one of a variation in lighting or weather, the controller configured to collect a portion of image data of a tile of the set of image tiles, wherein the portion is less than the whole tile of the set of image tiles, the controller configured to determine a tile match for the tile by selecting, from the set of previous versions of the set of image tiles a previous version that is determined to be a match based on a comparison of each previous version in the set of previous versions to the portion of the image data of the tile, the controller configured to determine whether the portion of the tile is different from a portion of the match previous version of the tile, the controller configured to collect the image data of one or more images tiles of the set of the image tiles based on the portion of the tile being different from the portion of the previous version of the tile, a controller configured to examine image deviation data associated with one or more image tiles of a set of the image tiles used to form a larger set view of a volume of space, the controller also configured to determine whether the one or more image tiles of the set are due for revision to update the larger set view of the volume of space based on the image deviation data that is examined, the controller configured to direct a vehicle that is moving through, by, or toward the volume of space with one or more onboard sensors to capture partial data of the one or more updated image tiles responsive to determining that the one or more image tiles of the set are due for revision, the controller configured to examine the partial data to determine whether the partial data indicates that the one or more updated image tiles has changed, the controller configured to update a timestamp of the one or more updated image tiles responsive to determining that the one or more updated image tiles has not changed, or direct the one or more sensors to obtain additional data of an entirety of the one or more updated image tiles responsive to determining that the one or more updated image tiles has changed (See claim 1, 10-11 for detailed analysis.),
the control configured to update a time that the one or more image tiles are due for revision based on the image deviation data (Bailly, ¶0051, “freshness of data such that a map may be updated to reflect changes on the road within a threshold time frame, for example, within days, hours, minutes or seconds” ¶0052, “once a map element is made from sensor data that is one month old, the map element may be ready to be updated (although any duration of time may be used and is consistent with the present disclosure” ¶0151, “The match record includes the current location of the vehicle 150 and a current timestamp.” ¶0158, “A mismatch record includes a mismatch record type, the current location (e.g., latitude and longitude coordinates) of the vehicle 150, and a current timestamp.” ¶0219, “Using the comparison, the vehicle 150 determines 1540 whether there is a discrepancy between the sensor data and map data.” ¶0244, The online HD map system 110 can be configured to combine the information obtained from a plurality of vehicles 150 to select the appropriate change candidate for the lane modification proposals that have the highest frequency in the change candidate for the lane modification proposals that are received from the plurality of vehicles 150.” ¶0245, “the dynamic layer represents information that changes at a higher frequency than the information in the base layer, such as for lane closure information that may change in hours, days, or weeks. The online HD map system 110 can be configured to store the lane closure information as part of the dynamic layer of an HD map.”).
Bailly teaches all limitations of the claim. For sake of addressing applicant’s argument, examiner in addition provides Banerjee to teach the obviousness of the claim below.
Banerjee teaches the control configured to update a time that the one or more image tiles are due for revision based on the image deviation data (Banerjee, ¶0033, “the rate at which individual map tiles are updated will reflect the amount of change occurring in the areas represented by the tiles. For example, geographic areas that are undergoing a rapid increase in infrastructure, with an accompanying increase in the number of roads and/or buildings can be updated more frequently than those in which there are few changes taking place over time.”).
Bailly and Banerjee are considered to be analogous art because all pertain to updating a map tile. It would have been obvious before the effective filing date of the claimed invention to have modified Bailly with the features of “the control configured to update a time that the one or more image tiles are due for revision based on the image deviation data” as taught by Banerjee. The suggestion/motivation would have been in order to allow the computing technology to efficiently update a map interface at appropriate times, while increasing the accuracy of the map interface to reflect more current conditions within a depicted geographic area (Banerjee, ¶0034).
Zhou also suggest “storing, for each tile of a set of image tiles, a set of previous versions comprising variations of the tile, wherein each of the previous versions comprise at least one of a variation in lighting or weather” and “determining a tile match for the tile by selecting, from the set of previous versions of the set of image tiles a previous version that is determined to be a match based on a comparison of each previous version in the set of previous versions to the portion of the image data of the tile” (Zhou, ¶0003, “Generally, the map in the vehicle is managed based on map tiles. A map tile is a raster image that is obtained by slicing a map region into several rows and columns based on a specific size and format, a zoom level, or a scale. When the map is updated, the vehicle downloads the latest version of the map tile from the cloud to update the map.” ¶0102, “the map in the vehicle is managed based on map tiles. A map tile is a raster image that is obtained by slicing a map region into several rows and columns based on a specific size and format, a zoom level, or a scale. When the map is updated, the vehicle downloads the latest version of the map tile from the cloud to update the map. For example, to accelerate map update, incremental update is used to update the map, and only changed map tiles are updated, thereby reducing an amount of map update data.” ¶0173, “the first device compares the coordinate information of the to-be-updated map tiles with coordinate information of tiles used for path planning, to obtain the update policy.” ¶0215, “A map content similarity can be calculated based on an image similarity. Image similarity calculation includes feature extraction and feature comparison.”” The second device may perform feature comparison by using algorithms such as a Hamming distance algorithm and/or a cosine similarity algorithm.” ¶0225, “the freshness of the to-be-updated map tiles in the first device is related to versions of the to-be-updated map tiles in the first device.” ¶0275, “map content similarities between versions of the plurality of to-be-updated map tiles in the first device and latest versions of the plurality of to-be-updated map tiles, and freshness of the plurality of to-be-updated map tiles in the first device”)
Bailly, Banerjee and Zhou are considered to be analogous art because all pertain to updating a map tile. It would have been obvious before the effective filing date of the claimed invention to have modified Bailly with the features of “storing , for each tile of a set of image tiles, a set of previous versions comprising variations of the tile, wherein each of the previous versions comprise at least one of a variation in lighting or weather” and “determining a tile match for the tile by selecting, from the set of previous versions of the set of image tiles a previous version that is determined to be a match based on a comparison of each previous version in the set of previous versions to the portion of the image data of the tile” as taught by Zhou. The suggestion/motivation would have been in order to reducing an amount of map update data (Zhou, ¶0102).
As to claim 19, claim 18 is incorporated and Bailly discloses the vehicle is a first vehicle, and the controller is configured to one or more of schedule a second vehicle to move through or by the volume of space with the one or more sensors to capture the one or more updated image tiles or identify a third vehicle that is moving through, by, or toward the volume of space with the one or more sensors to capture the one or more updated image tiles responsive to determining that the one or more image tiles has changed by more than a threshold amount (See claim 9 and 12 for detailed analysis.).
As to claim 20, claim 18 is incorporated and Bailly discloses the vehicle is a first vehicle, and the controller is configured to communicate the set of the image tiles to at least a second vehicle for the at least the second vehicle to control or change movement of the at least the second vehicle while the at least the second vehicle is moving through the volume of space (See claim 13 for detailed analysis.).
As to claim 21, claim 1 is incorporated and Bailly discloses the tile match is determined based on metadata of each tile of the set of image tiles (Bailly, ¶0200, “The status update message includes metadata describing any map discrepancies identified by the vehicle 150 indicating differences between the map data that the online HD map system 110 provided to the vehicle 150 and the sensor data that is received by the vehicle 150 from its vehicle sensors 105.” ¶0319, “the sensor data may be annotated with certain metadata, such as a timestamp of when the sensor data was collected, a location where the sensor data was collected (e.g., latitude, longitude, and altitude), a map version of the map used by the vehicle (e.g., a production map, a demo map, a beta-testing map, etc.), etc.”).
As to claim 22, claim 21 is incorporated and Bailly discloses the metadata comprises contextual information of the tile comprising at least one of time of day, season, or measure of lighting (Bailly, ¶0204, “The rate at which vehicles 150 drive on that portion of the street may be specified as an average number of vehicles 150 that drive on that street in a given time, for example, every hour. In an embodiment, the street metadata store 1350 also stores the rate at which vehicles 150 travel on a portion of the street at particular times, for example, night time, morning, evening, and so on.” ¶0215, “a time of day at which the identified vehicle 150 traverses the particular location, or time of day (e.g., sunlight direction) versus direction of travel, as this may affect quality of the camera data.” ¶0319, “the sensor data may be annotated with certain metadata, such as a timestamp of when the sensor data was collected, a location where the sensor data was collected (e.g., latitude, longitude, and altitude), a map version of the map used by the vehicle (e.g., a production map, a demo map, a beta-testing map, etc.), etc.”)).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to YU CHEN whose telephone number is (571)270-7951. The examiner can normally be reached on M-F 8-5 PST Mid-day flex.
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/YU CHEN/Primary Examiner, Art Unit 2613
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